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9,988 | https://devpost.com/software/myfacemaskapp | Prototype model 1 "Dany" pink opaque
Prototype model 1 "Dany" white opaque
AiRFace.it (App)
A new customizable, economic and ecological mask tailored to you
Millions of disposable masks are thrown out every day, which in addition to having a significant environmental impact on nature also have a high monetary expenditure.
To meet all these needs, the
AiRFace.it App
team has developed a project that allows the customization of the mask or the creation of transparent masks that can adapt to the features and therefore customizable by scanning the face in 3D.
This is
AiRFace.it App
, a mobile application that can be downloaded free on IOS and Android devices.
The scanning process is quick and easy: it happens through the use of the mobile phone camera.
In addition, the material used in the production of the masks, biodegradable and hypoallergenic allows a repeated use, being able to sterilize the washing at high temperatures .
The mask is therefore ergonomic and environmentally friendly, because you just need to change the filters.
The 3D model can also be printed from the comfort of the house without leaving. The advantage is that, being custom-built, the signs released by normal masks after hours of use will be reduced.
Considering the difficult and delicate situation we are experiencing,
AiRFace.it App
would ensure protection and prevention with zero impact on the environment and would meet individual needs.
It would be an optimal solution, without going out to buy it if you already have a 3D printer or otherwise we print and deliver directly to your home! The App is free as well as the availability of the various basic 3D models.
Ergonomic
My face mask with its 3D scanning process, allows you to create ergonomic masks suitable for every feature of your face. This custom adaptation will allow you to reduce the marks released by normal masks after hours of use.
3d Printer
The realization of the 3D masks allows anyone to create them independently.
In fact, a 3D printer and a mobile phone are enough to quickly create personalized templates based on the desired quantity.
Ecological
The material of these masks is absolutely ecological, a very important feature if you consider high consumption
daily, especially in
some sectors.
In fact, these masks can
be reused several times later
washing at high temperatures which allows sterilization.
Trasparent
One of the main features of AiRFace.it is transparency.
The idea of making these masks with a transparent material was born mainly from the awareness of the importance of lip reading for deaf people.
Privacy
For us your privacy comes first, that's why AiRFace.it complies with all Gdpr (
https://gdpr.eu
) regulations and no personal data will be transmitted.
The problem solved by the project
With AiRFace.it App we want to find the solution to the problem of the availability of personal protection devices for everyone, in fact thanks to this app anyone can print his mask, following our guidelines for the use of safe and biodegradable materials, with their own 3D printer,only if you are certificated member of our network to ensure the quality and safety of the mask produced according to all applicable regulations, so that you have a mask for you and your family that can last for all this complicated period that we are living.
The solution you bring to the table
AiRFace.it is installable for free on all iOS and Android devices that have compatibility requirements and in a simple automated way and can create your own 3D mask and send it directly to the 3d printer certificated
The impact of the solution on the crisis
The idea behind this project is to create a safe, cost-effective product that respects nature for us and future generations
The needs to continue the project
This project needs funds in order to create the best mask with the best materials and for this a significant investment in research and development in addition to wanting to make and print masks to those who do not have the opportunity to have their own 3D printer
The value of your post-crisis solutions
We believe a lot in this project because it is a valuable help to anyone who does not have the opportunity to always have a disposable mask and this mask can be reused even after this crisis (hopefully it ends as soon as possible) in any sector that needs personal protection devices
The AiR net blockchain
We are creating a network of certified makers to be able to print masks for doctors and nurses for free to thank them for their valuable help.
We are working with other startups to create a network of certified makers using the Ethereum blockchain to create smart contracts in order to be able to transparently verify the entire network.
We are creating a decentralized system that is based on blockchain eos to ensure the total transparency of certification of the materials used to print the masks.
Currently our team also collaborates in the creation of protective equipment for doctors and nurses to thank them for their difficult work.
Built With
blockchain
c#
html5
java
javascript
kotlin
objective-c
python
swift
Try it out
airface.it
bitbucket.org | AiRFace.it App | A new customizable and ecological mask tailored for you | ['Massimiliano Pizzola', 'Daniela Tabascio'] | [] | ['blockchain', 'c#', 'html5', 'java', 'javascript', 'kotlin', 'objective-c', 'python', 'swift'] | 84 |
9,988 | https://devpost.com/software/masked-ai-masks-detection-and-recognition | Platform Snapshot
Input Video
Model Processing
Model Processing
Output Video Saved
Output Video Snapshot
Output Video Snapshot
Output Video Snapshot
Output Video Snapshot
Output Video Snapshot
Output Video Snapshot
Inspiration
The total number of Coronavirus cases is 5,104,902 worldwide (Source: World o Meters). The cases are increasing day by day and the curve is not ready to flatten, that’s really sad!! Right now the virus is in the community-transmission stage and taking preventive measures is the only option to flatten the curve. Face Masks Are Crucial Now in the Battle Against COVID-19 to stop community-based transmission. But we are humans and lazy by nature. We are not used to wear masks when we go out in public places. One of the biggest challenges is “People not wearing masks at public places and violating the order issued by the government or local administration.” That is the main reason, we built this solution to monitor people in public places by Drones, CCTVs, IP cameras, etc, and detect people with or without face masks. Police and officials are working day and night but manual surveillance is not enough to identify people who are violating rules & regulations. Our objective was to create a solution that provides less human-based surveillance to detect people who are not using masks in public places. An automated AI system can reduce the manual investigations.
What it does
Masked AI is a real-time video analytics solution for human surveillance and face mask identification. Our main feature is to identify people with masks that are advised by the government. Our solution is easy to deploy in Drones and CCTVs to “see that really matters” in this pandemic situation of the Novel Coronavirus. It has the following features:
1. Human Detection
2. Face Masks Identification (N95, Surgical, and Cloth-based Masks)
3. Identify human with or without mask in real-time
4. Count people each second of the frame
5. Generate alarm to the local authority if not using a mask (Soon in video demo)
It runs entirely on the cloud and does detection in real-time with analysis using graphs.
How we built it
Our solution is built using the following major technologies:
1. Deep Learning and Computer Vision
2. Cloud Services (Azure in this case)
3. Microservices (Flask in this case)
4. JavaScript for the frontend features
5. Embedded technologies
I will be breaking the complete solution into the following steps:
1. Data Preparation:
We collected more than 1000 good quality images of multiple classes of face masks (N95, Surgical, Clothe-based masks). We then performed data-preprocessing and labeled all the images using labeling tools and generated PASCAL VOC and JSON after the labeling.
2. Model Preparation:
We used one of the famous deep learning-based object detection algorithm “YOLO V-3” for our task. Using darknet and Yolo v-3, we trained the model from scratch on 16GB RAM and Tesla K80 powered GPU machine. It took 10 hours to train the model. We saved the model for deploying our solution to the various platforms.
3. Deployment:
After training the model, we built the frontend which is totally client-based using JavaScript and microservice “Flask”. Rather than saving the input videos to our server, we are sending our AI to the client’s place and using Microsoft Azure for the deployment. We are having on-premise and cloud solutions prepared. At the moment, we are on a trail so we can’t provide the link URL.
After building the AI part and frontend, We integrated our solution to the IP and CCTV cameras available in our house and checked the performance of our solution. Our solution works in real-time on video footage with very good accuracy and performance.
Challenges we ran into
There are always a few challenges when you innovate something new. The biggest challenge is “The Novel Coronavirus” itself. For that reason, we can’t go outside the home for the hardware and embedded parts. We are working virtually to build innovative solutions but as of now, we are having very limited resources. We can’t go outside to buy hardware components or IP & CCTV cameras. One more challenge we faced was that we were not able to validate our solution with drones in the early days due to the lockdown but after taking permission from the officials that problem was not a deal anymore.
Accomplishments that we're proud of
Good work brings the appreciation and recognition. We have submitted our research paper in several conferences and international journals (Waiting for the publication). After developing the basic proof-of-concept, We went on to the local government officials and submitted our proposal for a trial to check our solution for better surveillance because the lockdown is near to be lifted. Our team is also participating in several hackathons and tech event virtually to showcase our work.
What we learned
Learning is a continuous process. We mainly work with the AI domain and not with the Drones. The most important thing about this project was “Learning new things”. We learned how to integrate “Masked AI” into Drones and deploy our solution to the cloud. We added embedded skills in our profile and now exploring more features on that part. The other learning part was to take our proof of concept to the local administration for trails. All these “Government Procedures” like writing Research Proposal, Meeting with the Officials, etc was for the first time and we learned several protocols to work with the government.
What's next for Masked AI: Masks Detection and Recognition
We are looking forward to collaborating with local administrative and the government to integrate our solution for drone-based surveillance (that’s currently in trend to monitor internal areas of the cities). Parallel, The improvement of model is the main priority and we are adding “Action Recognition” and “Object Detection” features in our existing solution for even robust and better solution so decision-makers can make ethical decisions as because surveillance using Deep Learning algorithms are always risky (bias and error in judgments).
Built With
azure
darknet
flask
google-cloud
javascript
nvidia
opencv
python
tensorflow
twilio
yolo | Masked AI: AI Solution for Face Mask Identification | Masked AI is a cloud-based AI solution for real-time surveillance that keeps an eye on the human who violates the rule by not using face masks in public places. | [] | [] | ['azure', 'darknet', 'flask', 'google-cloud', 'javascript', 'nvidia', 'opencv', 'python', 'tensorflow', 'twilio', 'yolo'] | 85 |
9,988 | https://devpost.com/software/covidcentral-u21txv | Landing Page
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Content Summarizer
Comparison of 4 Types of Content Summarizer
Text Insights
Preprocessing
Inspiration
This year has been really cruel to humanity.
Australia is being ravaged by the worst wildfires seen in decades, Kobe Bryant’s passing
, and now this pandemic due to
the Novel Coronavirus
originated from the Hubei province (Wuhan) of China. Coronavirus disease (COVID-19) is an infectious disease caused by a newly discovered coronavirus.
More than 3 million people
are affected by this deadly virus across the globe (Source: World O Meters). There have been around 249,014 deaths already and it’s counting. 100+ countries are affected by this virus so far. This is the biggest health crisis in the last many years.
Artificial Intelligence
has proved its usefulness in this time of crisis. The technology is one of the greatest soldiers the world could ever get in the fight against coronavirus. AI along with its subsets (Machine Learning) is leveraging significant innovation across several sectors and others as well to win against the pandemic. After
Anacode releases “The Covid-10 Public Media Dataset”
, we took this as an opportunity to use Natural Language Processing on those data composed of Articles. According to Anacode “It is a resource of over 40,000 online articles with full texts which were scraped from online media in the timespan since January 2020, focussed mainly on the non-medical aspects of COVID-19. The data will be updated weekly”. Anacode further says “We are sharing this dataset to help the data community explore the non-medical impacts of Covid-19, especially in terms of the social, political, economic, and technological dimensions. We also hope that this dataset will encourage more work on information-related issues such as disinformation, rumors, and fake news that shape the global response to the situation.”
Our team leveraged the power of NLP and Deep Learning and built
“CovidCentral”
, a PaaS
(Platform as a Service)
. We believe our solution can help media people, researchers, content creators, and everyone else who is reading and writing articles or any kind of content related to the COVID-19.
What it does
Our tagline says
“Stay central with NLP powered text analytics for COVID-19”. CovidCentral is one of its kind NLP driven platform for fast and accurate insights. It generates a summary and provides analytics of large amounts of social and editorial content related to COVID-19. STAY CENTRAL INSHORTS.
It does three things:
1.
CovidCentral platform can help to
understand large contexts related to COVID-19 in a matter of minutes.
Through the platform, Get actionable insights from hundreds of thousands of lines of texts in minutes. It generates an automated summary of large contents and provides word-by-word analytics of the texts from total word count to the meaning of each word. The user can either enter an URL to summarize and getting insights or enter the complete content directly into the platform.
2.
The large content of text data is hard to analyze. It is very difficult to analyze the large content of texts. CovidCentral can help people to get insights within minutes. Manual analysis of texts leads to a number of hours. Media people, researchers, or anyone who is having the internet can access our platform and
get the insights related to the COVID-19.
3.
Humans are lazy in nature and people want to save time. This platform can generate content’s summary within minutes via a single URL. CovidCentral uses NLP and Deep Learning technologies to provide an automated summary of texts. Very helpful for getting short facts related to the COVID-19.
Why Use CovidCentral?
1. Fast
2. Ease of Use (User-friendly)
3. High Accuracy
4. Secure (No content or data will be saved in the server rather we are sending NLP to you at the frontend.)
How we built it
We built CovidCentral using AI technologies, Cloud technologies, and web technologies. This platform uses NLP as a major technique and leverages several other tools and techniques. The major technologies are:
a. Core concept:
NLP (Spacy, Sumy, Gensim, NLTK)
b. Programming Languages:
Python and JavaScript
c. Web Technologies: HTML, CSS, Bootstrap, jQuery ( JS)
d. Database and related tools:
SQLITE3 and Firebase
(Google's mobile platform)
e. Cloud:
AWS
Below are the steps that will give you a high-level overview of the solution:
1. Data Collection and Preparation:
CovidCentral is built on mainly using “Covid-19 Public Media Dataset” by Anacode. A dataset for exploring the non-medical impacts of Covid-19. It is a resource of over 40,000 online articles with full texts related to COVID-19. The heart of this dataset are online articles in text form. The data is continuously scraped from a range of more than 20 high-impact blogs and news websites. There are 5 topic areas - general, business, finance, tech, and science.
Once we got the data, the next step is obviously “Text Preprocessing”. There are 3 main components of text preprocessing:
(a) Tokenization (b) Normalization (c) Noise Removal.
Tokenization
is a step that splits longer strings of text into smaller pieces, or tokens. Larger chunks of text can be tokenized into sentences, sentences can be tokenized into words, etc. Further processing is generally performed after a piece of text has been appropriately tokenized.
After tokenization, we performed
“Normalization”
because, before further processing, the text needs to be normalized. Normalization generally refers to a series of related tasks meant to put all text on a level playing field: converting all text to the same case (upper or lower), removing punctuation, converting numbers to their word equivalents, and so on. Normalization puts all words on equal footing and allows processing to proceed uniformly.
In the last step of our Text preprocessing, we performed
“Noise Removal”
. Noise removal is about removing characters digits and pieces of text that can interfere with your text analysis. Noise removal is one of the most essential text preprocessing steps.
2. Model Development:
We have used several NLP libraries and frameworks like Spacy, Sumy, Gensim, and NLTK. Apart from having a custom model, we are also using pre-trained models for the tasks. The basic workflow of creating our COVID related NLP based summarizer or analytics engine is like this: Text Preprocessing (remove stopwords, punctuation). Frequency table of words/Word Frequency Distribution – how many times each word appears in the document Score each sentence depending on the words it contains and the frequency table. Build a summary or text analytics engine by joining every sentence above a certain score limit.
3. Interface:
CovidCentral is a responsive platform that supports both i.e. Mobile and web. The frontend is built using web technologies like HTML, CSS, Bootstrap, JavaScript (TypeScript, and jQuery in this case). We have used a few libraries for validation and authentication.
On the backend part, it uses python microservice “Flask” for integrating the NLP models, SQLITE3 for handling the database, and Firebase for authentication and keeping records from the User forms.
4. Deployment:
After successfully integrating backend and frontend into a platform, we deployed CovidCentral on the cloud. It runs 24*7 on the cloud. We deployed our solution on
Amazon Web Services (AWS)
and use an EC-2 instance as a system configuration.
Challenges we ran into
Right now, the biggest challenge is “The Novel Coronavirus”. We are taking this as a challenge and not as an opportunity. Our team is working on several verticles whether it is medical imaging, surveillance, bioinformatics and CovidCentral to fight with this virus.
There were a few major challenges:
Time constraint
was a big challenge because we had very little time to develop this but we still pulled CovidCentral in this short span of time. The data which has more than 40K articles are pretty much messy, so
we got difficulties dealing with messy data
in the beginning but after learning how to handle that kind of data, we eliminated that challenge to some extent. We also got challenges while deploying our solution to the cloud but managed somehow to do that and still testing our platform and making it robust.
Accomplishments that we're proud of
Propelled by the modern technological innovations, data is to this century what oil was to the previous one. Today, our world is parachuted by the gathering and dissemination of huge amounts of data. In fact, the International Data Corporation (IDC) projects that the total amount of digital data circulating annually around the world would sprout from 4.4 zettabytes in 2013 to hit 180 zettabytes in 2025. That’s a lot of data!
With such a big amount of data circulating in the digital space, there is a need to develop machine learning algorithms that
can automatically shorten longer texts and deliver accurate summaries that can fluently pass the intended messages.
Furthermore, applying text summarization reduces reading time,
accelerates the process of researching for information, and increases the amount of information that can fit in an area.
We are proud of the development of CovidCentral and to make it Open Source so anyone can use it for free on any kind of device to get important facts related only to COVID-19.
What we learned
Learning is a continuous process of life, the pinnacle of the attitude and vision of the universe. I tell my young and dynamic team (Sneha and Supriya) to keep on learning every day.
In this lockdown situation, we are not able to meet each other but we learned how to work virtually in this kind of situation. Online meeting tools like Zoom in our case, GitHub, Slack, etc helped all of us in our team to collaborate and share our codes with each other.
We also
strengthen our skills in NLP (BERT, Spacy, NLTK, etc)
and how to integrate our models to the front-end for end-users. We spent a lot of time on the interface so people can use it and don’t get bored. From design to deployment, there were many things that helped us improve our skills technically.
We learn many things around us day by day. Since we are born, we learn many things, and going forward, we will add more relevant features by learning new concepts in our platform.
What's next for CovidCentral
We are adding features like “Fake News Detector” to spam fake news related to the COVID-19 very soon on our platform. CovidCentral’s aim is to help content creators, media people, researchers, etc to
only read that matters the most
in a quick time. APIs to be released soon so anyone who wants to add these features in their existing workflow or website can do it so they won’t need to use our platform rather they can just use our APIs.
We are also in discussion with
some text analytics companies to collaborate
and bring an even more feasible, robust, and accessible solution. In the near future, we will make CovidCentral an NLP powered text analytics platform in general for all kinds of text analytics for anyone, free to use from anywhere on any kind of devices (Mobile, Web, Tablet, etc).
Built With
amazon-web-services
bootstrap
css
firebase
flask
html
javascript
natural-language-processing
nltk
python
sqlite
Try it out
covidcentral.herokuapp.com | CovidCentral | CovidCentral is one of its kind NLP driven platform for fast and accurate insights. It generates a summary and provides analytics of large amounts of social and editorial content related to COVID-19. | [] | [] | ['amazon-web-services', 'bootstrap', 'css', 'firebase', 'flask', 'html', 'javascript', 'natural-language-processing', 'nltk', 'python', 'sqlite'] | 86 |
9,988 | https://devpost.com/software/covnatic-covid-19-ai-diagnosis-platform | Landing Page
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Segmentation of Infected Areas in a CT Scan
Check Suspects using Unique Identification Number (New Suspect)
Check Suspects using Unique Identification Number (Old Suspect)
Suspect Data Entry
COVID-19 Suspect Detector
Upload Chest X-ray
Result: COVID-19 Negative
Upload CT Scan
Result: Suspected COVID-19
Realtime Dashboard
Realtime Dashboard
Realtime Dashboard
View all the Suspects (Keep and track the progress of suspects)
Suspect Details View
Automated Segmentation of the infected areas inside CT Scans caused by Novel Coronavirus
Process flow of locating the affected areas
U-net (VGG weights) architecture for locating the affected areas
Segmentation Results
Detected COVID-19 Positive
Detected Normal
Detected COVID-19 Positive
Detected COVID-19 Positive
GIF
Located infected areas inside lungs caused by the Novel Coronavirus
Endorsement from Govt. Of Telengana, Hyderabad, India
Endorsement from Govt. Of Telengana, Hyderabad, India
Generate Report: COVID-19 Possibility
Generate Report: Normal Case
Generated PDF Report
Inspiration
The total number of Coronavirus cases is
2,661,506 worldwide
(Source: World o Meters). The cases are increasing day by day and the curve is not ready to flatten, that’s really sad!! Right now the virus is in the community-transmission stage and rapid testing is the only option to battle with the virus. McMarvin took this opportunity as a challenge and built AI Solution to provide a tool to our doctors. McMarvin is a DeepTech startup in medical artificial intelligence using AI technologies to develop tools for better patient care, quality control, health management, and scientific research.
There is a current epidemic in the world due to the Novel Coronavirus and here
there are limited testing kits for RT-PCR and Lab testing
. There have been reports that kits are showing variations in their results and false positives are heavily increasing.
Early detection using Chest CT can be an alternative to detect the COVID-19 suspects.
For this reason, our team worked day and night to develop an application which can help radiologist and doctors by automatically detect and locate the infected areas inside the lungs using medical scan i.e. chest CT scans.
The inspirations are as below:
1. Limited kit-based testings due to limited resources
2. RT-PCR is not as much as accurate in many countries (recently in India)
3. RT-PCR test can’t exactly locate the infections inside the lungs
AI-based medical imaging screening assessment is seen as one of the promising techniques that might lift some of the heavyweights of the doctors’ shoulders.
What it does
Our COVID-19 AI diagnosis platform is a fully secured cloud based application to detect COVID-19 patients using chest X-ray and CT Scans. Our solution has a centralized Database (like a mini-EHR) for Corona suspects and patients. Each and every record will be saved in the database (hospital wise).
Following are the features of our product:
Artificial Intelligence to screen suspects using CT Scans and Chest X-Rays.
AI-based detection and
segmentation & localization of infected areas inside the lungs
in chest CT.
Smart Analytics Dashboard
(Hospital Wise) to view all the updated screening details.
Centralized database (only for COVID-19 suspects) to
keep the record of suspects and track their progress
after every time they get screened.
PDF Reports,
DICOM Supports
, Guidelines, Documentation, Customer Support, etc.
Fully secured platform
(Both On-Premise and Cloud)
with the privacy policy under healthcare data guidelines.
Get Report within Seconds
Our main objective is to provide a research-oriented tool to alleviate the pressure from doctors and assist them using AI-enabled smart analytics platform so they can
“SAVE TIME”
and
“SAVE LIVES”
in the critical stages (Stage-3 or 4).
Followings are the benefits:
1. Real-world data on risks and benefits:
The use of routinely collected data from suspect/patient allows assessment of the benefits and risks of different medical treatments, as well as the relative effectiveness of medicines in the real world.
2. Studies can be carried out quickly:
Studies based on real-world data (RWD) are faster to conduct than randomized controlled trials (RCTs). The Novel Coronavirus infected patients’ data will help in the research and upcoming such outbreak in the future.
3. Speed and Time:
One of the major advantages of the AI-system is speed. More conventional methods can take longer to process due to the increase in demand. However, with the AI application, radiologists can identify and prioritize the suspects.
How we built it
Our solution is built using the following major technologies:
1. Deep Learning and Computer Vision
2. Cloud Services (Azure in this case)
3. Microservices (Flask in this case)
4. DESKTOP GUIs like Tkinter
5. Docker and Kubernetes
6. JavaScript for the frontend features
7. DICOM APIs
I will be breaking the complete solution into the following steps:
1. Data Preparation:
We collected more than 2000 medical scans i.e. chest CT and X-rays of 500+ COVID-19 suspects around the European countries and from open source radiology data platform. We then performed validation and labeling of CT findings with the help of advisors and domain experts who are doctors with 20+ experience. You can get more information in team section on our site. After carefully data-preprocessing and labeling, we moved to model preparation.
2. Model Development:
We built several algorithms for testing our model. We started with CNN for classifier and checked the score in different metrics because creating a COVID-19 classifier is not an easy task because of variations that can cause bias while giving the results. We then used U-net for segmentation and got a very impressive accuracy and got a good IoU metrics score. For the detection of COVID-19 suspects, we have used a CNN architecture and for segmentation we have used U-net architecture. We have achieved 94% accuracy on training dataset and 89.4% on test data. For false positive and other metrics, please go through our files.
3. Deployment:
After training the model and validating with our doctors, we prepared our solutions in two different formats i.e. cloud-based solution and on-premise solution. We are using EC-2 instance on AWS for our cloud-based solution.
Our platform will only help and not replace the healthcare professionals so they can make quick decisions in critical situations.
Challenges we ran into
There are always a few challenges when you innovate something new. The biggest challenge is “The Novel Coronavirus” itself.
One of the challenge is “Validated data” from different demographics and CT machines.
Due to the lockdown in the country, we are not able to meet and discuss it with several other radiologists. We are working virtually to build innovative solutions but as of now, we are having very limited resources.
Accomplishments that we're proud of
We are in regular touch with the State Government (Telangana, Hyderabad Government). Our team presented the project to the Health Minister Office and helping them in stage-3 and 4.
Following accomplishments we are proud of:
1. 1 Patent (IP) filled
2. 2 research paper
3. Partnership with several startups
4. In touch with several doctors who are working with COVID-19 patients. Also discussing with Research Institutes for R&D
What we learned
Learning is a continuous process. Our team learnt
"the art of working in lockdown"
. We worked virtually to develop this application to help our government and people. The other learning part was to take our proof of concept to the local administration for trails. All these “Government Procedures” like writing Research Proposal, Meeting with the Officials, etc was for the first time and we learned several protocols to work with the government.
What's next for M-VIC19: McMarvin Vision Imaging for COVID19
Our research is still going on and our solution is now endorsed by
the Health Ministry of Telangana
. We have presented our project to
the government of Telangana for a clinical trail
. So the next thing is that we are looking for trail with hospitals and research Institutes. On the solution side, we are adding more labeled data under the supervision of Doctors who are working with COVID-19 patients in India. Features like
Bio-metric verification, Trigger mechanism to send notification to patients and command room
, etc are under consideration. There is always scope of improvement and AI is the technology which learns on top of data. Overall, we are dedicated to take this solution into real world production for our doctors or CT and X-rays manufacturers so they can use it to fight with the deadly virus.
Built With
amazon-web-services
flask
google-cloud
javascript
keras
nvidia
opencv
python
sqlite
tensorflow
Try it out
m-vic19.com | M-VIC19: McMarvin Vision Imaging for COVID19 | M-VIC19 is an AI Diagnosis platform is to help hospitals screen suspects and automatically locate the infected areas inside the lungs caused by the Novel Coronavirus using chest radiographs. | [] | ['1st Place Overall Winners', 'Third Place - Donation to cause or non-profit organization involved in fighting the COVID crisis'] | ['amazon-web-services', 'flask', 'google-cloud', 'javascript', 'keras', 'nvidia', 'opencv', 'python', 'sqlite', 'tensorflow'] | 87 |
9,988 | https://devpost.com/software/papure-2tpv60 | paPURE Setup - Angeled View - Utilizing Snorkeling Mask
paPURE Setup - Front View - Utilizing Snorkeling Mask
paPURE Setup - Side View - Utilizing Snorkeling Mask
paPURE Setup - Back View - Utilizing Snorkeling Mask
Original Prototype of paPURE Design View
paPURE Base - Top View - Inserted Compressor Fan and Fan Shroud
paPURE Base - Top View - Empty
Abstract:
The Filtrexa paPURE is an affordable, 3D printed powered air-purifying respirator (PAPR) that provides our healthcare providers with better protection than even N95s, especially in high-risk and confined environments (E.g. ICUs, ERs). It incorporates readily available components and can be easily manufactured locally. We can thus increase accessibility of PAPR technology by enabling hospitals to produce and purchase it as per their need, optimizing the 3D-print to produce it at a cost that is over ten times cheaper than PAPRs currently offered on the market, and using exchanging highly specific components for readily available and affordable components. The Filtrexa paPURE also has made design changes to improve comfort, ease of use, and longevity of PAPR technology.
Introduction
One of the most immediate and impactful effects of the COVID-19 pandemic are global shortages of proper personal protective equipment (PPE), forcing healthcare providers (HCPs) to consistently work in high-risk environments and unnecessarily place their own lives at risk. Our product is a powered air-purifying respirator (PAPR) that creates a positive pressure field with filtered air to protect frontline healthcare workers from airborne threats such as SARS, TB, measles, influenza, meningitis, and most immediately COVID-19. This technology improves upon current PAPR devices in terms of cost-efficacy, ease of access, and ease of implementability. Our solution not only serves to combat general PAPR shortages across the country, but also eases PPE shortages that arise from COVID-19 and future patient surges through an on-demand 3D printing process.
Value Proposition
Powered, air-purifying respirators (PAPRs) are currently the gold standard in medicine when treating patients diagnosed with COVID-19 and other highly infectious respiratory diseases[1] due to their positive pressure system. This system filters air extremely effectively before it reaches the airway. However, this technology package is costly, often totaling over $1800[2] and requires highly specific components which are currently in short supply. Both well-established hospitals such as the Mayo Clinic (with a ratio of 4500 physicians to 200 PAPRs)[2] and smaller county hospitals such as the Hunterdon Medical Center (where not a single PAPR is available to physicians) are facing critical shortages of personal protective equipment (PPE). Evidently, the aforementioned barriers render PAPR technology inaccessible to most frontline HCPs, leaving them far more vulnerable to infection.
Alternatives to PAPR technology include N95s, surgical masks, and currently, homemade masks due to a worldwide shortage of PPE. Although they provide a barrier against aerosols, standard and surgical N95s are easily compromised with an improper fit and have an assigned protection factor (APF) of ten[4], while PAPRs have an APF of 25 to 1000, rendering PAPRs far more effective at protecting HCPs. Additionally, physicians tend to prefer PAPRs over N95s because PAPRs are reusable, easier to breathe through, do not require fit testing, and make them feel safer[1][5].
Our Solution
In order to provide purified air to those in the most high-risk environments, we have developed a novel, inexpensive, and accessible PAPR device that is both lightweight and 3D-printable within 24 hours. Printed using readily-available filaments (e.g. PLA, ABS), paPURE is mounted to the user’s hip and assembled via on-hand motors and batteries. (See Appendix 2.5).
Through PAPR technology, HCPs are given access to filtered positive pressure air systems (in which airflow serves to seal any gaps in masks, as well as reduce respiratory fatigue in HCPs), drastically decreasing infection risk in areas such as ICUs and ERs.
Our device’s customizability allows for interoperability with existing masks, filters, and hosing (See Appendix 3.1), enabling hospitals, or possibly surrounding hobbyists/machinists (regulatory dependent), to produce PAPRs for their physicians and nurses. For images and procedures: See Appendix 1 and 2.
The system features a dual battery set-up that allows HCPs to utilize one or both batteries independently, as well as swap out batteries while the device is in use (such as during an extended patient procedure that a physician cannot leave from). Additionally the belt system, with the fan/chassis on you lumbar and 2 battery on ports on both hips gives a better weight distribution for improved comfort in extended usages (such as a surgeon leaning in an awkward position during the operation). The use of an inline filter means that air is pushed into a filter at the end of the device, as opposed to regular PAPRs that pull air through filters. This setup means that the risk of an imperfect seal compromising air quality is virtually nullified as no negative pressure system exists after air filtration in our device. Additionally, the aforementioned inline filters are better at filtering biological particles without disturbing airflow than standard P100s and are already used extensively in anesthesiology and respiratory care departments of hospitals across the country.
After printing the device’s chassis and shroud, integration with an inline bacterial/viral filter, housing, and masks will be followed by on-site fit and efficacy testing to ensure proper device assembly.[6] Then, an HCP would don their mask, clipping the paPURE chassis and two smart power tool batteries to a provided utility belt, and connecting to the mask via a hose. At most, we expect equipping paPURE to add 1-3 minutes to a medical professional’s routine and greatly improve safety and comfort.
An Improvement from Traditional PAPRs
Our technology eliminates the need for a middle-man manufacturer. Because the only required components are readily available to hospitals and clinics, hospitals can produce the device as per their need. We anticipate working with local 3D-printing facilities to produce and assemble the product, then to distribute the Filtrexa PAPR to hospitals. Physicians and NIOSH officials (most notably Richard Metzler, the first Director of the National Personal Protective Technology Laboratory at NIOSH), have already given us promising feedback regarding the need for this technology, and we are looking into potential partnerships with PPE developers and/or motor manufacturers. Some hospital purchasing experts have additionally communicated a need for affordable PAPRs. Our solution is over 10 times cheaper than current PAPR technologies ($155; see Appendix 2, Figure 2), increasing likelihood of adoption. To allow smaller hospitals to easily obtain our technology, we plan to raise awareness of our business through phone calls and emails to hospitals throughout the country.
Implementation Plan
paPURE’s solution is implementable almost immediately. The main barrier between our tested prototype and implementation is FDA/NIOSH approval (FDA EUA Sec II/IV Approve NIOSH Certified Respirators). We have also identified conditions that will allow us to expedite the regulation and roll-out of the production (such as the IDE and 501(k) pathways suggested to us by regulatory experts).[15] Because our device is based on existing PAPR technology, this predicate nature in combination with existing precedents for 3D-printed medical technology, can help expedite its deployment.[16]
Our technology minimizes the need for a middle-men. We are partnering with regional additive manufacturers to allow for quick, standardized, yet still decentralized production of the device. The only required components are readily available to hospitals and clinics, allowing HCPs to produce the device as per their need. Additionally, if regulatory approval permits, we may utilize local schools/universities/hospitals with on-site 3D printers in order to allow for fully decentralized manufacturing. After NIOSH Approval, our device (and depending on regulatory guidelines, possibly our CAD file) will be sent to those with 3D printers available, who could print and assemble the device (See Appendix 3.1).
Players involved in the production of this technology would be hospital assembly workers, but the design is easily assembled by anyone (the only limitation being that assembly be done under a fume hood to prevent contamination). Physicians we’ve already talked to have given us promising feedback regarding the need for this technology. We are currently looking into potential partnerships with PPE developers (See Appendix 3.2) and/or motor manufacturers. Our solution is over ten times cheaper than current PAPR technologies (See Appendix 3.3), increasing the likelihood of adoption.
Due especially to the length of this health crisis, hospitals are facing dire shortages of PPE. This has accelerated our timeline, but we are confident that it is feasible given the current state of emergency (See Appendix 3.4).
Since this product has yet to be implemented in hospitals, we are writing to you today to gauge your interest in paPURE. Additionally, any feedback you have relating to our product or interest in helping us with laboratory testing of paPURE would be greatly appreciated.
We anticipate our project to reach full fruition within 6-12 months. Our timeline is as follows. Our second iteration of prototyping for clinician testing will conclude in 2-3 weeks, followed by initial clinical testing, which will finish in around 1.5 months. As soon as clinical testing is finished and the product is validated, we will submit our product officially to NIOSH for regulatory approval. We anticipate receipt of regulatory approval within 1.5 months from submission. After approval is obtained, we will also apply for either a provisional patent or copyright, depending on legal advice. Within 1-2 months after regulatory approval, we plan to roll out our product to hospitals via centralized 3D-printing. During the next 1-2 months, we will continue to iterate and optimize the product. Official hospital rollout, with multiple 3D-printing partners and company partnerships, will occur around a month later. This will be around 6-7 months from now. As seen, our timeline is aggressive as we wish to equip healthcare providers with PPE as soon as possible. The prior goals mentioned in our timeline are our key goals and objectives for the project at this time.
Current Testing and Partnerships
Technical Testing is being carried out at Filrexa's primary residence and at Johns Hopkins University and includes analysis of airflow data, battery life, and filtration efficacy. For clinical testing, we already have established connections for clinical testing with both Johns Hopkins Medical Institute and Stanford University. In regards to business-focused assistance, we have also partnered with FastForwardU for advising regarding intellectual property protection, strategic marketing, and clinical networking.
Planned Partnerships
We plan to designate one 3D-printing company (current candidates include Xometry, Protolabs, Cowtown, and Health3D) as our manufacturer during our initial launch into the market, but will continue to partner with additional 3D-printing companies as our business grows. Due to our unique manufacturing approach, all hospitals, regardless of their size, will be able to order and quickly receive PAPRs, lowering the impact of the current shortage. In order to supply the auxiliary materials such as motors, batteries, and more, we plan to initiate company partnerships with large corporations such as 3M, Dyson, Black and Decker, GE, Cuisinart, Hitachi, Makita, Shop Vac, Hoover, Bissell, Shark, iRobot, and Bosch.
Additional Video
https://youtu.be/iFMtzt52BEQ
Appendix and Citations
Click here!
Website
paPURE Website
Built With
3dprinting
cad
cpap
p100 | paPURE | paPURE is a hospital accessible PAPR Technology utilizing 3D printing and readily available hardware to give healthcare's frontline the gold standard of personal protective equipment right now. | ['Sanjana Pesari', 'Hannah Yamagata', 'Sneha Batheja', 'Joshua Devier'] | ['2nd Place Overall Winners', '1st Place', 'The Wolfram Award', 'The Best Business Idea', '3rd Place Hack', 'Best COVID-19 Hack'] | ['3dprinting', 'cad', 'cpap', 'p100'] | 88 |
9,988 | https://devpost.com/software/smarttracker-covid19 | Inspiration :
Now a days whole world facing the novel Corona Virus, to track the spread of novel Corona Virus country-wise, details of confirmed cases, deaths and Recovered, awareness regarding COVID-19. This Android app was created to spread awareness about the covid -19 virus.
What it does :
The Android app named as ‘SmartTracker-Covid-19’ created to spread awareness about the COVID -19 virus. App includes following functionalities:
CoronaEx Section -
This section having following sub components:
• News tab: Having latest new updates. Fake news seems to be spreading just as fast as the virus but as we have integrated from official sources so everyone will be aware from fake news.
• World Statistic tab: Real-time Dashboard that tracks the recent cases of covid-19 across the world.
• India Statistic tab: Coronavirus cases across different states in India with relevant death and recovered cases.
• Prevention tab: Some Prevention to be carried out in order to defeat corona.
CoronaQuiz section - quiz that will help people know about the Corona virus and its effects on human body. It chooses random questions and show the correct answer for the questions and at the end user will get to know their highest score.
Helpline Section - As this application particularly made for Indian citizen to use, all state helpline number of India included.
Chatbot Section - A self-assisted bot made for the people navigate corona virus situation.
Common Questions: Start screening,what is COVID-19? , What are the symptoms?
How we built it :
We built with using Android studio. For the quiz section we have used sqlite database and live news data we have integrated from the News API. For the coronavirus statistic we have collected data from worldometer and coronameter.
Challenges we ran into :
At time of integrating the chatbot in application.
Accomplishments that we're proud of :
Though , It was the first attempt to create chatbot.we have tried to up our level at some extent.
What's next for SmartTracker-COVID19 :
For the better conversation we will be looking to work more on chatbot.
Built With
android-studio
chatbot
java
news
quiz
sqlite
Try it out
github.com | SmartTracker-COVID-19 | Android app to track the spread of Corona Virus (COVID-19). | ['Pramod Paratabadi', 'Supriya Shivanand Madiwal .'] | ['Best Use of Microsoft Azure'] | ['android-studio', 'chatbot', 'java', 'news', 'quiz', 'sqlite'] | 89 |
9,988 | https://devpost.com/software/virtualcovid | GamePlayVeiw03
GamePlay View 04
GamePlay View 01
GamePlay View 02
Virtual Gaming: CoviFitness [Virtual Covid Game]
This is an extension to the Covid Raccoon that I developed in extension to Covid Raccoon Game. Good news is that you can play it virtually!
Kindly Refer to my
Github repo
or
Youtube Video
for better documentation as some images are missing here.
CoviFitness
is a 2D fun, interactive and awaring game made for kids and individuals to play the game with real time moves.
Are you also getting bored and lazy this covid?
Do you have a habbit of skippinig morning walks?
Is your exercise getting rescheduled due to your sleep cycle?
Do you also want flexible timing for work-out?
Well in that case,
CoviFitness
is a must try!
Installation Instructions
Open Terminal and type the following command:
pip install -r requirements.txt
Once all the dependencies are installed, open the terminal and type the command:
python3 CoronaIntegrated.py
Calibrations
When you run the code, the following text will appear on your screen:
Don't move during this process, it tries to detect the face and accordingly do the calibration. Note that most of the movements are defined based on the facial orientation.
Once the Calibration is successful, you will see this window:
This will end by popping a cv2 window which will proceed to calibration, this is for calibrating the bending height, make sure your camera is positioned in such a way that your chin must be above this blue line.
These lines are added with time delay so that they won't get changed quickly and allow for reaction time. In case you want to bring down the height even more you can modify this line of code in
CoronaIntegrated.py
.
The popup screen looks like this:
Move your right hand to the top-right box to lower the line, move your left hand to the top-left box to raise the height, once you're satisfied, move both of the hands to complete the calibration process.
Once the calibration is complete the following screen pops up:
Now enjoy the game, jump to make your character jump and crouch to make it crouch. Note that currently these controls are calibrated and the other control (like boxing gesture is in test mode).
Project Components
Computer Vision (OpenCV python)
Pygame (For building intutive 2D game)
Inspiration
I have always been curious about learning new things, whether it be related to stem or something else (though, I am always inclined towards STEM). Game Dev is a booming field and seems to have a promising future if correctly used.
Video games are no more just a source of fun and entertainment, today we can use this virtual technology (especially in fields of AR and VR) to make use of this tech and create a real-life learning experience. From the very beginning, this has caught my attention to the field of gaming. This project is one such attempt to demonstrate how these things can actually change the way we live.
Though I am well versed with other Development (App-Dev/ Web-Dev/ Designing) and Instrumentation Tech (IoT/ Robotics etc.) but Game-Dev was always something which I wanted to learn, and that's what turned me to try it here for the first time after creating a very basic 2D game
covid raccoon
.
What it does?
The game is a story about a boy (Here it's me) who is sanetizing entire city and needs to safely reach his home, which is located at the end of the city. Various types of viruses, infected hosts and bats are roaming around the city, which need to be dotched or sanetized without coming in contact with them.
Here are some of the GamePlay Screenshots:
It allows you to Roam around the city, which is apparently static (unless you add your custom background :-P) and look for the virus-infected people or viruses escape them till you reach your home, which is at the end of your city.
In this adventure, you will see different types of viruses that will try to infect you! and you're on a mission to reach your home while sanetizing the city and without getting infected.
To escape from the viruses, you have to ensure that you don't come in contact with them at any cost! Also, you need to keep a distance from those who are already infected.
Unless you're not sanitizer protected, any incoming virus can infect you. If you catch a sanitizer (which always happens), you will be able to blow it three times before it ends, and then you have to protect yourself against them.
For all the land viruses, you need to jump and skip them. On the other hand, for all the air viruses, you need to bend down and let them pass away.
With your speed, it takes a fixed amount of time to reach the end of the city where your sanitization process is over, and you could safely keep yourself locked unless the pandemic ends!
How I built it?
The whole project is built in Python using OpenCV (cv2) and Pygame Library.
After finishing my first project (Covid Raccoon), I started working on integrating it with Vision functionality. This entire game is solely built in python with opencv and pygame library. The characters (in the form of png images) are prepared in Microsoft PowerPoint.
Purpose of this Project
I have created this project mainly because of three reasons:
Keeping the World Corona fit by involving in the fun activity. This game will help them exercise in a fun way even from the home.
Getting Exposure of Game Development This project has pretty much helped me to take my first step towards Game development, slowly I would try to dive deeper and do more customizations and learn more.
For the Beginners and Developers For the Beginners and Developers who want to learn PyGame, I am planning on converting this project into Video Tutorial Series. This will not just be there for them to get started with PyGame but also to use this project as the base template to do the modifications in their own project.
For the Kids and Babies to Develop their Minds to Generate Awareness about Cleanness and Sanetization This game could led to a positive awareness among the mind of kids and create a good image of importance of sanitation and hygene in maintaining their health, I am not sure how nicely it will work, but expect it to have some positive impact.
Built With
computer-vision
haar-cascades
image-processing
opencv
pygame
python
Try it out
github.com | Covi Fitness | A vitual gaming experience during Covid lockdown where the game responds to your own own actions and accordingly performs it in the virtual screen. | ['Shivam Sahil'] | [] | ['computer-vision', 'haar-cascades', 'image-processing', 'opencv', 'pygame', 'python'] | 90 |
9,988 | https://devpost.com/software/covi_fight | Inspiration
The virus has affected humanity in various ways, be it our economy, our freedom of movement, and the loss of loved ones. Then how do we live on, comfortably, and safely with this virus around?
Even after the lockdown is over, there is a massive possibility that traces of the virus will remain, and it can spread again.
We wanted to bring people back their mobility and keep them safe at the same time. We wanted people to know about their status while they leave their houses.
What it does
CoviFight alerts me about the risks of catching the virus if I have come in
contact with an infected person
within the past three weeks. It also informs the healthcare system accurately about the spread of infection.
CoviFight also generates a
map with hotspots for what places have virus traces
, so that people can prevent travelling at these places and authorities can sterilize or lockdown these places efficiently rather than having a complete lockdown of a country.
How we built it
We develop a three-tier app:
• A user's app
• A provider's app
• An official's portal.
While utilizing
Bluetooth and GPS
of your phone, CoviFight makes sure that the confidentiality of every individual is secured and can not be compromised. Data is encrypted using a secret key, and no one can view it without your permission. It only traces the past data of positively tested patients. This way, CoviFight also meets the
GDPR compliance.
By using
Geo-fencing and Machine Learning
, we predict your chances of catching the infection so that you can take preventive measures.
A provider's app for aggregation points like shops, restaurants, and public transport synchronizes with the nearby user app. This interface is the key to the detection of infection points, be it
a stationary workplace or a moving vehicle
. If McDonald's installed CoviFight and had an infected customer in the past 15 days, all the customers after the positive tested patient would get alerted, and hence the restaurant can be sterilized.
Only the medical system may update a person's status over the official's portal, and the
authenticity
of the app is maintained hence preventing
false positives
or self-reporting, which might lead to falsification of records.
So, with the help of our app, people can move around while being alerted about their status, stay away from the virus, and be free from the worry of their privacy maintenance at the same time.
Take a look at our demo by clicking
here
Challenges we ran into
To maintain the authenticity of the predictions and analysis, we were initially in a fix as to how to update a person's status as positive or negative. Then we decided to come up with a three-tier system, and we developed a Doc App or official's portal, which is only accessed by the medical system so that the authenticity is maintained.
No one else can manipulate the data.
Accomplishments that we're proud of
• We have made sure that the
privacy
of every individual is maintained and can not be compromised. The encryption algorithms meet the standards of the leading social networking apps existing in the market.
• CoviFight not only alerts people about their own risks but provides heatmaps of the traces of the virus too. CoviFight also shows what
specific restaurant or public transport( like a bus or a train) may be infected
precisely.
• We do not need to compare data between people, thus making
computation very cheap and exponentially faster and efficient.
Our Journey So Far
•
Winners( Runner up) in the #EUvsVirus, a Pan-European Hackathon
Organised by the European Innovation Council to counter COVID-19 pandemic with more than 9k participants and 2000 teams. We stood second in the Real time Communication and Prevention challenge.
•
Top 6 finalists of The Global Hack, by Garage48, April 2020
The Global Hack is a hackathon designed to share and rapidly develop ideas for urgently needed solutions in the face of the COVID-19 crisis, and to build resilience post-pandemic, with over 12k participants from 100+ countries. The team developed a mobile application solution for the containment and tracking of this virus. We were in the top 6 teams in the Crisis Response Track.
•
We were also in the Top 23 Student Innovators in COVID-19 SAMADHAN MHRD( Ministry of Human Resource Development, India) Mega Online Challenge
What we learned
It has been an enjoyable experience to work with people who have not even met each other before and still successfully develop this amazing app. We learned a lot through the hackathon, from interacting with the mentors and getting their guidance, to develop the app.
What's next for CoviFight
We plan
to get this deployed
at its earliest so that people may get their
safe mobility
back. We plan to deploy this on the Play Store and make a version for iOS as soon as we can.
We are also in touch with the Indian Government and we might be able to save lives in India also.
The necessities to continue the project:
• Approval from government authorities to implement and track data.
• Participation from Hospitals/government bodies to update the status of a patient so that system can generate realtime alerts and mark hotspots.
• Cloud resources to scale up the project. Currently limited by the free tier of cloud infrastructure.
The value of our solution after the crisis:
• This application can be used for any contagious disease management.
• It can be used in disaster management to understand the right victims and relief reaches all rightful beneficiaries( such as in the case of floods and storms).
• It can be used by Providers such as McDonald's and Public transport systems to implement targeted location-based marketing complying with data collection practices.
What we have done till now.
• Implemented masked identities for users to comply with GDPR and privacy requirements.
• Identification of hotspots in realtime based on the patient status update.
• Fixed bugs in the flow and to make it work E2E.
• Produced a product demo.
New Technology introduces
• Blockchain to manage user identification data(making it immutable), adding the security of ECC digital signature
• Moving from NoSQL mogoDB to a hybrid of BlockChain and GraphDB for better analysis and prediction while keeping the user's id secrete on the Graph
• Use of Kubernetes for creating multiple threads for gaining concurrency
•Adding caching mechanism to mobile devices to handle any kind of network failure.
Built With
firebase
google-directions
har
java
machine-learning
maps
python
Try it out
github.com
sidhantha.medium.com | CoviFight | A source - contact tracing app, CoviFight is a 3-tier solution that uses geo-fencing and machine learning to trace and track the COVID-19 spread | ['Shikhar Mathur', 'Anshuman Saboo', 'MANIT BASER', 'vishwas puri', 'Sidhantha Poddar', 'Yash Bhagat', 'Neil araujo', 'Navdeep Chawla'] | ['2nd Place Overall Winners', 'The Wolfram Award'] | ['firebase', 'google-directions', 'har', 'java', 'machine-learning', 'maps', 'python'] | 91 |
9,988 | https://devpost.com/software/teledoc | Product Roadmap
Inspiration
Have you ever had shortness of breath, a high temperature, and a really dry cough? Well, I am sure you might say you had COVID-19. In fact, 20% of these cases are asymptomatic.
You might not know you are infected!
What if there was a time where you never had to go to a doctor to get checked up, to find what you had?
We would like to build the much needed medical tricorder of our time, to automatically diagnose and screen infectious diseases remotely without the patient's intervention.
The problem our project solves
COVID-19 has impacted the lives of literally everyone on the planet. As such we now live in a different world, and even beyond the COVID-19 effective preventative measures need to be put in place in all public settings including hospitals, airports, hotels, workplaces, and so on. Our vision is to build a screening machine that could be used readily for the screening of diseases. Our final product will look something like a conventional metal-detector chamber installed at airports, but will the capability to screen people for diseases and infections. For this to be possible, none of the existing methods, include X-Rays/CT/PET/MRI etc, can be used as they all involved the use of ionising radiation and hence cannot be used in public spaces. Not to mention these solutions are bulky and expensive in addition to having long scan times to produce their results.
Our solution utilises harmless non-ionising RF radiation, with emission levels on par with cellphones, ensuring the complete safety of the public and the machine operator. We plan to initially focus on the airport screening application, and are hoping that our product will help open up the airports once again. After proving the effectiveness of our product on airports, we plan to scale up to other immediate verticals including hospitals and workplaces. In this way we are aiming for a huge global-scale impact through our products.
What it does
Our Solution is an AI-powered remote/non-invasive Telediagnostic detection and screening tool for diseases and infections, saving trillions of pounds and millions of lives to effectively diagnose late-stage COVID-19. Our software tells you the percentage chance of having COVID-19 as well as relay vital information to the primary care specialist for further diagnosis. Our key differentiator from other AI software is that our powerful software can successfully distinguish between bacterial and viral infections.
In the hardware part, we plan to build a handheld portable microwave tomography system based on impulse radio ultrawideband (UWB) radar technology. Microwave tomography is the only non-ionising tomography technique which is not only safe for human beings but also is much more compact, cheap and fast. It generates images on par with CT scans to quickly image the internal human organs for on-the-spot decision making by health professionals, cutting the wait out of lengthy conventional tomography procedures using expensive equipment.
How we built it
We are using Imagenet to do transfer learning on 1000+ CT and X-Rays scans. With an API using Flast and Node.JS to serve data from our API to doctors/frontline staff via our Web App.
In the hardware part, we plan to build an impulse radio ultrawideband (UWB) radar based handheld microwave tomography system. Microwave tomography is the only non-ionising tomography technique which is not only safe for human beings but also is much more compact and cheap.
Challenges we ran into
Getting contacts in the healthcare industry and space has been a challenge to validate our idea, which we have partially overcome by interviewing two doctors and one clinical pharmacist until now.
Our further challenges include working with hospitals and the governments to guide the development of our product. Any contacts will be valuable.
Getting approval from the medical boards and the legal compliance will be the key challenges to address.
Accomplishments that we're proud of
We believe we are the best people to build this tech, as Kashif has a PhD in Radar technology with 13 publications and pioneered Radar-based remote telemetry technology for pedestrian safety, for which he has won the British Engineering Excellence Award in 2015.
Cyril has 5 years of experience in building startups. He worked Human-Computer Interaction Lab and built software for screening anxiety/depression and physical therapy that went on to get funding from the NSF and NIH. He has 3 patents issued with the design and software of Unmanned Aerial Vehicles.
What's next for TeleDoc
We are part of Entrepreneur First Accelerator and looking to take our product to market according to the following roadmap:
Jun 2020: AI-powered COVID-19 triage tool MVP release
Sep 2020: Radar-based remote pulse/heart-rate monitor prototype release. Also, AI triage tool final release.
Dec 2020: Radar-based remote pulse/heart-rate monitor final release. Also, Radar-based remote blood pressure monitor prototype release
Mar 2021: Radar-based remote blood pressure monitor final release. Also, Radar-based remote blood glucose monitor prototype release
Jun 2021: Radar-based remote blood glucose monitor final release. Also, Radar-based remote chest wall dynamics monitor prototype release
References
J. Marimuthu, K. S. Bialkowski and A. M. Abbosh, "Software-Defined Radar for Medical Imaging," in IEEE Transactions on Microwave Theory and Techniques, vol. 64, no. 2, pp. 643-652, Feb. 2016.
Paulson, C. N., Chang, J. T., Romero, C. E., Watson, J., Pearce, F. J., & Levin, N. (2005). Ultra-wideband radar methods and techniques of medical sensing and imaging. In B. M. Cullum, & J. C. Carter (Eds.), Proceedings of SPIE - The International Society for Optical Engineering (Vol. 6007). [60070L] [
https://doi.org/10.1117/12.630004
]
T. Lauteslager, M. Tømmer, T. S. Lande and T. G. Constandinou, "Coherent UWB Radar-on-Chip for In-Body Measurement of Cardiovascular Dynamics," in IEEE Transactions on Biomedical Circuits and Systems, vol. 13, no. 5, pp. 814-824, Oct. 2019
Y. Han, T. Lauteslager, T. S. Lande and T. G. Constandinou, "UWB Radar for Non-contact Heart Rate Variability Monitoring and Mental State Classification," 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Berlin, Germany, 2019, pp. 6578-6582.
Vejella, Sujitha. “A MEMS BASED MICROWAVE PIXEL FOR UWB RADAR BASED 3-D DIAGNOSTIC IMAGING.” (2017).
Lee, Y., Park, J., Choi, Y. et al. A Novel Non-contact Heart Rate Monitor Using Impulse-Radio Ultra-Wideband (IR-UWB) Radar Technology. Sci Rep 8, 13053 (2018).
https://doi.org/10.1038/s41598-018-31411-8
Semenov S. Microwave tomography: review of the progress towards clinical applications. Philos Trans A Math Phys Eng Sci. 2009;367(1900):3021–3042. doi:10.1098/rsta.2009.0092
Built With
css3
flask
html
keras
node.js
pm2
python
react
tensorflow
Try it out
bit.ly | TeleDoc - A late stage COVID-19 detection triage tool | AI-powered remote/non-invasive Telediagnostic detection and screening tool for diseases and infections | ['Cyril Lutterodt', 'Kashif Siddiq'] | [] | ['css3', 'flask', 'html', 'keras', 'node.js', 'pm2', 'python', 'react', 'tensorflow'] | 92 |
9,988 | https://devpost.com/software/healthhack-7vxsrp |
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HealthHack
Inspiration
The Frontliner Emergency Response Team
What it does
It has Emergency Contacts directly for first aid and the future Health Care System
How I built it
A system for Medical, Emergency Disaster Relief Team
Challenges I ran into
Understanding and Communication
Teamwork
Accomplishments that I'm proud of
Trainings and experience
What I learned
HEALTH HACK can be a useful system especially this time of emergency
What's next for HealthHack
First Aid
Health Care
Built With
emergency
google-contacts
health
health-and-human-services-syndication
language
science.gov
Try it out
www.covidhealthhack.com | HealthHack | A mobile App where you can update your health status, emergency contacts, first Aid techniques and best for Disaster Emergency Response | ['Maria Leonore Ares'] | [] | ['emergency', 'google-contacts', 'health', 'health-and-human-services-syndication', 'language', 'science.gov'] | 93 |
9,988 | https://devpost.com/software/things-to-do-during-covid-lockdown-which-will-really-help-u | This time is a time most people are never used to which will definitely create imbalance in some aspect of your life
Am sure if you follow some of this steps it will really help.
What's next for Things To Do During Covid Lock-down which will really help U.
THINGS TO DO DURING LOCK-DOWN PERIOD
1. Watch a film
Netflix and Amazon Prime aren’t your only options, and you don’t necessarily have to pay for a subscription to watch plenty of excellent films.
2. Watch a documentary
If you’re in the mood for something a bit more cerebral, there are a few websites that give you access to free documentaries.
Whether you’re into sharks, revolutions, or serial killers, you’ll find something interesting to watch during lock-down. Some great sites include “Documentary Tube, Top Documentary Films and Documentary Heaven”.
3. WRITE A NOVEL
Is it time for you to create rather than consuming?
If you’ve always wanted to write a novel but never found the time or inspiration, this is your chance. Apparently Shakespeare wrote King Lear in isolation during the plague, so maybe this lock-down is when you’ll write your opus.
4. WRITE A SONG
If you have a musical persuasion, you could channel your current emotions into a song or even an entire album of them.
5. TRY A FITNESS CHALLENGE
Missing the gym? There are plenty of fitness challenges you can try out from home, so you can emerge from lock-down fitter, leaner, or stronger.
6. COOK SOMETHING NEW
One good thing about being home a lot is that you can finally spend time cooking things from scratch.
You can find great recipes online, even if you’re on a limited budget.
7. PLAY A BOARD GAME
Board game lovers will be pleased to know that there are ways to play your favorite games online, so you don’t have to wait for the lock-down to end to try out your new Scythe strategy or to finally play Terra-forming Mars with a friend.
8. LEARN A LANGUAGE
Always wanted to speak different languages? Think that French will be useful for work, or perhaps German?
Lock-down gives you plenty of time to dedicate to learning a new language, brushing up on vocabulary, and testing out pronunciation.
9. DEEP CLEAN YOUR HOUSE
Between dusty skirting boards, dirty tiling, and stained carpets, your home can offer days of distraction if you feel like doing that deep clean you’ve been putting off.
There are plenty of online cleaning guide if the task looks too big, and focusing on one room at a time will help you divide up the work.
10. RESET YOUR HOME
Being stuck at home can make you rethink how much of your stuff you really need.
Do you really wear all the clothes spilling out of your wardrobe? And do you think you’ll really re-read those GCSE essays sitting in a box upstairs? You can decide what to donate and what to throw out, ready for a full clear out when the lock-down is lifted.
11. SCARE YOURSELF IN A CREEPY LIBRARY
If you’ve always been fascinated by the inspiration for Lovecraft, horror films, and far too many conspiracy theories, you can now read as many as possible books online.
12. STRETCH OUT WITH A YOGA CLASS
If you’re trying to DE-stress and stay healthy during lock-down, you’ll be pleased to know that plenty of yoga studios are now streaming online classes for you to join in with.
13. GO TO THE THEATER
When you can’t go to the theater, let the theater come to you.
Recorded performances are nothing new, but some platforms like Marquee are offering free trials so that you can see whether it’s something you’d want to watch on a more regular basis.
14. HAVE A WORK OUT
Keeping active will make a big difference to how you feel during lock-down – physical activity should help you sleep better and lift your mood, even if you’re stuck in the same room for most of the day.
You don’t need any equipment for a good workout, and there are plenty of free online videos to take you through a routine.
15. START A BLOG
This could be a great time to build your audience, especially if you have relatively cheap, indoor hobbies that you can share.
Interest in pastimes like cooking and board games has shot up over recent weeks – if your hobbies are trending, why not set up a blog and share your knowledge? You can set up a WordPress account and blog for free, and take it from there.
16. LEARN FIRST AID
It’s good to be prepared for an emergency, especially when urgent care centers are overwhelmed or you may not want to leave self-isolation for a relatively minor injury.
You can basic first aid online for free.
17. DISCOVER YOUR ROOTS
Wonder where your family was in the flu pandemic of 1918?
Tracing your family tree can unearth lost memories or even distant relatives. Start by learning about genealogy online and you can discover more about yourself and your background.
18. UNDERSTAND NUTRITION
Comfort eating during lock-down is understandable, but won’t help you enter summer happier and healthier.
Understanding nutrition and how food affects your body, health, and mood, will help you make better decisions for your overall well-being and even better use of your current food cupboard.
You can also search online for better understanding about nutrition.
19. MEDITATE
Meditation and mindfulness doesn’t just help people stay calm – practitioners around the world rely on it to help them focus, remain present, and appreciate what they have.
It’s a simple concept that can be hard to master, but you can start now at home, and see if it works for you.
20. PLAN A HOLIDAY
If you’re lucky enough to have a job that lets you work from home for this time, you’ve probably saved money on your commute and buying lunch each day.
Why not calculate how much you’ve saved through the lock down and put it towards a holiday?
You can plan an excursion at home, catching up on all the things you’ve missed, or go further afield to experience something new.
21. HAVE A KITCHEN DANCE PARTY
You can definitely have too much screen time. If workouts aren’t your thing or you just miss a good dance, put together a list of your favorite songs and dance around your kitchen.
Don’t worry, nobody’s watching!
22. SEW A TEDDY BEAR
Recreate a favorite childhood toy or just up cycle some old clothing by sewing your own teddy bear.
As long as you have some fabric that you can use (perhaps some socks or an old t-shirt) and a small sewing kit, you can get started.
23. PRAY
The last but not the least, always pray to God.
Built With
word | Things To Do During Covid Lockdown which will really help U. | These are some of the things you can do to keep body and soul together during this covid-19 lock down. i really think this article will help. happy reading. | ['ADEYEMI ADEBAYO MAYOWA'] | [] | ['word'] | 94 |
9,988 | https://devpost.com/software/coval-2za3si | Going Back To Business
COVAL is a community of businesses and customers that keeps each other safe by keeping the regulations together
The Unmet Need
Due to the Covid 19 pandemic, people across the globe are staying at home in quarantine, causing economic loss and social disruption. Naturally, this reality is not endurable in the long term. In the near future governmental restriction will gradually decrease, while the amount of infected people will increase. Therefore, keeping track of potentially infected individuals who are obligated in quarantine is of great importance. Navigating between the need for proper economical and cultural life under democratic doctrines, while maintaining discipline, regulations and sense of security among the people is one of the greatest challenges our society will face. Therefore, there’s a great need for a technological solution that will allow citizens and business owners to go back to normal routine in a responsible and controlled manner. In our perspective, this technological solution should include two components:
Regulation infrastructure ensuring the enforcement of quarantine warrants, mainly keeping infected and potentially infected out of crowded places.
Efficient epidemiologic research tool. This tool should allow a very accurate identification of people who were in the same places (supermarkets, restaurants, bars, etc) and at the same time as the confirmed covid-19 carriers, and alarm them.
Our Vision
In order to face this great challenge, a collective responsibility and discipline among the people must be formed. Our vision is to move democratic countries from a governmental based enforcement system, to a social based enforcement system. We believe that this approach will prove as a stronger tool than the orthodox governmental methodologies both in effectiveness and endurance, while preserving the citizens’ privacy.
COVAL
COVAL creates a controlled businesses’ entry mechanism. COVAL prevents covid-19 carriers / people who are obligated in quarantine from entering businesses using the platform. Furthermore, in the case that one of the users gets infected, COVAL updates immediately all the users who were in the same places at the same time with him in an anonymous manner.
Businesses choosing to be part of the COVAL community gain an efficient and simple enforcement mechanism which assures them that all their customers are feeling good and are not obligated in quarentune warrant or are infected, while maintaining minimal friction. The only way to enter a business that is part of the COVAL community is by using the COVAL app. The process of verifying the people entering the business is done by a doorman that verifies each customer through the COVAL app by picture and ID number.
Customers choosing to be part of the COVAL community gain the ability to enter places that are protected by the platform. The user will be able to see all the businesses working with the platform on a map relative to his position. The user can choose a business by clicking it on the map or by directly searching it on the search bar, much like google maps. When selecting a desired business, the user will see all the measures the desired business is using in order to keep customers safe as possible, as seen in the illustration. When arriving at the destination the user will be able to issue an entrance request, in order to enter the business, which in time the host\guard will have to approve. In addition the user will be asked to sign a declaration of good health and integrity, each time when entering a property. The registration to COVAL is done by scanning driver license/ID like in other apps.
Everytime that the user opens the app, the app verifies that the user is not obligated in quarantine by connecting to a designated API of the local Ministry of Health. In case the user is obligated in quarantine by law at that moment, the app is locked and an explanation is shown on the screen.
A log containing the times and places that the user has entered in the last 14 days is saved locally on the device. In the case that the user gets infected, his log will be transferred anonymously to all the users of the platform, so that each user will compare locally between his log and the anonymous log of the new covid-19 carrier - the comparison result will not be transferred to anyone. Then all users who have crossed paths with the new carrier will get an alarm, and a recommendation to report to the MoH.
This way COVAL protects the businesses and the customers while preserving the customers’ privacy. COVAL is a creative, practical and long term endurable solution to get back to normal life and restore the economies of the world.
Incentives
Customers:
reduce significantly the chance of getting infected in public spaces, maintaining a basic lifestyle, receiving a reliable indication in the case they should enter quarantine.
Businesses:
attracting customers by providing a “covid-19 free” environment, reduces the chance of having a covid-19 carrier in their business that could cause damage to their reputation and even a temporary shutdown in some cases.
Base assumptions
Large Scale - Assimilating the product among businesses and customers at deployment will be a great challenge. With the right marketing and cooperation we can incentivize businesses towards using the app.
Ministry of Health API - our product is based on the existence of an API provided by the local MoH, that allows users to check their current status - obligated in quarantine / not obligated in quarantine.
About us
Ori Gil-ad: Bsc in electrical engineering and physics from the Technion. Currently a graduate student in electrical engineering at TAU.
Shay Shimonov: Bsc in electrical engineering and physics. Currently completing a Msc in electrical engineering at the Technion.
Harel Mendelman: Currently undergraduate student in the electrical engineering faculty of the Technion.
Ron Gatenio: Bsc software engineering from the Technion.
Roy Schory: Bsc software engineering from the Technion.
Built With
firebase
flutter
flutter-(user-app)
react
Try it out
github.com | COVAL | Going Back To Business | ['harel123123 .'] | ['3rd Place Overall Winners'] | ['firebase', 'flutter', 'flutter-(user-app)', 'react'] | 95 |
9,988 | https://devpost.com/software/research-platform-9fvt73 | Covid-19
The project is being developed in cooperation with the Crisis_Managment_Plattform
This project is a new type of research and an unprecedented global project that connects scientists, researchers and inventors in a way that has never existed before.
The data, which is crucial for research, is compiled internationally and is available to all researchers, scientists and inventors of this platform.
However, this is not just an international scientific project, it also includes a sociological project. It is a triple scientific project that has a great future. Ask yourself the question of what progress we can make in all areas of research if, instead of 200 scientists, 50,000 scientists, researchers and inventors research the projects together. With an incredible range of knowledge and ideas Thum bundled on a platform for the benefit of all people. The planning and organizational measures result from the association of international scientists, researchers and inventors. With the help of this platform, they organize virtual meetings to conduct research. Data is analyzed by a team of experts and integrated into the platform, so that everyone on this platform is always up to date with the latest research. Users of this platform also have the opportunity To propose a certain page, for example a research institute, to our team and after an examination by a team and consultation with the operator of the page, this is intrigued, and research institutions can have your page integrated so that all users on the platform see the information on the page The good thing about this platform is that users can organize themselves, plan meetings and exchange information at any time. At the same time, users have the opportunity to publish their discoveries internationally with all users of the platform.
Who is actually behind this whole campaign?
My name is Michael Rhein, I managed the patent exploitation TIZ-NORD Wilhelmshaven Technical Innovation Center for Research and Patent Exploitation. When the pandemic started, I thought about the options for dealing with this crisis as quickly as possible. So in the beginning I looked for solutions on my own until I noticed that the solution can be found right here. Because of this, I thought about how I could bring as many people as possible together to find a solution together. However, it was clear to me from the beginning that this would only be possible with experts in the fields of science, research and the inventions or medical means of the inventors resulting therefrom and so I developed the project of the research platform. I was aware that this would and will present me with enormous challenges, but I will be able to master these together with everyone.
What about the rights?
I have long considered how to organize the legal part of this platform. Now I have found a solution for this too. All those who register on this platform simply agree that the rights to the research results made on the research platform, inventions for the benefit of mankind, to all users registered on the platform who are involved in the creation of this invention, solution or the research results are evenly distributed . This is an optimal solution for doing research together. To implement this regulation, users accept the general terms and conditions of the platform, in which all legal points are defined.
What does it look like financially? Who finances the whole thing?
This platform is not about making the greatest possible profit, rather it is about developing things together that can avoid such a situation as Coovid-19 or at least bring about a quick solution. I try to get political funding from the governments from which the scientists, inventors and researchers come, which are then distributed to the respective research institutes, scientists, researchers and inventors, for this I will put together a finance team. We are all human beings, we all live on this planet, let's develop technologies and opportunities together that we may not even be able to imagine today. This platform, like all of us, lives from constant change and adaptation. Together we all develop this platform, so we become part of it.
Built With
api
audio
google-analytics
google-translate
html5
java
javascript
php
video
Try it out
forschungsplattform.com
forschungsplattform.com | Research Platform | This project is a new type of research and an unprecedented global project that connects scientists, researchers and inventors in a way that has never existed before. | ['Michael Rhein'] | [] | ['api', 'audio', 'google-analytics', 'google-translate', 'html5', 'java', 'javascript', 'php', 'video'] | 96 |
9,988 | https://devpost.com/software/advertising-services |
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inspirasi wirausaha muda
memberikan pengetahuan tentang kejadian dan inspirasi
Built With
facebook
facebook-ads
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m.facebook.com | advertising services | Kedepanya bekerja keras memberikan informasi dan motivasi | ['M ugi Nusantara'] | [] | ['facebook', 'facebook-ads'] | 97 |
9,988 | https://devpost.com/software/covid-analyst | Our User Interface shown on a Laptop
Heat Map with Risk Assessment making use of US Census Data Set
Our main screen showing the Heat Map, News, and Chatbot
Inspiration
Specific, region-targeted information surrounding COVID-19 is hard to come by. At best, a search on Google can get you the number of reported cases for your state along with countless news articles with questionable accuracy. We wanted to create an information hub for everything you need to know about COVID-19 in your region.
What it does
COVID Analyst uses machine learning and spatial data analytics with a combination of reliable data sources and research publications to give you an address-level risk heatmap of COVID-19 in your area. In addition, it scrapes credible news outlets to give you a feed of news in your area and an AI-powered chatbot will answer any questions you may have about COVID-19.
Key Features:
A risk heat map of your region created using published statistics from WHO and APM Research Lab and data from JHU and the US Census through spatial data analytics and machine learning.
A web scraper that provides the user with relevant, credible COVID-19 news in their region.
A chat bot that answers questions pertaining to the website and COVID-19 using live data and can conduct a symptom-based screening.
What separates us:
Our map provides information on an address-by-address level.
We were the first ones to receive and work with a dataset including race/gender/age information for the US from AMP Research Lab (American Public Media Lab).
How I built it
Using socio-economic information from Census Tracts (data such as poverty rate, education, race-ethnicity, population pyramid, proximity to health care, and old age, we produced heatmaps to find communities that are at higher risk for COVID-19. Data is extracted and stored in a spatial data model, and we use machine learning to evaluate the risk factor based on published statistics as weights.
Our web app is fully integrated with Google Cloud, running on App Engine, and using Places API and Dialogflow for the chat AI. We used React.js/Node.js for our web stack and conducted scraping with Node.js using Puppeteer.
Challenges I ran into
We were faced with hardware limitations (it took much more time than expected to process the data), so our app is currently limited to Wake County, North Carolina.
What's next for COVID Analyst
We started this as a sample for Wake County North Carolina (population about 1.1 million) but this work can be easily scaled to the entire US with the appropriate resources and time. We can also create a native mobile application along with the web app.
Built With
dialogflow
google-cloud
node.js
places-api
puppeteer
react
Try it out
github.com
covidanalyst.tech | COVID Analyst | AI-powered targeted analytics for the COVID-19 pandemic | ['Can Koz', 'Marina Tai', 'John Javad Roostaei'] | ['1st Place Overall Winners', 'Google Cloud 2nd Place', 'Track Winner: Health & Fitness'] | ['dialogflow', 'google-cloud', 'node.js', 'places-api', 'puppeteer', 'react'] | 98 |
9,988 | https://devpost.com/software/balancever-your-balanced-daily-routine | Brand
Our mission
Problem
Research
Research
Personas
The solution
Why?
Platform
Technology
Team
Inspiration
For many weeks several million people are in home office to slow down the spreading of COVID-19 and avoid our medical system to collapse. COVID-19 is not only a question about life and death, it’s also about the functioning of our economy and our mental and social well-being.
By moving our workplace from the offices to our homes, the boundary between work and life vanished. This can lead to long and lonely working hours and imbalanced life styles.
We had to stop hobbies and social interactions, throwing us into a new life situation. Many people struggle to structure their day and stay motivated. By the end of the day we feel mentally drained, physically exhausted and socially isolated.
What it does
We created a platform that can help structuring a work day effectively, provide suggestions what to do during breaks and free time and display a work-life balance score.
With Balancever you can generate a structure for your day, boost your efficiency and avoid long working hours.You can select diverse activities for your break and free time. Every users can also suggets ideas and share with their collegues and friends.
Find your online Yoga class, connect with friends for a coffee or browse through fun events. Balancever is a one-stop shop that helps you to shape your new remote lifestyle. Stay home, stay healthy, stay energized, stay connected, stay balanced.
How I built it
Design Thinking, Adobe XD, Adobe Illustrator, Adobe Premiere, Adobe Photoshop, Dreamweaver, Android Studio, Flutter, Firebase and Github
Challenges I ran into
Creating a solution for people that works in remote mode. The solution’s impact to the crisis is creating more connections where there is social distance, the product helps against the stress at home, help the economic system
Accomplishments that I'm proud of
Creation of a platform customized for desktop and mobile, with a engaging user experience. Integration of apps needed for wellbeing and events/activities.
What I learned
To transform remote working in smart working, you need to think about human well-being.
What's next for Balancever
After build it we have to populate it, create the content, be in contact with the online content creators (and we help the economic system at the end) and provide a product that can be improved by every stakeholders. Live video share events for peer to peer connect, sleep monitoring.
The value of our solution after the crisis
It's a product that you can always use, because help you to be in balance, working at home, working in the office. It's helpful for companies that will have employee more relaxed, more productive and in balance, for every workers, for everyone.
GitHub Repository
https://github.com/balancever
Prototype
https://xd.adobe.com/view/d0df8f06-659f-44ab-9e45-f67787fd553a-858c/?fullscreen
Mobile Platform User Experience
Link to see the first user experience:
https://youtu.be/-pULEcAUI2k
Follow us
https://balancever.eu
Built With
adobe-creative-suite
adobe-illustrator
adobexd
amazon-web-services
android
android-studio
design-thinking
firebase
photoshop
react
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xd.adobe.com | Balancever | Balancever is a platform to help remote workers improve their well-being and productivity by enhancing their work-life balance. | ['www.balancever.eu', 'Francesca Sanfilippo', 'Maurizio De Magnis'] | ['Challenge Winner', 'The Wolfram Award'] | ['adobe-creative-suite', 'adobe-illustrator', 'adobexd', 'amazon-web-services', 'android', 'android-studio', 'design-thinking', 'firebase', 'photoshop', 'react'] | 99 |
9,988 | https://devpost.com/software/eleutherios-alpha | Linear supply chain that scales or aggregates the service or supply chain
Circular supply chain that scales or aggregates the request or conversation
Aggregating, scaling or serializing a circular supply chain or process using a computer or Turing machine.
Eleutherios
Eleutherios (
https://eleutherios.org.nz
) is a platform that makes it easier for people or businesses to cooperate with one another or serve their customer's through a common forum or request.
Problem
The current human supply chain is linear or tries to scale the service or work that people or businesses are performing. For example, if a person was hungry and had $10 to buy food, they might order online and spend $5 on a pizza, $2 on a drink and $3 to have the items delivered to their house.
In this scenario the person can only scale their request or conversation for food, three times. Once for pizza, a second time for a drink and a third time for a delivery service.
The problem is the financial supply chain is forcing the food and logistic supply chain into a linear or one-to-one relationship with the service and the request.
request = $5 (finance supply chain) for pizza (food supply chain)
request = $2 (finance supply chain) for drink (food supply chain)
request = $3 (finance supply chain) for delivery (logistic supply chain)
Solution
Serialize or circularize the supply chain by scaling the customer's forum, request or conversation that they are having with people or businesses, not the service or work that they are trying to perform.
For example, if a person was hungry and isolated at home, they could register with Eleutherios and create a forum for some food. A food store owner could register as a service in the system and subscribe to the forum and ask the person what food they wanted? The food store owner could gather the food from their store and scale the forum by creating a sub-forum for a healthcare worker to help with the delivery of the food. The healthcare worker could scale the sub-forum again and create another sub-forum for a delivery service and accompany the delivery service and be the person that delivers the food to the isolated person.
In this example, it is the forum or request that is being scaled, not the service or work that people or businesses are performing. By delegating the forum or request to services in this way, means that more than one service or supply chain (i.e. civilian, food, healthcare and logistics) can participate in the forum or request at the same time.
Features:
Forum in forum (sustainability/manageability).
Tags for filtering forums or services (searchable).
Alerts to keep users informed when new forums or services are created in the system (notifiable).
Blocking to prevent unwanted services or users from serving in forums they have been asked not to serve in or for requesting services, they have been asked not to request (accountability).
Service reviews (accountability).
B2B or shared processing (scalability).
AI (automatable).
Eleutherios is built with an HTML/javascript (Angular) frontend and node.js (nosql/firebase) backend.
https://eleutherios.org.nz
Discuss or provide feedback.
https://www.facebook.com/groups/2982366048442234/
Help fix bugs or resolve issues.
https://github.com/aletheon/eleutherios-alpha/issues
Make a donation to the Eleutherios open source project.
https://opencollective.com/eleutherios
Built With
circular
css
html
javascript
supply-chain
typescript
Try it out
eleutherios.org.nz
github.com | Eleutherios | Global cooperative forum or supply chain | ['Rob Kara'] | [] | ['circular', 'css', 'html', 'javascript', 'supply-chain', 'typescript'] | 100 |
9,988 | https://devpost.com/software/medical-facility-tracking | Register Hospital Page
Update Information Modal
Home Page
Inspiration-
As we know the Corona virus outbreak is the biggest global issue right now. Currently COVID patients can only go to
government hospitals for checkup, and private facilities are not allowed to consult such cases. However, it is only a matter of time before the public infrastructure gets overwhelmed and the government will need to work with various private hospitals for treatment of COVID patients. In that situation, government and people will need transparent information of the private medical facilities and infrastructure.
What it Does-
The web application provides a platform where hospitals and other health facilities which can provide treatment during COVID-19 or any other probable pandemic can register themselves. The hospitals will update the platform with information such as availability if beds, ICU beds and doctors. All this information will help the government monitor the condition of healthcare infrastructure of the country. The application will also display the nearest facilities that are currently providing treatment, hence potential patients seeking treatment can use this application to get to the right place at the right time.
How I built It-
The tech stack includes: Python, Flask framework, MongoDB, HTML, CSS, Javascript and jQuery.
Challenges-
I typically prefer LAMP stack for my projects. But for this, I decided to learn a new development stack that is, Python, Flask and Mongo. Learning a new stack and creating a project with it was challenging and fun at the same time.
What I Learnt-
I am proud that finally I learnt a new development stack that too in just a single day. I also learnt about how the healthcare industry operates and how availability of transparent information can help prevent outbreaks like this in future.
Whats Next-
If anonymous medical details of patients were available to all, COVID outbreak could've been anticipated a long time ago and the situation would not have become this big. Medical Facility Tracking application intends to store patient's medical history anonymously on public Blockchain. This will be like an unified platform used all over the world.
Built With
css
flask
html
javascript
jquery
mongodb
python
Try it out
github.com | Medical Facility Tracking | Track hospitals and health infrastructure easily and seek treatment | ['Anubhav Dutta'] | [] | ['css', 'flask', 'html', 'javascript', 'jquery', 'mongodb', 'python'] | 101 |
9,988 | https://devpost.com/software/fanspeage |
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There is nothing impossible
Inspiration
I see a lot of people don't understand using pages
What it does
So everyone knows what the page from the yard is
How I built it
Memberikan kelas pembelajaran tentang cara menggunakan dan fungsi halaman
Challenges I ran into
Lots of people who don't want to listen no matter they don't know how important a page is
Accomplishments that I'm proud of
Patience and trust that person is an achievement that I am proud of whether or not the success is important that we have tried
What I learned
I learned a lot where a page that can make a business grow in the market. Patient learning invites people to join must be trusted with trust
What's next for Fanspeage
Development, I want fanspeage to develop rapidly even though I know it takes time for that
Built With
libaries
Try it out
www.facebook.com | Fanspage | I want to develop the page into a good and correct structure where everyone who visits it is more focused on that page | ['Komarudin Komarudin'] | [] | ['libaries'] | 102 |
9,988 | https://devpost.com/software/covaid-19 | Splashscreen
Covid_19
The problem is people's fear of corona disease, so a questionnaire has been done to find out whether the condition is sound or suspicious, and upon confirmation, an addiction panel appears to know the affected areas after their location is known through the map
Built With
dart
firebase
flutter
kotlin
objective-c
Try it out
github.com | covid_19 | Know location patient and quiz to person to know find covid_19 or not | ['Abdelrahman Ali'] | [] | ['dart', 'firebase', 'flutter', 'kotlin', 'objective-c'] | 103 |
9,988 | https://devpost.com/software/beating-covid-19 | super hearo's of today
GIF
Inspiration
all the doctors and nurses that is super hero's who risk there life every day
What it does
How I built it one step at a time
Challenges I ran into every day i deal with people from the tyson and other places that has tested positive
Accomplishments that I'm proud of i have beaten the virus several times since april
What I learned don't believe everything you hear on social media and the news
What's next for beating covid-19 staying healthy
Built With
english | beating covid-19 | A sure way of beating the covid-19 | ['jimmy campbell'] | [] | ['english'] | 104 |
9,988 | https://devpost.com/software/peeker-subr6c | Peeker
Module with Rechargeable Battery Case
Front and Back View
Our Seekr Team has grown!
The problem our project solves:
My grandfather is visually impaired and depends on others to do everyday tasks. Given that he is reliant on touch, we are worried that he will be susceptible to COVID-19. This has led him to struggle with self-isolation because of having no companionship, also making him more prone to emotional distress during this period of self-isolation.
This is the reality of 200 million people who are visually impaired around 188 countries. And research shows that the number is expected to triple within the next 4 decades. As social and emotional well-being is of the utmost importance for these marginalized people, the Peeker aims to provide life-long companionship and alleviate emotional distress.
The solution we bring to the table:
The Seekr is a personalized, interactive voice-assistive device with a bone-conducting earpiece. To use the Seekr, the user does not require any technical knowledge and can interact freely and independently. The user interface is designed in such a way to imitate the human interaction of able-bodied people. The bone-conducting earpiece does not block their natural senses and the rotating clip allows for convenient placement of the device
There are two main features of the Peeker 1) Inbuilt thermal imaging sensors which alerts the visual impaired of other people with high body temperatures around them 2) Text and Object detection through which the Peeker will alleviate loneliness and allow the experience of live companionship during this period of self-quarantine.
What we have done during the Hackathon:
We have developed a working prototype of the Peeker with standard features such as object and text detection within the course of the hackathon. The working prototype also receives speech input from the user and responds using voice output, making it a complete interactive device. In addition, we have developed the 3D design of our proposed final product, keeping minimalistic design, user experience, and fashion in mind.
To ensure that our features meet the needs of the visually impaired, we met some visually impaired workers in the front-line such as those working at restaurants, convenience stores, and NGOs to test our prototype and discuss which features would be most useful to them even after the COVID-19 pandemic.
We have also conducted thorough market research to analyze our competitors and have realized that there is no product like the Seekr especially with its adaptable and customized features. According to research, there are many other devices within the assistive device market, however, 39.9% of differently-abled people do not like to wear such devices as it usually is very bulky and medical equipment like or is blocking some of their senses. Hence, our device offers quality services without blocking any of their natural senses.
The solution’s impact on the crisis:
Our solution is simple. The Peeker protects the visually impaired from people with high body temperatures who might be susceptible to COVID-19. This is to encourage social distancing and reduce the chances of getting COVID-19.
Furthermore, the Seekr’s objective is to reduce reliance on touch so that the visually impaired are not in contact with the surfaces unnecessarily through its features. Finally, the interactive component of the device engaged the visually impaired to alleviate emotional distress by offering companionship and living independently. For instance, the Peeker allows the visually impaired to conduct activities such as reading a book, distinguishing between different objects, reading road signs, etc. which they otherwise could not do without a helping hand.
The necessities to continue the project:
Currently, our prototype is deployed on the Raspberry Pi. Going forward, we would like to design the integrated circuit of the final product ourselves, so the device is more compact and durable. In addition, our product will also have a silicone cover which is easily identified by the visually impaired.
Our current solution is trained on the COCO-object detection dataset, restricting the number of total objects detected to 80. Going forward, we want to train the model with our dataset focusing on the common items that the visually-impaired person uses on a daily basis.
Subsequently, we will partner up with manufacturing companies to mass-produce the Seekr. We are also looking to collaborate with NGOs, Governmental Organisations, Optometrists, and Eye Hospitals to develop more user-friendly features so that every Seekr is customized to the needs of the individual.
The value of our solution after the crisis:
The Seekr allows independence with ease to the visually impaired through Peeker. For example, they would be able to go grocery shopping with the help of text detection. They would be able to navigate where things are with the help of object detection. Other added features within the premium package such as different languages, haptic feedback accessories, heart rate, and blood pressure monitor, face recognition, and color detection ensures that the Peeker is a life-long companion that accommodates the visually impaired no matter which demographic they are from.
Built With
coco
opencv
pytesseract
python
pyttsx3
raspberry-pi
speech-recognition
yolo | Seekr | Your Visual Companion | ['Turzo Bose', 'Lamia Sreya Rahman', 'Kartikay Sharma'] | ['2nd Place', 'Top 10', '1st Place Hack'] | ['coco', 'opencv', 'pytesseract', 'python', 'pyttsx3', 'raspberry-pi', 'speech-recognition', 'yolo'] | 105 |
9,988 | https://devpost.com/software/spark-k6txdh | Inspiration
- Needed a place to track and plan our projects.
- Frustrated over apps that are specialized to do only one thing resulting in having to keep many tabs/apps open at the same time.
- Saw a need for an all-in-one productivity app.
- Believed it had the potential to increase the productivity of those affected by COVID-19.
What it does
- Features: Calendar, Tasks, Team Administration, Project Tracking, Messages, Meetings and Zoom Integration, Discussion Board
- A cumulative productivity app that puts all the apps you need into one
- Assists teams and organizations by improving productivity and tracking the progress of projects
- Highlights team collaboration with SparkRooms to coordinate team members
How we built it
- Written in HTML/CSS/JS, Python
- Written in Visual Studio Code
- Utilized Travis for continuous deployment and autonomous configuration
- Divide and Conquer - Frontend, Backend
- Git, VSCode Live Share, and Discord
Challenges we ran into
- Responsiveness & Mobile compatibility
- Rendering iframes on the dashboard
- Saving arbitrary user data within Firestore
- Git collisions: Committing changes to the same lines at the same time
Accomplishments that we're proud of
- Firebase for hosting, database, and authentication
- Fully functional login system with Google Oauth 2.0 Authentication
- Dashboard to render iframes to show lots of content in a single page
- Travis CI/CD
- Lots of backend and Javascript to process website
What's next for Spark
- Expand Spark for function enterprise and educational usage
- Increase responsiveness of site to enable mobile usage
- Create a way to send personal messages to team members
- Create more tools for users eg. a personal File Storage Method
Built With
bootstrap
css3
flask
fullcalendar
google-cloud
html5
javascript
jquery
node.js
python
travis-ci
Try it out
sparkapp.cf
github.com
docs.google.com | Spark | An intuitive and empowering all-in-one productivity application. | ['Raadwan Masum', 'Rohan Juneja', 'Safin Singh', 'Aadit Gupta'] | ['Wolfram Honorable Mention', 'Track Winner: Work & Economy'] | ['bootstrap', 'css3', 'flask', 'fullcalendar', 'google-cloud', 'html5', 'javascript', 'jquery', 'node.js', 'python', 'travis-ci'] | 106 |
9,988 | https://devpost.com/software/findthecluster | High-level overview
Analysis from actual data.
Architecture
(previously called "FindTheCluster")
Inspiration
Getting tested for COVID-19 can be challenging due to the limited availability of testing kits and overwhelming patient load on healthcare systems. Many individuals may only be mildly symptomatic, or asymptomatic - but they are often overlooked and deprioritized to undergo testing.
What it does
CheckIfCovid is a self-reporting survey for symptoms which calculates the probability of a COVID-19 infection based on the participant’s input. It works by training the data collected from other participants' responses and the data from confirmed COVID-19 cases to calculate the likelihood that the reported symptoms are associated with COVID-19.
Features
Instant assessment
- Immediately know the probability that you have COVID-19 based on self-reported symptoms
Geolocated symptoms
- Plot out all symptoms in a map and identify clusters. Have you ever wondered if all occupants within the building you live in are also experiencing persistent cough?
Privacy secured
- No personally identifiable information will be stored.
Third-party Integration
- integrate with existing health systems through our
API
. If you own a product, we encourage to integrate (and anonymize) your data.
How do we collect data
Survey
- Self-reported symptoms
Scrapers
- We get data of confirmed COVID-19 cases from CSSEGIS, ECDC, GISAID, KAGGLE.
Benefits
Provide data to the government to run more targeted testing on identified clusters.
More information dissemination or resources can be deployed to the identified clusters.
Provides awareness to occupants of the identified clusters.
Predict the probable locations of the next outbreaks.
Teams
We are currently organized into 3 teams and have a corresponding team page:
Survey App (
https://github.com/orgs/findthecluster/teams/survey-app
)
API App (
https://github.com/orgs/findthecluster/teams/api-app
)
Data Science (
https://github.com/orgs/findthecluster/teams/data-science
)
Slack room:
https://app.slack.com/client/T0103C6KMKM/C010RKNQ5QC
Related solutions
We found out there are similar solutions to our Survey app:
https://covidnearyou.org/#!/
https://covid.joinzoe.com/
https://www.apple.com/covid19/
https://github.com/ch-covid-19/welcome
https://fevermap.net/
https://flatten.ca/#home
https://howwefeel.org/
What we want to achieve is a call to unify these data in a single location, standardize it, and apply machine learning. We will open the
API
and data to institutions that need them.
Challenges
Lack of dataset that had cases who reported symptoms and then tested negative. We mainly used unsupervised learning to determine whether the given symptoms of a case and it's proximity to one of the identified clusters will likely test positive
Built With
next
node.js
python
react
typescript
Try it out
github.com
checkifcovid.com | CheckIfCovid | Calculate the probability of COVID-19 based on symptoms and location | ['Mark Santiago', 'Diana Zhong, MD', 'Glory Adedayo', 'Siddharth Pathak', 'Mohamed Abdelrehim', 'Rashnil Chaturvedi', 'Maria Christina Kalogera', 'Dominik Einkemmer', 'Yaakov Bressler', 'Sebastian-Sye Klute', 'Efren Macasaet', 'Prince Owusu Attah', 'Jason Lee', 'Benjamin Von Wong'] | [] | ['next', 'node.js', 'python', 'react', 'typescript'] | 107 |
9,988 | https://devpost.com/software/covid-feel-good | The "Secret Garden" VR experience
CNBC coverage of our work (25 April 2020)
The home page of the web site
The protocol page in the web site
The logo of the project
## Inspiration
Living in the time of the coronavirus means experiencing not only a global health emergency but also
extreme psychological stress
that puts a strain on our identity and our relationships. The coronavirus and the associated quarantine forces us to manage
three different psychological dilemmas simultaneously
:
the stress of the disease,
the disappearance of places,
and the crisis of the sense of community.
In fact, the coronavirus pandemic
is having a significant effect on people’s mental health that requires urgent support
.
On one side,
is currently difficult to find to any form of psychological support
. The social isolation of the quarantine and the economic downturn are limiting the possiblity of accessing to mental health specialist with the risk of a rise in conditions like anxiety, depression and addictions.
On the other side, one of the paradoxes of coronavirus is that
despite being a problem, it can also be a unique opportunity
. In fact, willingly or unwillingly, it forces us to change and manage new situations such as quarantine, close coexistence with children and spouse, lack of relationships, and so on.
This process of change can be dramatically boosted by transformative experiences
, forcing individuals to critically examine and eventually revise their core assumptions and beliefs. Unfortunately, most transformative experiences cannot be planned in advance, but happen suddenly in individuals’ lives, without a prior control on their contents and their effects.
## What it does
This protocol uses the power of virtual reality to provide a
transformative experience
that can help individuals in two ways:
By providing a digital place in which subjects can relax and reflect;
By facilitating a process of critical examination and eventually revision of core assumptions and beliefs.
In particular we used the rules defined for an effective design of Transformative Experiences, to develop the "Secret Garden" VR experience and its weekly protocol you can find in the
Covid Feel Good web site
.
For a long time,
the main barrier to a broad use of VR technology was its cost
. However, now the simplest and cheapest form of VR comprises nothing but a pair of magnifying lenses and a sheet of cardboard or a plastic box. These headsets
sell for 15–30 USD
. and use a standard smartphone as a tracker and display to generate the three-dimensional (3D) environment. Mobile-based VR is particularly suited to a specific VR content that can be very useful to address the coronavirus stress:
360-degree videos
.
360-Degree videos have the power to virtually transport users, immersing them in the video recording, allowing them to actively explore its content and experience the video from any angle.
As recently demonstrated by Li et al.
, these videos have the ability to induce specific emotions characterized by different levels of valence and arousal. More,
as shown by Robertson and colleagues
the neural representations of the part of the 360-degree video presented in VR (the scene within the current field of view) prime the associated representations of the full panoramic environment, facilitating subsequent perceptual judgments. In other words, 360-degree videos generate a dynamic interplay between memory and perception that can be used to improve the features of these cognitive processes and to update their contents.
## How we built it
"The Secret Garden" Virtual Reality immersive experience has been developed through an integrated process involving psychologists, 3D artists, musicians, storytellers and designers. This immersive experience storyboard has been:
written by
wellbeing psychologists
;
converted in a VR experience by
3D specialists
using the
Unreal engine
technology (with complex post-production activity related to VR conversion);
it has been sounded by
musicians
and then dubbed by a
professional dubber
. We used the Augmented Relaxation approach involving deactivating human threat protection system and activating soothing system (see
"Emotion Regulation Systems" theory
;
finally, the protocol has been designed by a team of
clinical and cognitive psychologists
.
## Challenges we ran into
A significant challenge for any psychological intervention during the quarantine is the
ratio between accessibility and efficacy
. Our goal was not to provide a full structured psychological intervention, but to
build the "surgical mask" of mental health support
.
Surgical Masks do NOT provide the wearer with a reliable level of protection against coronavirus (20%) versus the 95/99% of FFP2 and FFP3 masks.
However, they are very effective in protecting others from the wearer’s respiratory emissions, and their use is significantly better than wearing a scarf.
Here, we try to do the same.
The goal of this VR protocol is not to solve complex mental health problems, but rather to reduce the burden of the quarantine by relieving anxiety and stress and improving interpersonal relationships.
Additionally, by facilitating self-reflectiveness and constructive exchange with relevant others, it improves our ability to adapt to the challenges and take advantage of the opportunities offered by the Coronavirus.
## Accomplishments that we're proud of
We have already completed the protocol and the VR experience in English, Italian, Spanish and Catalan
. You can test it now in the
Covid Feel Good web site
. We are now working to produce the experience in other languages and with more contents.
## What we learned
Creating easy tools for mental health is not easy
. In particular it is difficult to
balance the difficulty and the involvement required with the efficacy of the process
. In this view, focusing on clear goals and simplifying as much as possible the technology needed improves the efficacy of the system.
## What's next for COVID Feel Good
We want to start a
multicentric controlled study to verify the efficacy of the presented approach
. Our goal is to reach at least 240 subjects in three months.
More, at the moment COVID Feel Good is a self-help VR experience. The next step is
to add the clinicians in the process, by developing a set of easy VR tools to empower them
.
Built With
unreal-engine
Try it out
www.covidfeelgood.com | COVID Feel Good | An easy self-help virtual reality protocol for coping with the psychological burden of Coronavirus. | ['Brenda Wiederhold', 'Luca Bernardelli', 'Riva Giuseppe'] | [] | ['unreal-engine'] | 108 |
9,988 | https://devpost.com/software/wecare-5l9dgi | Home Screen of app, which allows you to report your symptoms, check the status of your circle, and get daily personalized tips.
Map Screen of app, which allows you to see hotspots around you and your Care Circle.
Care Circle screen of app, which allows you to health conditions of your loved ones.
Web interface, which can be used to update the symptoms. It is synced with the app.
New logo.
Update with a key.
Hotspots for countries.
Options from the start.
Questions about your health.
Hot spots.
App design
As the outbreak of COVID-19 continues to spread throughout the entire world, more stringent containment measures from social distancing to city closure are being put into place, greatly stressing people we care about. To address the outbreak, there have been many ad hoc solutions for symptom tracking (e.g.,
UK app
), contact tracing (e.g.,
PPEP-PT
), and environmental risk dashboards (
covidmap
). However, these fragmented solutions may lead to false risk communication to citizens, while violating the privacy, adding extra layers of pressure to authorities and public health, and are not effective to follow the conditions of our cared ones. Unless being mandatory, we did not observe the large-scale adoption of these technologies by the crowd. Until now, there is no privacy-preserving platform in the world to 1) let us follow the health conditions of our cared ones, 2) use a statistically rigorous live hotspots mapping to visualize current potential risks around localities based on available and important factors (environment, contacts, and symptoms) so the community can stay safer while resuming their normal life, and 3) collect accurate information for policymakers to better plan their limited resources.
Such a unified solution would help many families who are not able to see each other due to self-quarantine and enable early detection and risk evaluation, which may save many lives, especially for vulnerable groups. These urgent needs would remain for many months given that the quarantine conditions may be in place for the upcoming months, as the outbreak is not reported to occur yet in Africa, the potential arrival of second and third waves, and COVID-19 potential reappearance next year at a smaller scale (like seasonal flu). There is still uncertain information about immunity after being infected and recovered from COVID-19. Therefore, it is of paramount importance to address them using an easy-to-use and privacy-preserving solution that helps individuals, governments, and public health authorities.
WeCare Solution
WeCare is a cross-platform app that enables you to track the health status of your loved ones. Individuals can add their family members and friends to a Care Circle and track their health status and get personalized daily updates on best prevention practices. In particular, individuals can opt-in to fill a simple questionnaire, supervised by our epidemiologist team member, about their symptoms, comorbidities, and demographic information. The app then tracks their location and informs them of potential hotspots for them and for vulnerable populations over a live map, built using opt-in reports of individuals. Moreover, symptoms of individuals will be tracked frequently to enable sending a notification to the Care Circle and health authorities once the conditions get more severe. We have also designed a citizen point, where individuals get badges based on their contributions to solving pandemic by daily checkup, staying healthy, avoiding highly risky zones, protecting vulnerable groups, and sharing their anonymous data.
WeCare includes a contact tracing module that follows the guidelines of Decentralized Pan-European Privacy-Preserving Proximity Tracing
(PEPP-PT)
. It is an international collaboration of top European universities and research institutes to ensure the safety and privacy of individuals.
What we have done during the weekend
Have been in contact with other channels in Brazil and Chile.
We have updated the pitch (extended), app-design and backend connection of the app this week. New contacts with Chile and Singapore. We have also made some translation work with the app. Shared more on social media about the project and also connected to more people on slack and LinkedIn. We have also modified the concept of Care Circle and how to add/remove individuals. Now, the app is very easy-to-use with minimal input (less than a minute per day) from the user. We are proud of the achievements of our team, given the very limited time and all the challenges.
Challenges we ran into
The Hackathon brought together plenty of people of different expertise and skills. There were challenges that we faced that were very unique, as we faced a variety of communication platforms on top of open-source development tools.
Online Slack workspaces and Zoom meetings and webinars presented challenges in forms of inactive team members, cross-communications, and information bombardment in several separate threads and channels in Slack and online meetings of strangers that are coordinated across different time zones. In developing the website and app for user input data, our next challenge was in preserving the privacy of user information.
In the development of a live hotspot map, our biggest challenge here was to ensure we do not misrepresent risk and prediction into our live mapping models.
Also for the testing of the iOS version, we ran to the new restriction of App Store for COVID-related apps, which should be backed up by some health authorities or governmental entities.
The solution’s impact on the crisis
We believe that WeCare would help many families who can see each other due to self-quarantine and enable early detection and risk evaluation, which may save many lives, especially for vulnerable groups. The ability to check up on their Care Circle and the hotspots around them substantially reduces the stress level and enables a much more effective and safer re-opening of the communities. Also, individuals can have a better understanding of the COVID-19 situation in their local neighbourhood, which is of paramount importance but not available today.
The live hotspot map enables many people of at-risk groups to have their daily walk and exercise, which are essential to improve their immunity system, yet sadly almost impossible today in many countries.
The concept of Care Circle motivates many people to invite a few others to monitor their symptoms on a daily basis (incentivized also through badges and notifications) and take more effective prevention practices.
Thereby, WeCare enables everyone to make important contributions toward addressing the crisis.
Moreover, data sharing would enable a better visual mapping model for public assessment, but also better data collection for the public health authorities and policymakers to make more informed decisions.
The necessities to continue the project
We plan to continue the project and fully develop the app. However, to realize the vision of WeCare we need the followings:
Public support: a partnership with authorities and potentially being a part of government services to be able to deploy it on AppStore. It also makes WeCare more legitimate. This would increase the level of reporting and therefore having a better overview and control of the crisis.
Social acceptance: though being confirmed using a small customer survey, we need more people to use the WeCare app and share their data, to build a better live risk map. We would also appreciate more fine-grained data from the health authorities, including the number of infected cases in small city zones and municipalities.
Resources: So far, we are voluntarily (and happily) paying for the costs of the servers. Given that all the services of the app and website would be free, we may need some support to run the services in the long-run.
The value of your solution(s) after the crisis
The quarantine conditions and strict isolation policies may still be in place for upcoming months and year, as the outbreak is not reported to occur yet in Africa, the potential arrival of second and third waves, and possible COVID-19 reappearance next year at a smaller scale (like seasonal flu).
Therefore, we believe that WeCare is a sustainable solution and remains very valuable after the current COVID-19 crisis.
The URL to the prototype
We believe in open science and open-source developments. You can find all the codes and documentation (so far) at our
Website
.
Github repo
.
Pitch:
https://youtu.be/7fMrVqxoPKY
Pitch extended version:
https://youtu.be/Vo0gs3WlptU
Other channels.
https://www.facebook.com/wecareteamsweden
https://www.instagram.com/wecare_team
https://www.linkedin.com/company/42699280
https://youtu.be/_4wAGCkwInw
(new app demo 2020-05)
Interview:
https://www.ingenjoren.se/2020/04/29/de-jobbar-pa-fritiden-med-en-svensk-smittspridnings-app
Built With
node.js
python
react
vue.js
Try it out
www.covidmap.se
github.com | WeCare | WeCare is a privacy-preserving app & page that keeps you & your family safer. You can track the health status of your cared ones & use a live hotspot map to start your normal life while staying safer. | ['Alex Zinenko', 'Sina Molavipour', 'Ania Johansson', 'Hossein S. Ghadikolaei', 'Christian M', 'Seunghoon HAN', 'Tomasz Przybyłek', 'Mohamed Hany', 'Alireza Mehrsina'] | ['1st Place Overall Winners', '2nd Place'] | ['node.js', 'python', 'react', 'vue.js'] | 109 |
9,988 | https://devpost.com/software/helps-to-use-less-examination-of-corona-virus-slices |
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Inspiration
What it does
I have just idea no more, but I think it helps too much
How I built it
Challenges I ran into
Accomplishments that I'm proud of
What I learned
What's next for helps to use less Examination of Coronavirus slices
helps to use less Examination of Coronavirus slices | helps to use less Examination of Corona virus slices | helps to use less Examination of Corona virus slices | ['Mohammed Eleyan'] | [] | [] | 110 |
9,988 | https://devpost.com/software/faco-fight-against-corona-jfcza9 | GIF
Confusion matrix for our final model
INSPIRATION
A diagnosis of respiratory disease is one of the most common outcomes of visiting a doctor. Respiratory diseases can be caused by inflammation, bacterial infection or viral infection of the respiratory tract. Diseases caused by inflammation include chronic conditions such as asthma, cystic fibrosis, COVID-19, and chronic obstructive pulmonary disease (COPD). Acute conditions, caused by either bacterial or viral infection, can affect either the upper or lower respiratory tract. Upper respiratory tract infections include common colds while lower respiratory tract infections include diseases such as pneumonia. Other infections include influenza, acute bronchitis, and bronchiolitis. Typically, doctors use stethoscopes to listen to the lungs as the first indication of a respiratory problem. The information available from these sounds is compromised as the sound has to first pass through the chest musculature which muffles high-pitched components of respiratory sounds. In contrast, the lungs are directly connected to the atmosphere during respiratory events such as coughs, heart rate.
PROBLEM STATEMENT
In this difficult time, a lot of people panic if they have signs of any of the symptoms, and they want to visit the doctor.
It isn’t necessary for the patients to always visit the doctor, as they might have a normal fever, cold or other condition that does not require immediate medical care.
The patient who might not have COVID-19 might contract the disease during his visit to the Corona testing booth, or expose others if they are infected.
Most of the diseases related to the respiratory systems can be assessed by the use of a stethoscope, which requires the patient to be physically present with the doctor.
Healthcare access is limited—doctors can only see so many people, and people living in rural areas may have to travel to seek care, potentially exposing others and themselves.
SOLUTION
We provide a point of care diagnostic solutions for tele-health that are easily integrated into existing platforms. We are working on an app to provide instant clinical quality diagnostic tests and management tools directly to consumers and healthcare providers. Our app is based on the premise that cough and breathing sounds carry vital information on the state of the respiratory tract. It is created to diagnose and measure the severity of a wide range of chronic and acute diseases such as corona, pneumonia, asthma, bronchiolitis and chronic obstructive pulmonary disease (COPD) using this insight. These audible sounds, used by our app, contain significantly more information than the sounds picked up by a stethoscope. app approach is automated and removes the need for human interpretation of respiratory sounds, plus user disease can also be detected by measuring heart beat from camera of smartphone.
The application works in the following manner:
User downloads the application from the app store and registers himself/herself.
After creating his/her account, they have to go through a questionnaire describing their symptoms like headache, fever, cough, cold etc.
After the questionnaire, the app records the users’ coughing, speaking, breathing and heart rate in form of video from smartphone.
After recording, the integrated AI system will analyze the sound recording, heart rate comparing it with a large database of respiratory sounds. If it detects any specific pattern inherent to a particular disease in the recording, it will enable the patient to contact a nearby specialist doctor.
The doctor then receives a notification on a counterpart of this app, for doctors. The doctor can view the form, watch the audio recording, and also read the report given by the AI of the application.
The doctor, depending upon the report of the AI, will develop a diagnosis, suggest medicines, or recommend a hospital visit if the person shows symptoms of corona or other serious condition.
In cases where the AI detects a very seriously ill patient, it will also enable the physician to call an ambulance to the users’ location and continuously track the user.
HOW WE ARE GOING TO BUILD IT
We will take a machine learning approach to develop highly-accurate algorithms that diagnose disease from cough and respiratory sounds. Machine learning is an artificial intelligence technique that constructs algorithms with the ability to learn from data. In our approach, signatures that characterize the respiratory tract are extracted from cough and breathing sounds. We start by matching signatures in a large database of sound recordings with known clinical diagnoses. Our machine learning tools then find the optimum combination of these signatures to create an accurate diagnostic test or severity measure (this is called classification). Importantly, we believe these signatures are consistent across the population and not specific to an individual so there is no need for a personalized database Following are the steps the app will take:
Receive an audio signal from the user's phone microphone
Filter the signal so as to improve its quality and remove background noise
Run the signal through an artificial neural network which will decide whether it is an usable breathing or cough signal
Convert the signal into a frequency-based representation (spectrogram)
Run the signal through a conveniently trained artificial neural network that would predict the user's condition and possible illness
Store features of the audio signal when the classification indicates a symptom
IMPACT
FACO will help patients get themselves tested at home, supporting in areas where tests and access to tests are limited. This will help democratize care in hard-to-reach or resource-strapped areas, and provide peace of mind so that patients will not overwhelm already stressed healthcare systems. Doctors will be able to prioritize patients with an urgent need related to their speciality, providing care from the palm of their hand, limiting their exposure and travel time.
CHALLENGES WE RAN INTO
No financial support
Working under quarantine measures
Working in different time-zones
Scarcity of high-quality data sets to train our models with
One Feature Related Problem- Legal shortcomings we might face when adding the tracking patient feature
ACCOMPLISHMENTS
We went from initial concept to a full working prototype. We got a jumpstart on organizational strategy, revenue and business plans—laying the groundwork for building partnerships with healthcare providers and pharmacies. On the creative side, we built our foundational brand and design system, and created over 40 screens to develop a fully working prototype of our digital experience. Our prototype models nearly the entire app experience—from recording respiratory sounds to reporting to managing contact, care, and prescriptions with physicians. Technologically, we successfully developed an algorithm for disease and have begun the application development process—well on our way to making this a fully functional product within the next 20 days.
You can explore the
full prototype here
or
watch the demo
(and
check out our promo gif
)!
WHAT WE'VE DONE SO FAR
We wanted to show that the project is feasible. Scientific literature has shown that audio data can help diagnose respiratory diseases. We provide some references below. However, it is unclear how reliable such a model would be in real situations.
For that reason, we used a publicly available annotated
dataset
of cough samples:
It is a collection of audio files in wav format classified into four different categories.
We wrote code in Python that converts those samples into MEL spectrograms. For the time being we are not using the MEL scale, just the spectrograms. We did several kinds of pre-processing of the signals, including data augmentation, then convert all pre-processed signals, along with their categories into a
databunch
object that can be used for training artificial neural networks created in the fastai library. The signals within the databunch were divided into training and validation sets.
Because the dataset size was reduced, we used
transfer learning
. That is, we used previously trained networks as a starting point, rather than training from scratch. We treated the spectrograms as if it were images and used powerful models pre-trained to classify images from large datasets. In particular, we tried both two variants of
resnet
and two variants of
VGG
differing on their depth (number of hidden layers). This approach implied turning the sprectograms into image-like representations and normalizing them according to the statistics of the original dataset our models were trained on (imagenet). We first changed the head of the networks to one that would classify according to our categories and trained only that part of the net,
freezing
the rest. Later on we
unfroze
the rest of the net and further trained it. We finally compared the different models by the confusion matrices that we obtained from the validation test. We finally settled on a model based on
VGG19
. We exported the model for later use in classifying audio samples through the pre-existing interface of our mobile app.
The results are promising, especially considering the small amount of data that we have available at this moment. We have included an image of the final confusion matrix that shows how our current network can correctly classify all four categories of signal about 50% of the time, far better than the random level of 25%. We conclude that wav files obtained trough a phone mic provide information that can be useful for diagnosing respiratory condition. We are confident that we can vastly improve both the sensitivity and the specificity of our model if we can gain access to larger, more representative datasets.
We provide an image of the final confusion matrix for our model in the gallery.
This is a
repository
that contains the most important pieces of our work, including some code, the confusion matrix image and the exported final model.
SUMMARY
We are developing digital healthcare solutions to assist doctors and empower patients to diagnose and manage diseases. We are creating easy to use, affordable, clinically validated and regulatory cleared diagnostic tools that only require a smartphone. Our solutions are designed to be easily integrated into existing tele-health solutions and we are also working on apps to provide respiratory disease diagnosis and management directly to consumers and healthcare providers.
Feel free to click on our
website
for more information. We developed this website using Javascript, HTML, CSS, Figma, and integrated it with Firebase to manage hosting and our database. Thank you for reading, and don't hesitate to reach out if you have any questions!
REFERENCES
Porter P, Claxton S, Wood J, Peltonen V, Brisbane J, Purdie F, Smith C, Bear N, Abeyratne U,
Diagnosis of Chronic Obstructive Pulmonary Disease (COPD) Exacerbations Using a Smartphone-Based, Cough Centred Algorithm, ERS 2019, October 1, 2019.
Porter P, Abeyratne U, Swarnkar V, Tan J, Ng T, Brisbane JM, Speldewinde D, Choveaux J, Sharan R, Kosasih K and Della, P,
A prospective multicentre study testing the diagnostic accuracy of an automated cough sound centered analytic system for the identification of common respiratory disorders in children,
Respiratory Research 20(81), 2019
Moschovis PP, Sampayo EM, Porter P, Abeyratne U, Doros G, Swarnkar V, Sharan R, Carl JC,
A Cough Analysis Smartphone Application for Diagnosis of Acute Respiratory Illnesses in Children, ATS 2019, May 19, 2019.
Sharan RV, Abeyratne UR, Swarnkar VR, Porter P,
Automatic croup diagnosis using cough sound recognition, IEEE Transactions on Biomedical Engineering 66(2), 2019.
Kosasih K, Abeyratne UR,
Exhaustive mathematical analysis of simple clinical measurements for childhood pneumonia diagnosis, World Journal of Pediatrics 13(5), 2017.
Kosasih K, Abeyratne UR, Swarnkar V, Triasih R,
Wavelet augmented cough analysis for rapid childhood pneumonia diagnosis, IEEE Transactions on Biomedical Engineering 62(4), 2015.
Amrulloh YA, Abeyratne UR, Swarnkar V, Triasih R, Setyati A,
Automatic cough segmentation from non-contact sound recordings in pediatric wards, Biomedical Signal Processing and Control 21, 2015.
Swarnkar V, Abeyratne UR, Chang AB, Amrulloh YA, Setyati A, Triasih R,
Automatic identification of wet and dry cough in pediatric patients with respiratory diseases, Annals Biomedical Engineering 41(5), 2013.
Abeyratne UR, Swarnkar V, Setyati A, Triasih R,
Cough sound analysis can rapidly diagnose childhood pneumonia, Annals Biomedical Engineering 41(11), 2013.
FACO APP VIDEO DEMO
LINK
FACO PRESENTATION
LINK
FACO 1st Pilot Web App
LINK
Built With
android-studio
doubango
fastai
firebase
google-cloud
google-maps
java
machine-learning
mysql
numpy
pandas
python
pytorch
sklearn
sound-monitoring-and-matching-api
spyder
webrtc
Try it out
github.com | FACO: Fight Against Corona | A contactless digital healthcare solution to assist doctors and empower patients to diagnose and manage diseases | ['Archit Suryawanshi', 'Oghenetejiri Agbodoroba', 'Ntongha Ibiang', 'Sahil Singhavi', 'Ruthy Levi', 'Navneet Gupta', 'Mohamed Hany', 'Prachi Sonje', 'GAVAKSHIT VERMA', 'Shraddha Nemane', 'snikita312', 'Gauri Thukral', 'udit agarwal', 'Francisco Tornay', 'Rubén Aguilera García'] | ['1st place', 'The Best Women-Led Team'] | ['android-studio', 'doubango', 'fastai', 'firebase', 'google-cloud', 'google-maps', 'java', 'machine-learning', 'mysql', 'numpy', 'pandas', 'python', 'pytorch', 'sklearn', 'sound-monitoring-and-matching-api', 'spyder', 'webrtc'] | 111 |
9,988 | https://devpost.com/software/smart-ventilators-pq2nwa | Side View Of the final Ventilator Attachment assembly in FUSION 360
Side View Of the final Ventilator Attachment assembly in FUSION 360
Top View Of the final Ventilator Attachment assembly in FUSION 360
Isometric View Of the final Ventilator Attachment assembly in FUSION 360
Isometric view Of the final Ventilator Attachment assembly in FUSION 360
Back View Of the final Ventilator Attachment assembly in FUSION 360
this is the actual 4T arrangement sitting inside the model
Valve with inlet and outlet pipe
Inspiration
As we know the world needs a helping hand in this difficult time period and ventilator shortage is a really big issue across globe. I come from India where we have only 20,000 ventilators for 1.3 billion population which is almost 1 ventilator for every 65,000 people. This condition inspired me to do something for the humanity, since i am doing mechanical engineering I targeted mechanical ventilators and tried to increase its efficiency to the fullest
What it does
I have made and special attachment which can be attached to any ventilator. this attachment is nothing just a simple 4T pipe splitting into 4 at the end which can be attached to the outlet of ventilator to use a single ventilator for multiple patient. Now the hack is that I have attached an unidirectional flow control valve at the ends of these junction this allows us to control pressure in each pipe an also stops cross contamination which enables it to be used in any situation irrespective of the type of patient we have
Also all these flow control valves are connected to micro controller which is further connected to an APP which enables a single doctor to regulate many ventilators and much more patients just through a tap of a button in the app
How I built it
I used Autodesk Fusion 360 to design the 4T pipe and the flow control valve and used the same software for the assembly of the same (4T pipe and unidirectional flow control vale )
Further I have Made and entire assembly which exactly reflects how the real world attachment will look like
I did flow simulations on ANSYS and used ANSYS Fluent tool for taking out computational fluid dynamics of the flow and taking out different pressures and calibrations to achieve a viable scale for the APP
IOT part is done on Arduino micro controller and IOT modules like Node MCU etc for the control of these valve
Making an APP for this setup so that the doctor can control all of them through an APP
Challenges I ran into
TO find appropriate pressure stats for an ventilator and developing perfect calculations for the pressure calculations
Since I am a mechanical engineer so i don't have much knowledge of these IOT although i have made a simple IOT model in Proteus but i wasn't able to make a very good code for the same
The biggest challenge with which i am still struggling is to build the APP due to no knowledge of the APP i am searching for someone who can help me in coding aspects of IOT and building APP part for the project
What I learned
A lot more about fluid dynamics, building equations and getting results out of iy. Tackling new challenges like methods of stopping cross contamination without any additional part . Generating an ideas so that it can meet every aspect like cost, application, etc
What's next for Smart Ventilators
Trying to build a really good APP for it and refining codes for IOT part so as to make the system more and more effective and easy to use
Built With
autodesk-fusion-360
cfd
iot | Smart Ventilators | The idea is to optimize a single ventilator multiple patient system and reduce the need of ventilator assistance doctors by providing an app to control these valve from anywhere any time | ['Akash Pandey'] | ['Wolfram Honorable Mention'] | ['autodesk-fusion-360', 'cfd', 'iot'] | 112 |
9,989 | https://devpost.com/software/zero-contact-uav-bot | Ardu Pilot Software
AA Interactive Form to collect Input
UAV Weather Forecast For Pre-Flight Checks
Mission Planner
UAV / Drone Taking off
Access Database for Logging
Sky Vector for logging Aeronautical chart
Code snippet in step level (MainTask)
Code snippet (Sub Task Module) for Input
Inspiration
The Novel Corona-virus has affected humanity in various ways, be it our economy, our freedom of movement, and the loss of loved ones. Something that struck me was elderly people having to wait in a queue for medicines at an outlet. Even though there are home delivery services, the risk of infection is extremely high as this job requires you to move around places at a higher rate and I recollected news of people infected by pizza delivery agents / Swiggy agents throughout India on multiple occasions. The Lockdown definitely has slowed down the infection rates but we are forgetting that all essential services are not contactless. That's when I decided to create a solution to this by using a Drone / UAV to Deliver essentials and medicines primarily for the vulnerable among us so that we ensure they are safe, Drones are usually manually remote-controlled by a pilot. Me myself being an aerospace engineer with focus on Avionics and with Automation Anywhere. I decided to use an AutoPilot Mission Planner to write coded commands to the Flight controller in order to make the Flight Autonomous and deliver the essential package and return home.
From the News
Bengaluru on superspreader alert after delivery boy tests positive
-
Click here to read
83-year-old man collapses while waiting in New World queue in New Lynn
-
Click here to read
Features in a nutshell
Interactive User input
Database Logging
Autonomous UAV Flight
Automated Pre Flight Checks
Address to Geo Coordinates conversion
Distance, Payload release altitude Calculation
AutoPilot Command creation (Flight Plan)
Payload Delivery (Essential package Delivery)
Scalability
What it does
The Bot collects the delivery address and input data using Interactive forms and converts the address string into location coordinates using Geocoding API and uses Python Script to calculate the Flight Distance using Haversine Formula based on the range of the UAV and Performs Pre-Flight Checks such as Wind speed, Temperature, Precipitation Probability, Cloud Cover, Visibility and more. It also checks for any nearby airport and logs the Aeronautical charts for the way-points using Sky Vector web service. It then Sends Flight information to the DGCA for Flying permission via API. It then calculates the payload release altitude based on logic using the Indian regulatory guidelines for construction. Finally, the bot compiles this information to create a flight plan command and uses the Mission Planner which is Ground Control Software to write the code into the Flight controller AutoPilot using a wireless transmitter and launches the UAV on its mission. While doing this each flight is tracked by a unique flight control number and logged to a database for future audit and compliance purposes and folder is created with Logs, charts, and autopilot code. Hence this Bot enables users to completely automate the Pre-Flight processes and automate the creation of code for Autonomous UAV Flight which will Deliver the payload (Essential Package) at the desired location and return back home and complete the mission. This makes the complete process contactless and safe. Hence serving the essential needs of the most vulnerable and reducing the infection rate.
How I built it
This RPA Solution is Built on Automation Anywhere A2019 and integrates with various technology as mentioned below, which is the real beauty of RPA.
Microsoft Bing Geocoding API
Python 3.8.3
Ardu Pilot Mission Planner ( with wireless transmitter )
Interactive Forms
UAV Forecast Service
Sky Vector Chart Service
DGCA API
Microsoft Access Database
UAV / Drone & Payload release mechanism
Challenges I ran into
One of the challenges was to use complex mathematical formulae using Python to derive certain parameters. However, the Python Package on A2019 made it really easy to call Python functions inside and code and get the output. Also creating a waypoint plan for the Autopilot was initially a challenge however using the product documentation I was able to create the flight plans using Log to file package making all the values dynamic.
Accomplishments that I'm proud of
I am happy that I was able to use my academic knowledge in Aerospace, my work expertise in Robotic Process Automation, and my curiosity to explore new possibilities in creating this solution which can help the world in this traumatic situation. I am also happy that I was able to bring out the true sense of Anywhere in the name "Automation Anywhere".
What I learned
It was indeed a great experience to develop this bot with a lot of research, trial & error and new learnings. I was able to start off with Python and I'm looking forward to trying out further possibilities.
What's next for Zero Contact UAV Bot
The RPA solution can be scaled up for usage with Queue (WLM) and to further improvise and add on more features. To make the solution more independent we can have a "Raspberry Pi" attached to the drone and connected to the Flight controller and the Internet. We can install AA Bot agent on the Raspberry Pi running windows and we can remotely deploy the automation considering the Drone as a bot runner with wings ;). This drone will be a fully automated solution for an Autonomous Flight using Robotic Process Automation as the base Technolgy.
Other areas of usage
Delivery Services
Search and Rescue Facilities
Climbers and Firefighters
Mine and Oil Industry
Military and Gaurd Services
Disaster Relief Services
Built With
api
ardupilot
automationanywhere
autonomousuav
flightcontroller
geocodingapi
missionplanner
payloadreleasemechanism
python
skyvector
uavforcast
Try it out
github.com | Zero Contact - Essentials Delivery UAV Bot | The Bot creates and executes an Autonomous Flight Plan for a UAV / Drone based on Guidelines for Contact less Delivery of Essential commodities during the pandemic. | ['Manuel Varghese Philip'] | ['The Wolfram Award', 'First prize', 'Gold'] | ['api', 'ardupilot', 'automationanywhere', 'autonomousuav', 'flightcontroller', 'geocodingapi', 'missionplanner', 'payloadreleasemechanism', 'python', 'skyvector', 'uavforcast'] | 0 |
9,989 | https://devpost.com/software/khousto-entergy-com-liheap-outreach-bot | I work for a public utility that services Louisiana, Mississippi, Texas, and Arkansas. As of 2016, 37% of our customers experienced an energy burden above the national threshold.
The federal government has a program, Low Income Home Energy Assistance Program, or “LIHEAP” that assists low-income households, particularly those with disproportionately high energy costs, to cover their home energy costs by making payments directly to the customers’ utility provider.
Customers can receive LIHEAP assistance by contacting agencies across the state and applying for a LIHEAP grant. Historically, the agencies have not had the adequate marketing resources to notify the communities they serve that assistance may be available to them. We have tried manual outreach campaigns in the past, but they are costly and time-consuming with a limited subset of customers able to be contacted.
With the onset of COVID-19, some of the hardest hit financially have been our low-income customers. The pandemic created a more pressing need to get LIHEAP information to low-income customers who may need more assistance than ever in paying their electric bill.
Additionally, with the passing of the CARES Act, an additional $900 million was given to LIHEAP so there are now more funds than ever for our customers to receive.
We created a bot to assist with the customer outreach informing them of the LIHEAP program and instructing how to apply for a LIHEAP grant.
First the LIHEAP bot pulls all customer data on a weekly basis. This consists of demographic information along with any past due bill amount. The bot then compares the customer information with credit information to find those whose annual household income is $35,000 or less. Using both sets of data, the bot will create a subset containing only those whose annual household income is $35,000 or less and who have a past due bill of greater than $125. Using this subset of customer data, the bot then does a geographic comparison by zip code to find the closest LIHEAP agency by customer. The LIHEAP bot then contacts the customers via email and auto-dialer letting them know they may be eligible to receive a LIHEAP grant, provides them with the contact information (address, phone number, email, and website) for the closes LIHEAP agency, and in the email outreach includes an infographic of a guide to applying for a LIHEAP grant.
The bot runs every week in production and currently contacts about 75,000 customers each week. From the first week’s running, we found that of the customers who went through the process and received a LIHEAP grant, the average grant was almost $500. At scale, we estimate that we should see over $1 million in LIHEAP grants given to our eligible customers.
This bot positively impacts all stakeholders of our company; it helps our low-income customers by assisting them in receiving grants to pay their electric bill, it supports our communities by informing them of options available to them, the grants also reduce our potential electric disconnects and lowers bad debt write-off to the company, supporting our shareholders’ interests, and assists our employees by performing an outreach that would have previously been done manually for a minute subset of who the bot is able to contact.
Built With
automation
Try it out
github.com | LIHEAP Outreach Bot | Create a bot to reach out to low-income utility customers and provide them with info on how to receive a federal grant for bill payment assistance | ['Katie Houston'] | ['Second prize'] | ['automation'] | 1 |
9,989 | https://devpost.com/software/central-patient-register | Process Flow Chart
Pie Chart for Top diseases with most number of people affected in district
Line Chart for Patients Corresponding to Different DiseasesAgainst Age
Inspiration
Covid-19 pandemic situation in India as well as all districts but districts level authorities don’t have idea about the patients and diseases information. So, this process provided the all information about the patient and diseases then district level authorities easy to handle this type of the situation.
What it does
• Collect the patient details in standard format from the all district level hospitals.
• Bot will segregate data disease wise and will generate the evident data through chart as well
• Bot will generate the different types of report (clustering the types of disease originating in particular area ) and bot will send the all information to district level authorities.
Additionally: BOT can categorically post the same updates on district portal
How we built it
• Patient registration form filled by hospital.
• Bot will collect all patient information from district level hospital.
• Bot will merge the all hospital of patients information.
• Bot will show the age wise bar chart and disease wise pie chart.
• Bot will highlight the district as well as show the count patient and disease wise in map.
• Bot will send email with all reports to district level authorities.
Challenges we ran into
• AA 2019 being very different compared to previous versions was itself a challenge to understand and work upon.
• To implement idea of Central Patient Register on National level and to collect and manage huge data was bit of challenging
Accomplishments that we're proud of
• To get the desired Outputs what has been thought of and decided in the Project Planning Phase.
• Got well Equipped with the new functionalities added in AA2019, like extracting and writing excel data through table format, incorporating Python to analyses the collected data.
• Proud to generate the reports that could help India as a whole to be aware from the CORONA pandemic and insights of the hotspots areas to avoid spreading contamination and take necessary precautions.
What we learned
• Correct Data collection and analysis could play the vital role in predicting the future danger and to prepare ourselves for the corresponding precautions
• AA2019 has come up with new add-ons that enhanced the data analysis capacity and the scope of automation.
What's next for Central Patient Register
• Bot can maintained those information state wise.
• Bot can maintain the accidental cases and other cases.
• Bot can categorically post the same updates on district portal.
Built With
dashboard
excel
folium
forms
javascript
matplotlib
pandas
python
web
Try it out
drive.google.com | Central Patient Register | During any pandemic situation the most crutial thing is timely communication between the hospital and the administration.Our BOT consolidates the data and generates the insight for administration. | ['Shruti Kirti', 'Ashish Dhakate', 'Swapnil Shelke', 'Nidhi Jain'] | ['Third prize'] | ['dashboard', 'excel', 'folium', 'forms', 'javascript', 'matplotlib', 'pandas', 'python', 'web'] | 2 |
9,989 | https://devpost.com/software/covid-hero | chifa - the covid hero chatbot
web page
chatbot chat session
Inspiration
Since the outcome of fast-growing pandemic Covid-19, it has become important for us as an individual to keep a minimum distance from other well beings that we call social distancing. It has become important to know the precautions and so one may face many doubts and queries related to COVID. To keep us aware and to answer the COVID related queries we have developed a chatbot called COVID-hero that will guide you throughout this global disaster.
How we built it
This app lets you know the coronavirus cases in your country. It’s more than statistics, it’s also helped the user to know what the Do’s and Don'ts in this pandemic are. It also helps to know the symptoms of COVID-19.
Permit to the invalid persons (blind or illiterate) scan QR and that 'll read for us the notice
Remember the drugs taking time for persons who's has Alzheimer for example
There is also an option for self-screening. You can use it to test yourself whether you have coronavirus or not.
Challenges we ran into
This project deals with API and Dialog flow. API will let you the exact data of the country. Most members we new with dealing with API. They were knowing what API means but didn't do a practical project. This was taking time busting for us. Most importantly, we were having time timezones so our coordination was not establishing among each other. This project needs a lot of attention.
Accomplishments that we're proud of
At last, we planned our whole work which team members have to do what. Due to timezone, we establish a common time we all met and discuss our work. We successfully created the chatbot with teamwork and consistency. As most of them never experienced any hackathon. Everyone shows their teamwork and at last created our project at best.
What we learned
With teamwork we accomplish our project. We learn team collaboration and remotely working. We all learn new technology like trending one chatbot. We learn HTML/CSS and javascript. We deal with APIs and dialog flow. We know how the frameworks work. The most important thing we learn consistency and teamwork which makes this project successful. Our connections increased with this hackathon.
What's next for COVID-hero
We are planning to introduce this website on a large scale. We will be adding more features like Doctor consultancy, showing data through graphs, and informing the nearest hospital with an SMS. We will work on the website and make it more useful by adding a sign-in feature. We will also create a chatbot for the hospital. With data collected we will make more usefull and more intelligent the chatbot to permit anticipate users illness.
Built With
css
dialogflow
html
javascript
node.js
Try it out
covid-hero.herokuapp.com
github.com | covid-hero | BE AWARE STAY SAFE WITH YOUR TRUE COVID-FRIEND --Covid-hero | ['SOULEYMANE TOURE', 'Rahul Sinha', 'Subhayu Kumar Bala', 'apmit2704 Mittal'] | [] | ['css', 'dialogflow', 'html', 'javascript', 'node.js'] | 3 |
9,989 | https://devpost.com/software/whatsapp-and-rpa-automated-loan-application-processing | Inspiration - The time taken to process loan application when I applied for a loan and the current COVID-19 scenario where people have lost their job and would like to apply for a loan
What it does - It automated the application process and helps the user to apply for a loan, get details on FAQ for loan document, etc. right from his mobile using bank authorized WhatsApp channel then all the documents are collected via the bank website and verified against 6 parameters by RPA Bot and then it forms the user with the application status in less than 5 min. Alos the bak gets the data to perform analytics on it which will help the bak to take key business decisions based on the data collected.
How I built it - Level -1 WhatsApp bot integrated with NLP, Level-2 Website to collect user data, Level-3 RPA bot with Work Load management to do the heavy lifting of multiple verifications for the data and match them against submitted documents.
Challenges I ran into - WhatsApp free trial with limited functionality, barcode reading with python as free libraries have limited options.No access to user information from Cibil and Experian website which is publicly available hence had to use dummy values
Accomplishments that I'm proud of - Created this whole project in less than 24 hours and the learning of coalescing 3 different technologies to create a unified solution.
What I learned - When we try to solve a real-life problem the ideas and bring this into action drive us and also RPA when combined with next-gen technologies, can be if used to cater multiple un-explored solutions.
What's next for WhatsApp and RPA Automated Loan Application Processing - Creating an ML library to do predective Analysis and create another way of automating this where the user can directly fill the details and uploads documents from WhatsApp along with multi-lingual support..
Built With
a2019
api
barcode-reader
iqbot
lamp-stack
natural-language-processing
php
python
rest
whatsapp | WhatsApp and RPA Automated Loan Application Processing | We leverage WhatsApp to help the applicant apply for a loan and then all the different verifications are handled by the BOT which then updates the applicant via WhatsApp and email | ['Avinash Raj'] | [] | ['a2019', 'api', 'barcode-reader', 'iqbot', 'lamp-stack', 'natural-language-processing', 'php', 'python', 'rest', 'whatsapp'] | 4 |
9,989 | https://devpost.com/software/chatbot-using-ibm-watson-automation-anywhere-and-ai | Android
flask
Noise reduction
node-red
Automation Anyhere api call
Inspiration
Started when my employees worried of getting sick and scared of going outside, So I reaches out to Dr. anjali and started working on this project.
What it does
It will give active cases near you, you can ask queries reagarding covid-19, detect coughing
How we built it
We built it using python , C
Challenges we ran into
It has taken tremendous effort to build this during the hackathon. Including training multiple AI model in limited amount of time, Configuring IBM cloud, Node-red application, Building a flask RESTful app, android application and also integrating with AA
Accomplishments that we're proud of
Building succesful model
What we learned
Building AI models, IBM and AA platform features
What's next for Chatbot using-IBM-Watson Automation Anywhere and AI
Including more complex automation using AA
Built With
c
flask
python
Try it out
github.com | Chatbot using-IBM-Watson Automation Anywhere and AI | A chatbot to periodically get alert of Covid-19 active cases near your location, cough detection and health enquiry. Everything pushed to an API, where the company can check their employees health | ['Nandakishor M', 'anjali m'] | [] | ['c', 'flask', 'python'] | 5 |
9,989 | https://devpost.com/software/smart-checking | SMART
Checking
Inspiration
I have travelled during 'lockdown' and found out that travel in COVID-19 era is hard. It requires longer hour, many health-related checking and a lot of documents.Therefore, a simpler way for checking travellers COVID-19 era would be crucial.
What it does
SMART Checking use bot to automate checking travellers documents, extract data,and gain insights from the documents. So, any decision could be made in much shorter time.
How I built it
SMART checking is built using Automation Anywhere Enterprise A2019
What's next for SMART Checking
Bot for more documents format.
Built With
a2019 | SMART Checking | SMART Checking: Automated Document Checking for Travelling in COVID-19 Era | ['Tri Labs'] | [] | ['a2019'] | 6 |
9,989 | https://devpost.com/software/face-mask-recognition-for-covid-19 | End - To - End COVID-19 Solution
Face Mask recognition:
What it does : The application identifies who all in the image are wearing a face mask. It can be used for single person image or even group image.
How we built it : Python code first identifies the number of faces in the image. Then it checks whether every face has a mask on it or not. Once python checks for face mask in every image, automation anywhere BOT will create a report to show how many people had face mask or not
Challenges we ran into : Create a object detection algorithm from scratch was a difficult task as it required proper environment setup and integration.
Accomplishments that we're proud of: The algorithm is accuracy is same as that any prebuilt object detection recognition tool in market
What we learned: Building python algorithms from scratch and also integrating them with RPA tools
What's next for Face mask recognition for COVID-19 : we are working on a full fledged solution for COVID19 were the algorithms for face mask, face recognition, social distancing, temperature check will all be integrated with automation anywhere and the final report will have details of all
Built With
python
Try it out
github.com | Face mask recognition for COVID-19 | Face recognition + RPA will be able to identify potential risk in Corporates | ['Abhinay Deshmukh', 'Allen Richy', 'Jagruti Dama', 'Saurabh Talawdekar'] | [] | ['python'] | 7 |
9,989 | https://devpost.com/software/covid19-infobot | Inspiration
People are in great misconceptions and believing myths regarding Covid 19. So, I wanted to create a bot which can be a fact machine for everybody
What it does
This info bot is capable of telling latest data of covid19 cases in India and fact regarding covid 19
How I built it
Its built using dialogflow and nodejs webhook.
Challenges I ran into
Implementation of webhook and creating a bot was very new to me this is my first chat bot
Accomplishments that I'm proud of
I have made the bot capable of bursting myth of covid19.
What I learned
Dialogflow, NodeJs and ExpressJs
What's next for Covid19 Infobot
I want to implement languages like hindi and want to make it more capable of giving facts. Apart from that I want it to give more details on live covid19 data so it can fetch data for every city.
Built With
bot
covid19
dialogflow
express.js
heroku
node.js
react
redux
Try it out
bot.dialogflow.com
souravdey777.github.io
github.com
github.com | Covid19 Infobot | Idea is to create an awareness chatbot that is easily accessible through different apps Assistants, or via the website. Knowledge giving and capability of telling latest info of covid19 cases in India | ['Sourav Dey'] | [] | ['bot', 'covid19', 'dialogflow', 'express.js', 'heroku', 'node.js', 'react', 'redux'] | 8 |
9,989 | https://devpost.com/software/forgeconnect-automate-bot | ForgeConnect Automate Bot automates the creation of apps in the Atlassian cloud.
Try it out
bitbucket.org | ForgeConnect Automate Bot | ForgeConnect Automate Bot automates the creation of apps in the Atlassian cloud. | ['Warp Smith'] | [] | [] | 9 |
9,989 | https://devpost.com/software/autocode | Architecture Diagram
Problem Statement
Our Inspiration
COVID-19 has forced most of us to work from home for the last 3 months or so and now we realize that it may soon become the new normal. This transition has brought new challenges to our workdays. At the end of each day, many of us have felt burnt out and we have been looking for productivity-improving tools and techniques. All of us felt the need of a personal assistant, who could help us summarize the meeting points in a deck, who could create flow charts/architecture diagrams out of handcrafted notes and send it to different stakeholders, who could help in creating mock-up web pages, and so on. While such an assistant would always be an asset; in current times, it can prove to be a game-changer.
What it does?
We as developers, always have tools and skills to automate a portion of our tasks, but what if we could give a similar power in everyone's hands? Users can now take a picture of their meeting notes/ hand-drawn mock-ups and send it to AutoCode. AutoCode will read the image and extract relevant information from it. It then creates a PowerPoint deck or a web mockup for you and emails it to you.
AutoCode is building a modern productivity suite for workers. All of us would want people to focus on what matters instead of wasting their time on mundane tasks, such as formatting slides, aligning shapes, annotating images, reshaping training data, etc.
How we built it
We used a combination of Computer Vision, RPA and Python language to build the AutoCode solution. The solution can be divided into 3 modules: A2019 RPA code, Computer Vision (Google API) python script, and another python script that generates the PowerPoint/web page. The A2019 code lies at the heart of our solution. It orchestrates the entire process and decides the flow of the process. The computer vision (Google API) python script extracts the text and coordinates of the entities present in the input handwritten image and saves it in a form of structured excel table (xlsx). The PowerPoint creating python script uses this structured output and maps out the entities in a PowerPoint template, thereby, creating a deck.
Challenges we ran into
As a team, we all agree our biggest challenge was to work remotely and stay connected to make sure that we develop this solution efficiently and in time. Our other challenge was to find and use the appropriate technologies to get the desired results. We tried multiple Computer Vision APIs by providers such as Microsoft, AWS, Google, Abbyy, etc. to arrive at a decision of using Google Vision API. Also, creating the logic to convert structured data into PowerPoint and HTML codes was a challenging task. In addition to these challenges, we had many plans for our end product, all of which could not be possible within this time but we would surely want to work on them in the weeks to come.
What we learned
First, of all, we learned, working, and collaborating in this new normal. Probably, it was the first hackathon, that we participated in, remotely. It was difficult at times, but an enriching experience altogether.
Secondly, we learned that the automation use cases are more obvious and evident than what we think them to be. At times, we are just stuck with point use cases that come from our client discussions and ignore the broader use cases that could have a much wider impact on society and business.
Thirdly, RPA, along with other cutting-edge automation and digital transformation technologies, has great potential in improving business efficiency, enhancing employee productivity, and driving innovation across industries.
Last but not the least, this hackathon has enabled us to think more innovatively and focus on the problem at hand; which many times gets difficult with the 'Business as usual' ecosystem we tend to work in.
What's next for AutoCode
Today, AutoCode is an innovative product and we have plans to scale it to become a generally available product for all. Initially, we plan to pilot the solution for a few companies and customize as needed to align with their templates, company logos, client logos, architecture diagrams, process flows. With time, we plan to understand the nuances of how we can scale this product to all the companies and more users, We will make required upgrades to the product and roll it out for the broader market. The product will be equally relevant in the post COVID world, as it is today, even if we assume an unlikely scenario of things to get back to pre-COVID normal.
Built With
a2019
api
automationanywhere
computer-vision
google-vision
imap
json
python
python-pptx
smtp
Try it out
drive.google.com | AutoCode | Revolutionize the workplace...Bringing the power of Computer Vision and A2019 to automatically understand handwritten notes and transform them into structured web pages and client deliverables | ['Abhi Saxena', 'Mohit Poddar', 'VAIBHAV BANSAL', 'Jayesh Muley'] | [] | ['a2019', 'api', 'automationanywhere', 'computer-vision', 'google-vision', 'imap', 'json', 'python', 'python-pptx', 'smtp'] | 10 |
9,989 | https://devpost.com/software/website-build-bot-templates | Website Build Bot Templates contains template forms that allow the automatic creation of websites of various types: blog, event, company, and ecommerce.
Try it out
bitbucket.org | Website Build Bot Templates | Website Build Bot Templates contains template forms that allow the automatic creation of websites of various types: blog, event, company, and ecommerce. | ['Warp Smith'] | [] | [] | 11 |
9,989 | https://devpost.com/software/covid-19-challenge | Inspiration
WhatsApp instructions of use
Start the conversation
Give us feedback
Winners at the COVID-19 Global Hackathon
Inspiration
Across the world, hospitals are collapsed because of thousands of citizens requesting medical services related to the pandemic.
Just in Europe, over 1 073 947 people are directly affected by COVID19
, and we got really inspired by a real story of a Doctor, that writes in an article
"I’m a Doctor in Italy. We Have Never Seen Anything Like This, my country’s health care system may soon collapse. None of us have ever experienced a tragedy like this."
The coronavirus COVID-19 has reached our cities, crossing borders and radically modifying our daily lives. The exceptional nature of the situation means that each and every one of us has to invest efforts that help stop this pandemic, but how can we do it?
So our team start thinking: What if we start promoting telemedicine and digitalising the consults related to symptoms or where to find hospitals, test labs, food or hygiene products. Also helping to fight Fake news and providing motivational content for any person passing through this hard moment.
Telemedicine & consultations online has great advantages: we do not saturate Hospitals with non-urgent visits, we lower the potential infection of doctors and also we reduce the number of displacement and, therefore, the contacts that may cause the spread of the virus.
*
Hospitals are collapsing because of the overwhelming request of medical services related to this pandemic. *
And this are also other problems we are seeing and it inspire us to build this solution:
1) Healthy individuals with lack of knowledge and inaccurate information unnecessarily going to the hospital with the risk of being exposed to the virus.
2) Waiting times prolonged for people that need the immediate attention.
3) Hospitals Exceeding their capacity & resources with non-emergency cases.
What it does
Through a virtual assistant that runs on WhatsApp, we provide non-emergency support, an through Natural Language Processing models we try to understand how the users feels during the day, for example:
User say:
"Bad, I feel very sick"
I think that I'm infected
Please connect me with a Telemedicine Volunteers
Marie resides in a remote town in Sussex in England, and during several weeks she presented pronounced cough and headaches. So, she start getting worried, and decided to consult a doctor, but this time she doesn't move from her home, and she will be treated in Amsterdam, 7,300 kilometers away. How? She turn on the mobile, open her WhatsApp and connect to a video call, detail her symptoms in the conversation, and wait for a doctor to connect to the call.
User say:
"I'm ok, just looking for information"
I live in Santiago de Chile and I want to track Today's news about COVID-19, find Hospitals near me, Test Labs, find Food and Hygiene products or identify a Fake new.
via GIPHY
User say:
"I want to become a Volunteer"
Doctors, Pharmaceutics, Psychologists, among other health workers can become members to our Volunteer Global Telemedicine network.
Become a Hero
How we built it
We use Natural Language Processing models to understand what users are saying and typing... We connect the NLP model to FB Messenger and Whatsapp API to capture Parameters from the conversations and provide the users the best option.
Also, this effort wouldn't be possible with the support of over 100 Developers and Citizens that help us on task's such as Testing, conversational design, communication among others. Their names are: Daniel Rojas Roa (VR/AR Developer), Andrey (Health Coach), Joshua Pedraza (AI Developer) & many other testers of the platforms across countries like: Canada, United States, México, Guatemala, Brasil, Chile, Costa Rica, Colombia, Spain and others.
Challenges we ran into
-Terms of Use of Messenger & Whatsapp for Business API for Emergencies Services.
-Train the model in different areas such as: Feeling Bad or Sick, Feeling ok and looking for news, places or products, and Becoming a Volunteer.
Accomplishments that we're proud of
Whatsapp Virtual Agent: (Testing Instructions):
1- Add the phone number as a contact:
+1 415 523 8886
2- Write the command:
*
Join *
3- Start the conversation: "Hi", "Heeelp", "Let's start" or any other
Open Github Repo to our solution
Terms of Use
What we learned
Contribution with multiple countries to address this pandemic can help us have a better context of the challenges that we share and which one are really different, make a match between them and scale a powerful solution against human main challenges, such as COVID19.
Telemedicine is an effective first filter and allows Medical & Health center's to allocate available resources to those critical cases who really need them. In addition, using remote control terminals, it facilitates the monitoring of chronically ill patients, to whom treatment is provided at home whenever possible.
What's next for Bacty Bot
Build cheap Telemedicine equipment
Empower Doctors across the world
//Disclaimer: Opinions are our own, not of any company, program or their products. Each Developer Expert is fully responsible of their services, and is not affiliated with other Company nor do they offer services on behalf of a Tech Company. Customers are fully responsible for their use of services, if any. This code is a sample, should not be used for any potential production workloads.//
Built With
facebook-messenger
machine-learning
natural-language-processing
whatsapp-api
Try it out
youtu.be
youtu.be
github.com
youtu.be | Bacty Bot | We connect Health Professionals and accurate information with possible COVID19 victims in Europe through WA & Web | ['Camilo Andres Montañez Aldana', 'Leandro Camacho', 'Jorge Grimaldo', 'Piero Divasto', 'Lissa Ng'] | ['Highlighted Project'] | ['facebook-messenger', 'machine-learning', 'natural-language-processing', 'whatsapp-api'] | 12 |
9,989 | https://devpost.com/software/covid-19-informer | Menu
Daily Graph
Language support
Understand User Queries
ML based daily Prediction
Location based response
Latest News
Deaths and Infected Updates
Recovery Update
Inspiration
With the spread of fake news about Covid-19, with thought why can't we use the same resource to spread proper authentic news for public awareness
What it does
Its a
WhatsApp Chatbot
which having key features as follows:
Designed to send you realtime statistics updated every 1 hour, you can also send Hi to get current data from the bot anytime !!!
District wise data for each State
State wise data for India
Country wise data
Some short headlines for the day
Predictions for next day using ML with past each-day statistics
Language support: Hindi is also available
You can even send your location to how far you are from nearest COVID-19 infected patient
Apart from the queries you ask the bot which is guided by menues, the bot can understand phrases to some extent.
Graph of last 15 days cases every day sharp at morning 9:00 AM
How we built it
We build the server using nodeJs which uses services of Chat-Api to interact with the Whatsapp server. Moreover we have used crontabs to schedule regular updates for our database and to inform users if there are any new cases.
Challenges we ran into
Understanding the user queries feature was started with a bit of hard coding but with due course of time we implemented it properly with NLP( Natural Language Processing).
Accomplishments that we're proud of
We already have 350+ users onboard who are regularly getting informed by our chatbot.
What we learned
We learned many things like serverside scheduling, standalone JavaScript codes for updates, etc. But more over all these we learned how it feels when we do something for the society.
What's next for Covid-19 Informer
With this Covid-19 Epidemic, We've learned this type of situation become infestation only due to lack of potential and transparent communication between the government and citizens of the country. In this world of technology, almost everyone of us have smart phone in our pockets, but most of us are far away from the genuine information, helpful services from the Internet. On the other hand, everyone has WhatsApp messenger installed and working. We have come up with an idea to deliver the information and these services to their whatsapp. Our solution includes a fully automated chat-bot and using some native services like locations, camera etc and we think that this can used for a hell lot more purposes.
Built With
chat-api
crontab
natural-language-processing
node.js
yandex
Try it out
pcms19.000webhostapp.com
github.com | Covid-19 Informer | With this Covid-19 Epidemic, We've learned this type of situation become infestation only due to lack of potential and transparent communication between the government and citizens of the country. | ['Shubham Kumar', 'DEBANJAN DAS MAHAPATRA', 'avnish awi'] | [] | ['chat-api', 'crontab', 'natural-language-processing', 'node.js', 'yandex'] | 13 |
9,989 | https://devpost.com/software/linkedin-jobs-finder | Inspiration
Helps students find jobs on LinkedIn during Covid-19
What it does
Automates the job finding process
How I built it
Built using the bot service in automation anywhere's Control Room
Challenges I ran into
It was my first dabble into RPA. I was new to some things but I didn't face many difficult challenges
Accomplishments that I'm proud of
It works!
What I learned
Robotic Process Automation
What's next for LinkedIn Jobs Finder
Add more features
Built With
automation-anywhere-bot | LinkedIn Jobs Finder | Automates the job finding process for students during COVID-19 | ['Glory Adedayo'] | [] | ['automation-anywhere-bot'] | 14 |
9,989 | https://devpost.com/software/onboarding-automation | On-Boarding Form
As per our policy in AstraZeneca, we have obtained permission from Botathon managers to showcase our bot internally with AA
Inspiration
Due to this lockdown owing to Covid-19, many organisations will face challenges in on-boarding new joiners to their company. New joiners would find it difficult to print, scan documents due to the closure of all shops. Hence we decided to make this transition smooth by making it digital
What it does
This Bot will generate a background verification form and send it to each new joinee and help in collating the information to the HR team. Based on HR's response, welcome mail will be triggered to each individuals.
How I built it
We used Google Forms to create a background verification which includes all the personal, educational, previous employment if any and reference details. Using AA 11.3 and VBA we automated the process.
Challenges I ran into
Time constraint and working remotely with team members
Accomplishments that I'm proud of
Being a part of a project which makes a positive difference in this Covid-19 situation
What I learned
It is possible to work together as a team even in remote workspace
What's next for Onboarding Automation
We are hoping that this Bot will make a significant difference in On-boarding process for all the organisations and further try to improve the capability of the process
Built With
aa11.3
googleforms
vba | Onboarding Automation | This Bot will help in smooth transition of new joiners to the organisation by helping the HR team in collating the Background verification. | ['Daniel Henry Paul Robin', 'Priyanga Rajaram'] | [] | ['aa11.3', 'googleforms', 'vba'] | 15 |
9,989 | https://devpost.com/software/fraud-detection-bot | Architectural Diagram
Theme- Insurance Industry
Problem Statement:
Workers' compensation claim fraud contributes significantly to the $40 billion insurance frauds per annum. A significant impact of COVID-19 has been the ‘Work from home’ culture. This presents new challenges to insurance companies as validation of claims from employees working at home is quite a challenging task.
Inspiration:
The inspiration behind this solution was to make our contribution to the community during and post-COVID. Automation Anywhere's IPA technology has enabled us to employ the most sophisticated digital technologies to solve problems. Additionally, our team has representation from Europe, the Middle East, and Asia and this allowed us to bring our different perspectives and skills on the table.
Solution:
Our solution, the Fraud Detection Bot is an intelligent process automation solution that leverages machine learning blocks such as natural language processing and computer vision to detect fraudulent claims. The solution is advanced in capabilities to extract information from unstructured documents and communicate with third-party sources for verification purposes. Based on the extracted information, the bot calculates a Fraud Score and generates the next action steps for claims adjusters. Claim adjusters can use the 'human-in-the-loop' feature of the solution to interact with the bot by viewing high-level insights and claims-specific information.
The bot has been designed with digital building blocks and uses APIs and python scripting. The Automation Anywhere IPA technology orchestrates the whole process allowing for end-to-end automation. The modularity in the design of the solution allows for quick and easy upgrades to the solution based on the insurance company preferences.
Challenges:
The biggest challenge in implementation was an initial lack of understanding about the insurance domain, however, after reaching out to some connections in the insurance industry, we were on track with a better idea about the problem.
Impact:
The impact of Fraud Detection Bot is not just limited to the current situation. Post COVID-19, we see that a lot of employees will continue to work from home and the Fraud Detection Bot will play an instrumental role in detecting fraudulent claims. The Fraud Detection Bot empowers insurance claims adjuster teams to identify fraudulent claims in an intelligent manner.
Leverages AI tech stack
Comprehends unstructured information
Generates Fraud score and next action steps
Facilitates bot-human interaction
Results in faster and error-free processing
Built With
amazon-web-services
azure
ipa
kpi-dashboard
natural-language-processing
python
textract
vision
Try it out
github.com | Fraud Detection Bot | This is the Fraud Detection Bot, a native-AI driven solution that detects fraudulent workers' compensation claims and enhances the capabilities of insurance adjustors. | ['Vikram Bhatia', 'Harshad Manglani', 'Lokesh Bhatia'] | [] | ['amazon-web-services', 'azure', 'ipa', 'kpi-dashboard', 'natural-language-processing', 'python', 'textract', 'vision'] | 16 |
9,989 | https://devpost.com/software/student-evaluation | Flow Chart 1
Flow Chart 2
Flow Chart 3
Average marks of Class in Different Subjects
Inspiration :: During Covid-19 crisis, maximum numbers of persons are doing Work from home, also children are doing Schooling from home. Maximum schools send students classes videos, assignments through whats up/ youtube or any other digital platform. But they are not able to manage each student profile. Maximum schools are updating Student profile, curricular, Leave Request on paper and some are updating in excel sheet manually. Hence we can provide support such schools to track student Academics.
What it does :: Software can read the Student data through excel file or database and then calculate attendance percentage for each student. If attendance is less than 80% for a month drop a mail and send SMS to Parents for less attendance.
Software can read the marks for each student and send the subject wise result to parents over email and SMS.
Software can check if fees is pending for any student and send reminder mail and SMS to parents to submit fees and maintain Reminder count.
How I built it :: Used AA2019 & Python
Challenges I ran into :: I was not sure how to send SMS online and how different graphs can be plotted using Python libraries.
Accomplishments that I'm proud of :: We can help number of government or other private schools which are not able to afford School Administrative Software and can help them to maintain academic tracker for student.
What I learned :: I learned about AA2019 and number of new things in Python.
What's next :: Whatever we do for one school, can be used for other schools also. We can also plan some Inter school tournaments and use this data to select best student among schools.
Built With
excel
folium
mail
matplotlib
pandas
python
Try it out
aa-botathon-us.my.automationanywhere.digital | Academic Tracker | Due to Covid-19 crisis, Schools are closed and they are taking classes online. Maximum schools does not have software to track student academics. We will help these schools to track student academics. | ['Vikrant Sehgal'] | [] | ['excel', 'folium', 'mail', 'matplotlib', 'pandas', 'python'] | 17 |
9,989 | https://devpost.com/software/productivitech | Statistics
Statistics
How ProductiviTech Works
Our Features
About Us
User Profile
Productivity Report
Attendee Breakdown
Recomendations
Inspiration
Due to the Covid-19 pandemic, each of our team members had to work or study remotely. Some of us were in the United States while others were in Nepal but we all experienced the same transition to online medium.
Faced with this new work environment, we realized that online meetings are quite difficult to oversee, especially when there is a large number of attendees. Meeting hosts cannot easily keep track of attendance throughout the entire meeting and it is a real challenge to keep track of which meeting attendees are paying attention. Some of the scenarios that we personally experienced were the following:
Professors could not easily keep track of the students who were paying attention to lectures and could not easily take attendance if the class was large.
Managers who held online meetings could not easily keep track of which employees were actively paying attention to specific segments of a presentation.
Based on our observations, we decided to create a tool that would allow the user to quickly analyze a recorded meeting and evaluate its productivity level based on the attentiveness of the attendees.
Our goal is to help meeting hosts capture the attention of their audience by learning from their past experience reflected in a "productivity dashboard".
What it does
Takes a meeting video recording as an input
Processes the video frame by frame and detects the faces and the eyes of the attendees
Saves the number of attendees.
For each individual attendee, frames are classified as "attentive" or "not attentive" based on the following parameters:
- Attendee face present/not present in the frame
- Attendee eyes present/not present in the frame
- Distance of detected face from the camera (chose a threshold)
After all the video is processed, the software calculates what percentage of the time that each individual attendee was attentive
Finally, the metrics are displayed in a dashboard with 3 tabs:
- Overall meeting productivity
- Individual attendee attentiveness
- Evaluation of the host based on attendee attentiveness together with personalized recommendations on how to improve meetings
How we built it
As our goal was to help meeting hosts capture the attention of their audience, we started by detecting the face and eyes of the person in the frame. We implemented this feature by using OpenCv library and HaarCascades algorithm. Once the faces and eyes were detected, we started to track the depth (the distance between the webcam and the attendee). Using the face, eye, and depth we calculated whether the student is attentive or not.
Using all the obtained data, we were able to calculate the attention and the engagement of the individual student. We were able to extract the name of the student from the frame by using Tesseract (optical character recognition engine). At last, all the results were provided to the host, using Plotly graphics.
For the front end, we used HTML, CSS (Bootstrap) and JavaScript. We also created graphics using tools like Adobe Photoshop and Illustrator. We first did research on what problems we are currently facing. We then created graphics of the problems faced, how we can solve it through our project and the main features of our project. In the development phase, we tried to keep it simple yet informative. We created an interface where you can view the important information at a glance. The user experience was also taken under consideration and an easy to use application was built.
Challenges we ran into
There are many popular video meeting platforms and each provider's application has a slightly different format (Google hangout meetings display the attendee names while Zoom meetings do not etc.). It was very difficult to implement a processing technique that would adapt to any video recording of a meeting, whether it is Zoom, Skype, Webex, Google Hangouts etc. We are still working on making our software more robust.
Splitting the frames of each individual attendee
Extracting the name from the video recording (text recognition in an image)
There is a very large number of corner cases in a video meeting:
- Camera off
- Multiple people in the same user frame
- Bad lighting
- Confusing background
- Poor connection leading to blurry images
- Too many attendees so their video stream is displayed on different screens
Accomplishments that we're proud of
We identified a challenge created by the new circumstances that the pandemic forced us into and we implemented a working solution
We built a visually pleasing and easy to interact front-end
We solved a few difficult challenges in the back-end (for example, identifying names in the frame)
We collaborated harmoniously and made use of each of our top skills. Our team had people in the United States and in Nepal and despite the 9 hours and 45 minute timezone difference, we had very productive meetings
We strongly believe that our presentation video is top notch
We are very proud of the brand name we chose. In the future, we would like to build a suite of productivity tools under this brand name
What we learned
Most of us did not have any previous experience with automation bots. It was great to learn how to use the Automation Anywhere functionality and it was very rewarding to see our process streamlined
What's next for ProductiviTech
Track the engagement of each attendee by identifying the instances when they speak in the meeting.
Add enhancements to the gaze tracker. We currently detect faces and eyes but we would like to analyze the direction of the gaze and correlate with what is happening on their screen.
Build more products that will be part of the "ProductiviTech productivity enhancing tools"
Built With
adobe-illustrator
bootstrap
css3
filmora9
flask
heroku
html5
javascript
opencv
pandas
photoshop
plotly
pytesseract
python
sqlite
Try it out
github.com | ProductiviTech | ProductiviTech is a software that analyzes recorded meetings frame by frame, gathers metrics such as attentiveness, and displays them in a personalized dashboard. Record. Review. Ramp up productivity. | ['Dilasha Shrestha', 'Teodor Nicola', 'Saras Karanjit', 'Saurav Bhandari'] | [] | ['adobe-illustrator', 'bootstrap', 'css3', 'filmora9', 'flask', 'heroku', 'html5', 'javascript', 'opencv', 'pandas', 'photoshop', 'plotly', 'pytesseract', 'python', 'sqlite'] | 18 |
9,989 | https://devpost.com/software/trending-bot | Provide NEWS from different Sites.
Our bot provides Trending NEWS of a country with its NEWS Title and its link from different and popular NEWS sites and provides a maximum of 20 results. For this bot, we have used API's from
www.newsapi.org
Most of the cases, people waste their time by looking up for NEWS and this bot is their solution.
Built With
api
rpa
ui | Trending bot | This bot provides Trending NEWS of a Country with NEWS Title and its link from different NEWS sites. | ['www.newsapi.org', 'AAKASH KAUSHIK'] | [] | ['api', 'rpa', 'ui'] | 19 |
9,989 | https://devpost.com/software/health-scout | Team lead views Employees health information through Bot Insights
Automation Workflow
Bot downloads the Form responses
Bot logs into Google Form
Employee submits Google Form
Non respondents list generation
Employee receives message from health scout bot
WhatsApp message to employees
Bot input file preperation
Inspiration
Employee Wellness, Ease of Use and Improving effectiveness
What it does
Collection of health information from team members, reminding team members and send a consolidated information to team lead
• The bot reaches to all the team members through WhatsApp to update their Health status, at the beginning of the shift
• Track their responses in a Google form
• Send 3 follow on remainders only to defaulters over the course of four hours to have each team member fill the form
• An email is sent out to the Team Lead/Manager on health status of entire team with Bot Insight link to visualize the information
How we built it
After designing the solution along with technical specifications, we have followed 'divide and conquer' approach and succeeded.
We have modular designed solution; we have developed each module independently and then integrated it to an end to end solution.
Challenges we ran into
Initially we were in a search to find easiest mode of communication to get better coverage for employees, in our experience emails were not an effective medium. We shortlisted on Web-WhatsApp and Google Forms as effective medium for updating, collation and reporting
There were few limitations in Google Forms which we had to work around.
Accomplishments that we're proud of
Major accomplishment we all can say that as a team "This Botathan event helped us to be a pioneer on A2019 journey within a short span of time"
What we learned
It’s not just building the Bot is our learning, we learnt about Usability, Ease of use, integrating multiple solutions to build a effective solution. Health Scout Bot development and A2019 Botathon experience by itself is a great learning.
Exploring towards new features of A2019, Bot Insights, WhatsApp API through Twilio, Google App Scripts for Forms are our learning.
What's next for Health Scout
As an organization we plan to re-use & leverage the bot for the many activities like,
sharing important organization level notification with employees
sending organization level survey responses/training feedback
automating reminders to be sent for any process
collecting information through customized google forms, tracking and reporting the response
Built With
botinsights
googleforms
macro
webwhatsapp
Try it out
drive.google.com | Health Scout | Automate collection of health information from employees through WhatsApp & Google Forms | ['Bharath Kumar B', 'Suganya Ramasamy', 'SARAVANAN M.R.', 'Venkata Sairam'] | [] | ['botinsights', 'googleforms', 'macro', 'webwhatsapp'] | 20 |
9,989 | https://devpost.com/software/providing-legit-job-postings-0i6soj | Team
Aerica Singla, Arushi Madan and Arun Venu
Inspiration
COVID-19 pandemic is affecting economies in every continent. Unemployment rates are spiking every single day with the United States reporting around 26 million people applying for unemployment benefits, which is the highest recorded in its long history, millions have been furloughed in the United Kingdom, and thousands have been laid off around the world. These desperate times provides a perfect opportunity for online scammers to take advantage of the desperation and vulnerability of thousands and millions of people looking out for jobs. We see a steep rise in these fake job postings during COVID-19. In the grand scheme of things, what may start off as a harmless fake job advert, has the potential of ending in human trafficking. We are trying to tackle this issue at the grassroot level.
What it does
We have designed a machine learning model that helps distinguish fake job adverts from genuine ones. We have trained six models and have drawn a comparison among them. To portray how our ML model can be integrated into any job portal, we have designed a mobile application that shows the integration and can be viewed from the eyes of a job seeker. Our mobile application has four features in particular: 1) Portfolio page: This page is the first page of the app post-login, which allows a job seeker to enter their employment history, much like any other job portal/app. 2) Forum: A discussion forum allowing job seekers from all around the world to share and gain advice 3) Job Finding: The main page of the app which allows job seekers to view postings that have been run through our Machine learning algorithm and have been marked as real adverts. 4) Chat feature: This feature allows job seekers to communicate with employers directly and discuss job postings and applications.
How I built it
We explored the data and provided insights into which industries are more affected and what are the critical red flags which can give away these fake postings. Then we applied machine learning models to predict how we can detect these counterfeit postings. In further detail: Data collection: We used an open-source dataset that contained 17,880 job post details with 900 fraudulent ones. Data visualisation: We visualised the data to understand if there were any key differences between real and fake job postings, such as if the number of words in fraud job postings was any lesser than real ones. Data split: We then split the data into training and test sets. Model Training: We trained various models such as Logistic regression, KNN, Random Forest etc. to see which model worked best for our data. Model Evaluation: Using various classification parameters, we evaluated how well our models performed. For example, our Random Forest model had a roc_auc score of 0.76. We also evaluated how each model did in comparison to the others.
Further on, we designed an app titled JOB, using Adobe XD. We also integrated a Twilio framework so as to add a system to notify job posters whose job postings may have been flagged. This is because, since our ML algorithm is not a 100% accurate, we would have cases of 'False Positives' wherein a true job posting would be marked as fake. In these times we would want to allow the job posters to challenge the decision by providing evidence.
Immediate impact
Especially during but also after COVID-19, our application would aim to relieve vulnerable job seekers from the fear of fake job adverts. By doing so, we would be re-focusing the time spent by job seekers onto job postings that are real, and hence, increase their chances of getting a job. An immediate consequence of this would be decreasing traffic onto fake job adverts which would hopefully, discourage scammers from posting fake job adverts too. Police departments don’t have the resources to investigate these incidents, and it has to be a multi-million-dollar swindle before federal authorities get involved, so the scammers just keep getting away with it. Hence our solution saves millions of dollars and hours of investigation, whilst protecting the workers from getting scammed into fake jobs and misused information.
What's next for Providing legit job postings
We wish to completely automate the notification system built using 'Twilio'.
Submission info
We have submitted this project to RookieHacks and Oxford Digithon after confirming that cross-hackathon submissions are allowed for the hackathons held over the same weekend.
DOMAIN.COM - Oxford Digithon MLH Challenge
kidsusepickuplinesiusepullrequests.space
Built With
javascript
python
tensorflow
twilio
Try it out
kidsusepickuplinesiusepullrequests.space
github.com | Providing legit job postings | Filtering out fake job adverts from existing job portals | ['Arun Venugopal', 'Arushi Madan', 'Aerica Singla'] | ['Best Isolation Hack'] | ['javascript', 'python', 'tensorflow', 'twilio'] | 21 |
9,989 | https://devpost.com/software/lab-assay-bot | Lab Assay Bot is a suite of bots that automates the data collection process of laboratory equipment and integrates with a Laboratory Information Management System (LIMS).
Lab Assay Bot automatically captures raw experimental data [measurements, equipment settings, calibration readings] from a variety of lab devices [microscopes, oscilloscopes, scanning electron microscopes, spectrometers]; assembles relevant data sets and visualizations that are stored securely; and generates descriptive reports containing Jupyter notebooks and ML model predictions.
Each bot is tailored to a specific lab device and corresponding LIMS.
Try it out
bitbucket.org | Lab Assay Bot | Lab Assay Bot is a suite of bots that automates the data collection process of laboratory equipment and integrates with a Laboratory Information Management System (LIMS). | ['Warp Smith'] | [] | [] | 22 |
9,989 | https://devpost.com/software/safemenu | Logo with QR code to our chat bot.
Inspiration
Problems that many of enterprenues facing, including my mother
What it does
Creates safe menu for visitors
How I built it
With help of my team
Challenges I ran into
Stong client focus. reaching the clients
Accomplishments that I'm proud of
That we are able to grow fast
What I learned
Team means a lot
What's next for SafeMenu
Growth. product development new functions. new solutions.
Built With
facebook
java-(spring)
javascript
messenger
mysql
Try it out
m.me | SafeMenu | The problem we’re trying to solve is a high risk of getting infected while you are visiting restraunt, because limitations slowly getting dawn, when the virus is still out there. | ['naz-priymak', 'Oleksii Pryhrodskyi'] | [] | ['facebook', 'java-(spring)', 'javascript', 'messenger', 'mysql'] | 23 |
9,989 | https://devpost.com/software/machbarschaft-25fcwg | Vision
Machbarschaft connects millions without internet access with their neighbours who are willing to provide help for basic supplies in order to keep vulnerable groups safe.
In this crisis, Machbarschaft allows to bridge human to human contact through a hybrid solution linking both analogue and smart digital technology. Our vision is to build a stronger community and a more equitable society where no one is left behind!
Inspiration
Every 9th household in the EU does not have any internet access. This makes it difficult for especially vulnerable people to request help. We are experiencing a huge movement of solidarity, especially in communities and neighborhoods. However, these volunteers are often are organized on digital platforms. Tens of millions are not able to access these platforms in the EU, leaving them in a drastic care gap.
Our mission is to close this gap through Machbarschaft. This solution enables vulnerable people to use their well-known devices to connect with their neighborhood. Especially in times of crises, strengthening neighborhood ties helps to build a more equitable and inclusive future. This way society can ensure everybody safe access to support.
Machbarschaft - how does it work?
We offer a smart bridge combining three key elements: the analog telephone, a phone bot powered by AI and an app. Our app and hotline represent the link between the digital-native generation and people in need of help and are not familiar with the use of the internet. With Machbarschaft, people in need can make a simple phone call and provide information about the category of their request and a few additional logistical information. The service hotline is run by an AI powered bot. The information will then be processed and finally displayed in our app which helpers download in advance. Registered and verified helpers receive push-notifications and they can look up requests near their current location on a map in the app. As soon as they select a request, they can contact the care recipient by phone to arrange further details. After, the helper sets off, and fulfils the request. In case of the much needed grocery shopping request, the helper brings the agreed items to the care recipient and receives the money for the groceries in exchange. In order to ensure appropriate protection against infection, the money is packed in an envelope and handed over at an appropriate distance and without any body contact. This way, we hope to make the ongoing crisis a little less threatening, especially for vulnerable groups and those in need of help.
The solutions impact to this crisis
Machbarschaft addresses the group that has been left behind so far: The vulnerable people without a wide social network and without internet access. Further, we offer our system to e.g. already existing societies that currently help in the segment of neighborhood aid, but perform their processes manually. We hope to enhance efficiency of their process through digitalizing the process.
Since every 9th household in the EU is possibly compromised in this crisis and beyond the crisis, there is a huge demand to cover. In addition, the gap between poor and rich is continuously growing leading to deteriorating situations. Therefore, scalability is key to Machbarschaft.
How did Machbarschaft improve during the Botathon?
Although our product is already in an advanced state, it is under constant development. Our main goal for the Botathon was to finish our Apps in order to start a first testing phase utilizing the whole "technology pipeline". We also tried to focus on our Bot Technology Part. With our Telephone Bot, it is possible to convert the resources of a central call center to a decentralized helper network with a direct connection to regional helpers. This provides protection against contagion, especially during corona, and also makes it easier to organize the process afterwards. Furthermore, we have tried to find approaches how we can overcome language barriers, which arise in particular from dialects of elderly people, by means of skillful helpers using artificial intelligence. A further important point for us is that humans remain humans and a psychosocial interaction is given despite the automation with the bot. Through the bot, a large network of helpers can be created, which gives people a sense of belonging and enables direct social contacts. We have also set our focus on digitalizing analog tasks.
What is needed and what are the next steps?
The immediate next step is to run further simulations and tests. In order to optimize our concepts and technology, we have already established various partnerships with civil societies as well as local authorities in Germany to run early testings with authentic target groups. This is why we already planned to our first pilot project in the city of Passau, Germany, we are already partnering with. After this proof of concept testing, we need more expertise in the areas of business strategy and product ownership, as the next steps will be constant optimization of our product while scaling up nationally. To prepare for scaling up, we already worked out a combined B2C and B2B concept. We will have to intensely expand our already large network in preparation for expansion. Further, our business plan has to be implemented in order to finance this non-profit project. Therefore, further partnerships and cooperations have to be established. At the same time, we plan to continue our already exisiting cooperations with similar non-profit projects with a similar solution. The reason is, that as a non-profit it is not easy to find ressources. Therefore, we aim to combine existing ressources and powers to really be able to implement our solution quickly and help people as soon as possible. Thus, we aim to quickly expand our easy scalable solution nationally, EU-wide and globally in order to support millions as soon as possible.
The value of Machbarschaft after the crisis
Machbarschaft has high sustainability goals. We aim to connect people beyond the current crisis. Why? Because, there are millions who struggle with everyday errands, and they still will also after the COVID-19. Machbarschaft hopes to contribute a small piece to solve this problem in the long-term perspective. We offers a smart platform to meet the age-old basic need of human to human connection - to be there for those who need it most. This is why we are not limited to the time of the current crisis. We aim to accompany those connections built through as well as fostering new connections to be built. As soon as there is no immediate infection risk, we are already planning on expanding our currently offered services far beyond of pharmacy and grocery shopping. Our vision is to build a stronger community and a more equitable society where no one is left behind!
Try it out!
Try out our hotline bot (24/7)! Our phone numbers for various countries:
+358 75 3250960 (Finland)
+44 131 510 5863 (United Kingdom)
+46 10 551 53 69 (Sweden)
+49 40 299960980 (Germany)
+420 910 902 652 (Czech Republic)
+1 779 201 6897 (USA)
Our apps and hotline are still under active development – please excuse any errors or bugs at this point and feel free to report it on our GitHub repository. You can download a first version of our Android app
here
. Also, take a look on the videos of our current Apps on iOS
here
and on Android
here
!
How we built it
Hotline
In order to be able to process calls from as many people as possible at the same time without having to resort to a conventional call center (also regarding the COVID-19 infection risk of call center employees), we developed an automatic service with Twilio. In this service, we modelled an easily understandable call flow in which all necessary data for a request for help is collected. In order to scare older people by using robotic voices, we recorded the questions ourselves (German only). We are also currently trying new solutions with voximplant to directly coordinate the caller with a helper with our bot system and in case there is no helper currently available the bot will create the help seek in the app directly.
Backend
The collected transcribed data from the phone call is then sent to a Firebase function (Javascript/NodeJS) via POST request which tries to generate longitude and latitude from the spoken address via Google Maps API. This data is then stored in a Firestore database along with the name and request, making it visible and sending push notification to nearby volunteers based on the geolocation. Another Firebase function triggers a callback to the help seeker via Twilio after 24 hours if no volunteer could be found or if an order has been marked as completed.
App
To ensure the best possible user experience, we program the app natively for iOS (Swift & UIkit for the frontend) and Android (Java). These apps communicate with the central database of Firebase, Cloud Firestore (NoSQL). For this we used the available SDK for Android and iOS from Google. Function and design of both apps are based on the created wireframe. After the users have verified themselves via an identification procedure. This is, for now, an optional step for us and may depend on the country and their legal requirements for the registration of phone numbers to be able to assist local authorities in case of fraud. After that, the user have to create their account via SMS confirmation. The user is informed about the process in the app and the procedure for dealing with requests for help. After the successful login, the user will see help requests in his or her area. These are visualized on a map (using the Google Maps API) and in a list. In advance, the user only sees the most necessary information in order to offer him a small decision support. As soon as he decides to accept a request for help, he has to confirm this and will receive further information. The user can contact the person seeking help again and exchange information about the details. Now the helper can go and take care of the request. As soon as he has completed the assignment, he can confirm this in our app. If an order has not been accepted after 24 hours, the person will be informed about the situation by a callback and it will be up to him/her to decide whether to continue the order or to withdraw it.
Website
Our simple website serves as a central information platform for interested volunteers. The purely static website machbarschaft.jetzt is based on a bootstrap theme, which was implemented using HTML5 and CSS3 (SCSS) technologies. A CMS has not been implemented yet. Since the website can be called up in any situation, we attached great importance to a responsive layout. The website serves not only to recruit new volunteers for our native apps but also to promote our entire concept to future supporters. Since our target group of people seeking help is mainly informed via analogue channels, supporters can download an attractive Machbarschaft flyer which can be hung up in the neighbourhood or distributed in mailboxes. With this, both target groups can be addressed in parallel – volunteers and people seeking help.
Current state
Our hotline and backend are fully functional and secure. Data from orders completed with our hotline are saved in our Firestore database and are available in our apps. The apps are working as well, they are fully connected to our database and can communicate to it. We are doing bug testings and are preparing our next phase to test the app with more users in a closed beta. The hotline is being tested by our team and we are preparing to test it with old people as soon as possible. In the future, we are going to improve the underlying technology to be even more AI-driven and making the hotline more flexible and adaptable to our users.
Who are we?
We are a diverse team of more than 30 people from all over Germany with a unique and unstoppable team spirit! We were brought together by the mission to provide safe and fast access to neighbourhood assistance for elderly people without internet access during the Corona pandemic. We are convinced: Together everything is possible!
University students and high school students
Software Developers
Designers (Marketing, Product and UX)
Doctors
Experts in Legal, Process management, Project management, Human Ressources, Design Thinking, Business Development, Data Specialists, Psychology, Marketing, Press, Public Relations
Business plan
Vision
The supply of all people in need is secured.
Mission
We connect needy people of the risk group without internet competence with digital-
affine helpers from the neighbourhood in order to guarantee the supply of the needy.
Strategic goals are long-term goals that make it tangible whether we are fulfilling our mission.
Offer help
to those who are vulnerable towards Covid-19 disease and who at the same time have no access to the internet and online solutions.
Connect neighbors
and bring them together across generations.
Qualify
the future
workforce
of Europe with regards to AI and digital technology.
Offer a sustainable solution, that will be used also after the Covid-19 pandemic.
Build the solution in a way it can be
transferred
to other use cases by NGOs.
Goal 1: Offer Help
Number of successful matches (in a period)
Proportion of successful matches =
Number of successful matches / Number of requests for help
Number of verified helpers on the apps
Goal 2: Connect Neighbours over Generations
Proximity of residence
Goal 3: Qualification
Number of technical team members working on our solution (per year)
Goal 4: Sustainability of the Solution
Number of use cases for which Machbarschaft offers its services
Goal 5: Transferability of the Solution
Publication as open source for other non-profit organizations
Number of institutions / associations that use parts of our
technical solution
KPIs (different target numbers of KPIs depending on local, national, EU-wide or global setting)
No. of help requests, no. of downloads (android vs. iOS), no. of verified app users, no. of successful matches, proportion of successful matches, no. of recurrent requests from the same care seeker, no. recurrent request completion by the same app user and helper
Go to Market Strategy
Machbarschaft uses a combination of B2B and B2C approach. B2B is particularly important to reach the final target groups with the aid of already existing and care providing community services, civil society organizations, NGO´s etc.
B2C
care recipient main characteristic: does not use internet
different segments (elderly, poor, internet illiterate, language barrier…)
Channels: social welfare offices, community services, doctors offices, hospitals, pharmacies, nursing care, outpatient physiotherapists,. churches, communities, bakeries, supermarkets, TV, radio, local newspaper, magazines, kids, grandkids, family, friends...
volunteers main characteristic: wants to support vulnerable group and frequently uses internet
different segments (between-14-55 yo., pupils to professionals, family or stand-alone…)
Channels: mainly internet based, social media, TV, radio, newspapers, family, friends...
B2B and Strategic Partners
non-profit: NGOs, citizens society groups/ initiatives that already established contact with care recipients and/ or helpers
industrial partners: telephone services, digital companies, marketing companies, companies specialized in elderly services
public authorities: local, regional, national, EU, global
Customer Journey & Personas
There are three main personas and customer journeys to be considered: care recipient, helper and civil societies that use us as support for digitalization of their service.
On Boarding Concept
Tools:
care recipients: explanation on flyers, TV etc. and re-explanation on our hotline
helpers: explanation on Social Media/ flyers and introduction within the app
Retention measured through no. of recurrent requests from the same care seeker, no. recurrent request completion by the same app user and helper
Successes
Probably the greatest achievement was to digitally bring together about 30 strangers from all over Europe with different experiences and levels of knowledge, to implement a great idea together and to develop a runnable app that carries the core goal of the idea within itself. Despite the circumstances that a personal meeting was not possible at any time, the communication ran smoothly. The team members were reliable, punctual and it was no problem that the communication was purely digital. Thanks to some tools provided by the organization, data exchange, various uploads and even communication within the team was no problem. Thanks to high quality input throughout the EUvsVirus Hackathon we were able to very quckly improve and optimize our solution, we were able to achieve a goal-oriented implementation. Thanks to this, we have done a considerable amount of work and can deliver a presentable result.
What we've learned
We have learned that extraordinary situations require extraordinary actions and that with the right will and motivation you can achieve incredible things! We have also learned to get out of our comfort zone. It was necessary to get into direct and fast close contact with complete strangers. We then received excellent advices and support. Even if we came to our limits in terms of our abilities and energy from time to time, we were able to motivate each other because, for all of us at Machbarschaft, our work is for "the greater good" of helping people.
More detailed info can be found in our pdf:
Machbarschaft Details Flyer
Facebook
,
Instagram
,
Twitter
,
YouTube
,
GitHub
and
LinkedIn
How did we work
Ticketing tool:
Trello
Communication: Slack
Repository:
GitHub
Website: HTML, CSS, Bootstrap
machbarschaft.jetzt/en
Built With
css3
firebase
firestore
html5
java
javascript
kotlin
swift
twilio
Try it out
github.com
machbarschaft.jetzt | Machbarschaft | hybrid analog and digital solution with a bot connecting millions without internet access with support. | ['Kilian Schneider'] | [] | ['css3', 'firebase', 'firestore', 'html5', 'java', 'javascript', 'kotlin', 'swift', 'twilio'] | 24 |
9,989 | https://devpost.com/software/covid-19-update-bot | Email Sample
considering the current situation and wave of rumors on COVID-19, I have created a free bot to trigger an email with the current count on COVID-19 cases across different states in India
Current status will be fetched from Govt of India Ministry of Health website and displayed in a table format for clear understanding. Also bot will send you an pdf attachment containing Protective measures suggested by the Government
Built With
robotic-process-automation
Try it out
botstore.automationanywhere.com | COVID-19 Update Bot | Free RPA bot to trigger an email with the current count on COVID-19 cases across different states in India (Data fetched from Indian Ministry of Health) | ['Narasimhan Narayanan'] | [] | ['robotic-process-automation'] | 25 |
9,989 | https://devpost.com/software/cryptovote | Log in Page
OCR Verification
DEMO FOR OCR READER (Since it got corrupted in our video):
https://imgur.com/xcbU6Gi
Inspiration
The COVID-19 Pandemic has led to many people wondering how they are going to vote for their selected leaders in the upcoming elections, especially in the United States where the presidential election will take place this November. People are hesitant to go to voting booths to vote due to the risk of catching the virus. The only options left are online voting, and mail-in voting. However, our traditional system for online voting is very unsafe and there have been many cases in various countries of hackers messing with the votes. As well, many have expressed fears of mail-in voting due to vote spoofing, and a rigging of the election. Motivated by this demanding issue that people keep forgetting about, we have decided to create CryptoVOTE.
What it does
CryptoVOTE is a decentralized web application that securely counts people's votes using a blockchain. The web application also has a verification Optical Character Recognition (OCR) system which reads the user's Voter ID or driver’s licence and verifies it with a simulated government database using MongoDB Atlas to make sure that the individual voting is eligible and real. The utilization of an OCR alongside the blockchain system makes it virtually impossible to hack, through brute force or any other malicious strategy - creating a safe way for people to vote online.
How we built it
We built CryptoVOTE using a wide variety of tools and frameworks. These include ReactJS for the front end, a Blockstack Gaia storage/MongoDB Atlas combo to act as a decentralized backend and store user votes in a blockchain format, Blockstack for the decentralization log in/log out process, and TesseractJS for the OCR verification as well as NodeJS and Express for the non-voting backend.
Challenges we ran into
Most of our challenges lied in deploying the actual application and backend. Due to unknown issues, we spent hours trying to deploy our front-end to firebase, and backend to Google App Engine. However, we later realized it was a combination of Blockstack and MongoDB issues. Due to CORS, we were unable to send POST requests to our backend, until we found out how to allow it in our application. MongoDB also didn’t allow us to deploy to Heroku, as we were unable to whitelist the dynamic IP address for MongoDB Atlas. Lastly, Blockstack caused some hiccups on the way, as it would not allow us to deploy our frontend to Firebase static hosting. However, in the end we were able to figure out the issues, despite it costing us hours.
Accomplishments that we're proud of
We are proud to have learned to create a truly decentralized and safe way of voting in just 24 hours. It was all of our first time creating a blockchain app and we are very excited to have succeeded in making it. We hope that our creation will be able to impact many and provide a safe and secure way to vote.
What we learned
It was our first time building a blockchain app and we learned a lot. We learned how the Blockchain system works, its technicalities, why it is so secure, its potentials for the future and how to build one. We also learned a lot about how backend databases work. After studying the Gaia Storage database and MongoDB Atlas one, we were eventually even able to combine the two to make a decentralized database and that was very exciting.
What's next for CryptoVOTE
CryptoVOTE has the potential to be an extremely useful and versatile app. It solves an urgent and complex COVID-19 issue that determines the fate of entire countries. The election process is extremely important and can not be messed around with at any cost and our app is integral in solving the unsecure online voting problem. We hope to talk to various organizations (whether it be as small as schools having a valedictorian election or as big as the American Presidential election) and offer them our solution to this grave problem.
Built With
blockstack
css3
express.js
gaia-storage
ganache
html5
javascript
metamask
mongodbatlas
tensorflowjs
tesseract
Try it out
github.com
mihirkachroo.github.io
cryptovote.tech | CryptoVOTE | A Decentralized Blockchain Web Application For Secure Election Voting | ['Bill Bai', 'Neil Mitra', 'Mihir Kachroo'] | [] | ['blockstack', 'css3', 'express.js', 'gaia-storage', 'ganache', 'html5', 'javascript', 'metamask', 'mongodbatlas', 'tensorflowjs', 'tesseract'] | 26 |
9,989 | https://devpost.com/software/botparty | Inspiration
Learning RPA
What it does
Performs automated functions
How I built it
Using AutomationAnywhere Software
Challenges I ran into
Time
Accomplishments that I'm proud of
Learned how to use RPA software
What I learned
Using RPA is a lot of fun
What's next for botParty
More botParties
Try it out
github.com | botParty | Just playing around with bots | ['Ed U'] | [] | [] | 27 |
9,989 | https://devpost.com/software/efficient-economic-lockdown-equlibrium | Inspiration
I was inspired by my high-school project about history of pandemics, study of aerodynamics, kinetics in physics, random walks, psychology of well-being in isolation, and following news of very different approaches of different countries, in a try to find an 'equilibrium approach'. It assumes that 2m away, always, no matter the circumstances, would be too rough of an approximation to use in every possibility in the world.
What it does
Simulates society on micro and macro scale to measure/approximate exposure, and what minimizes loss to society (economic loss, mental health loss, loss of life and different losses)
How I built it
Simple implementation.
Challenges I ran into
Lack of teammates, and a lot of real-life challenges.
Accomplishments that I'm proud of
Simplifying SIR model so much, succesfully.
What I learned
Syntax
What's next for Efficient economic lockdown equlibrium
Impact of those decisions on well-bing of people according to character, and on economy (closed places)- macroeconomic view.
Built With
java
r
Try it out
github.com | Efficient lockdown equlibrium, places closure SIR simulation | Modelling epidemics with different policies, different places to leave open, aiding goverments' policy decisions; featuring random walks. Modest try. | ['GabrielaNiemcewicz Niemcewicz'] | [] | ['java', 'r'] | 28 |
9,989 | https://devpost.com/software/employee-welfare-management-bot | Since we are now working from home due to this pandemic situation, we plan to develop a BOT which can get the pulse of all employees and understand their challenges and address their concerns in a best way. That's how we got inspired and developed our Employee Welfare Management BOT. Actually, we build it using a new environment - A2019, there was a lot of challenges in learning the new functionalities and finally we did it.We learned lot of new technical aspects in A2019 by doing this project.
We also plan to suggest this 'Employee Welfare Management BOT' to our leadership team to implement in our whole organization. | Employee Welfare Management BOT | Our idea is to get the pulse of all employees by sending MS Forms link and understand their challenges in some specific categories and tag the employee to respective group to address them. | ['Muralidharan Durai'] | [] | [] | 29 |
9,989 | https://devpost.com/software/asd-qunovb | Inspiration - Effective testing for COVID-19 is key to control the pandemic— knowing who is infected, who has been exposed, and who is immune. Though there have been major efforts around the world to increase the production capacity of Covid-19 testing kits, the demand is likely to exceed the actual capacity. Thus, there is a need to identify the potential patients of COVID-19 to ensure optimum testing and prevent any unnecessary disease spread while testing. This is what inspired us to create this solution
What it does - This solution will ask all relevant questions from the users and provide assessment results & recommendations based on the user’s symptoms. It also has the capability to book an appointment for the patient with the nearby doctors based on their availability
How I built it - This has been achieved by centralizing health care physicians’ data along with their availability schedule and combining the potential of RPA & Conversational AI. Chatbot assesses the user's symptoms and RPA helps in booking appointment with the doctor
Challenges I ran into - Building the connection between chatbot and RPA was a tricky task but FireBase database helped us resolve this. We were able to connect to Firebase database both through chatbot and RPA to make this handshake possible
Accomplishments that I'm proud of - Our solution is capable of increasing awareness towards Covid-19 self assessment and prevention. It also helps in booking appointment with doctors in case of medical assistance required. Also, the overall reach of this solution is around 2 billion people worldwide which will significantly improve the current Covid-19 testing across the world
What I learned - We have learnt a lot about how technology can help during these kind of situations. A simple solution can be also very helpful to the normal people and can create a big impact. Customizing the chatbot to interact with RPA was something very interesting that we learnt during this project.
What's next for COPE - Covid-19 Patient Evaluation - We can add features like video conferencing with doctors & placing IVR call to the patient's emergency contact in case of medical emergency. Also, this solution can be evolved to a Universal Patient Self-Assessment suite for other ailments as well
Built With
amazon-ec2
api
chatbot
database
excel
firebase
rpa
Try it out
github.com | COPE - Covid-19 Patient Evaluation | An initiative to use technology to empower people to cope with this pandemic. It's an advanced tool built to allow users to self assess their symptoms and seek guidance when to get medical attention | ['Akshit gupta', 'vaibhav aggarwal', 'Neha Singh', 'Naman Mehta'] | [] | ['amazon-ec2', 'api', 'chatbot', 'database', 'excel', 'firebase', 'rpa'] | 30 |
9,989 | https://devpost.com/software/anti-covid19-active-mask | prototype
The current pandemic has pushed me to seek solutions for a reusable, effective and stable face mask over time.
In fact, common filter masks tend to gradually lose the ability to filter viruses and bacteria.
On the contrary, this system is absolutely stable because it does not filter but inactivates the virus / bacterium, keeping it caught while it is destroyed by UVC rays and electrostatic charge.
Built With
hardware
Try it out
www.hackster.io | ANTI-COVID19 Active Mask | Common filtering masks tend to lose their ability to filter viruses and bacteria over time. This system does not. | ['andrea reale'] | [] | ['hardware'] | 31 |
9,989 | https://devpost.com/software/simple-payment-app | Inspiration: Creating a simple payment app on the Marqueta platform
What it does: Simple payment interface
How I built it: Using Marqueta API and Javascript
Challenges I ran into: Using Marqueta API and the encryption required for the product
Accomplishments that I'm proud of: Creating the final product
What I learned" Everything related to the Marqueta platform
What's next for Simple Payment App: Improve it further taking today's payment app challenges
Built With
api
java | Simple Payment App | To create a simple payment application on the Marqueta platform | ['Sandeep Chakravartty'] | [] | ['api', 'java'] | 32 |
9,989 | https://devpost.com/software/oksur | cover
Web site
Logo
Inspiration
To prevent the COVID-19 infections spreading, lots of diagnosis test-kits have been developed all around the world. Diagnosis is important for the isolation of the infected people, preventing them from spreading the disease and is also important for the observation and study of the infection. Most of the test kits based on the samples taken from blood, mucosa layer inside the nose and throat. These samples are used in RT-qPCR, antigen and antibody tests. RT-qPCR technique is the one with highest confidence, however it is costly, not portable and takes too much time. The problems with RT-qPCR raise the need for cheaper, efficient and portable new methods.
According to WHO, *
dry cough is an important symptom for 67,7% of the patients. *
WHO
A dry cough is when the cough does not include mucus secretion. Coughing of people with COVID-19 can have a distinct sound profile that can be differentiated from other coughing sounds. The different sound structure can be analyzed by algorithms we have developed, and these algorithms can be used as a novel diagnosis tool for COVID-19 that is cheaper, efficient and portable.
The Aim
This research aims to build up machine learning algorithms that can inform the diagnosis of COVID-19 based on the people's coughing and breathing sounds. After developing an algorithm by using large scale, crowdsourced data collection from healthy and non-healthy participants, we can create a novel diagnostic tool for COVID-19 that is cheaper, efficient and portable and we can use it as an early diagnostic tool.
If successful, all the countries and people in the world will be the beneficiaries. Moreover, the work in this project can also be scaled for the other respiratory diseases rather than COVID-19.
ML Model
This
is the research repository of Covid-19 Cough Sound Classification. You can read the details of research from the web site we prepared.
https://caglayan.github.io/covid19/en/research
Team
Our team is made up of two graduate students from Boğaziçi University, Istanbul.
Çağlayan Şerbetçi is a graduate student in System and Control Engineering and M. Görkem Durmaz has a bachelor’s degree in Molecular Biology & Genetics and she is now a graduate student in Computer Engineering department.
Project Web Site
In this project, COUGH AI, we have developed a website. This web site record coughs with various diagnostic information. It works on all mobile devices. Please record your cough sounds and help our research!
Web site:
https://caglayan.github.io/covid19/en/
more details.
Built With
javascript
machine-learning
matlab
node.js
react
Try it out
caglayan.github.io
github.com | COVID-19 Detection from Coughing Sounds Using AI | This research aims to build up machine learning algorithms that can inform the diagnosis of COVID-19 based on the people's coughing and breathing sounds. | ['Çağlayan Şerbetçi', 'Görkem Durmaz'] | [] | ['javascript', 'machine-learning', 'matlab', 'node.js', 'react'] | 33 |
9,989 | https://devpost.com/software/evisitor-card | Inspiration
The motivation originated from the present circumstance where everyone is looking for minimal touch to the common things. Most organizations see visitors every day to their office regardless of whether it is an interview candidate, vendor, or salesman. And all the visitors will be accessing the same gadget either tablet, visitor register or any medium to collect visitor entry and common ID cards which may not be reasonable in this circumstance.
What it does
eVisitor Card digitizes the visitor check-in to the workplace premises. This solution sends the approval code (QR Code) to the visitor. This QR Code will be validated upon visit without contacting any gadget. If the QRcode gets authorized, the bot will snap the picture of the visitor and will send the entry card over email.
How I built it
Below are the features and brief idea of how it was built:
1. Generate the QR Code
- Read the details from Google sheet and based on the email address generate the QR Code using Google Chart API.
2. Send the QR Code to the visitor
- Using the built-in email functionality of A2019 sends the email to the visitor with the QR Code generated at the above step.
3. Scan the QR Code
- Call python script to show the window to scan QR Code and once it finds the QR Code the code will return the content.
4. Validate the QR Code based on the details provided by visitors
- Based on the content returned from the above step, validate the content in visitor details Google sheet to check if any entry exists.
5. Show the camera window and take the photograph of the visitor
- If visitor details exist in Google sheet, Call Python script to show the camera window and Security can take the photo by clicking on Enter button.
6. Send digital entry card to the visitor over email
- Call DLL file and pass parameters i.e. username, password, visitor email address, and so forth which will send entry card to the visitor.
7. Delete the visitor details from google sheet
- Delete the visitor details from Google sheet once the entry card has been issued.
8. Add the visitor details in another google sheet to keep the details for future
- Store the visitor details from the above step in variable and pass these values in Google sheet
Challenges I ran into
Problem:
The challenge was to send the entry card over Gmail with the inline image (only for an image stored in the local machine) using the built-in email functionality where the image was getting displayed as blank however the same functionality was working fine while sending the email in outlook.
Solution:
Used DLL file to send the email with an inline image which is sending the email with an entry card to the visitor.
Problem:
Providing the dynamic cell in set cell option of Google sheet was throwing error and was not allowing to give the variable like A$countRow.Number:toString$ even though the count variable was typecasted to string.
Solution:
Assigned the cell address in a variable and used that variable in the Google sheet set cell option.
Accomplishments that I'm proud of
I am pleased with the idea of helping society in not spreading the deadly COVID-19 virus.
What I learned
I learned many new features of A2019 i.e. Forms, Google Sheet, etc while developing this solution. Apart from that I also learned how to create DLL files and use the same in A2019.
What's next for eVisitor Card
Scanning Government ID
Auto Face-detection
Built With
a2019
google-chart
google-spreadsheets
python
Try it out
github.com | eVisitor Card | No touch solution for visitor entry at workplace | ['Barkha Rastogi'] | [] | ['a2019', 'google-chart', 'google-spreadsheets', 'python'] | 34 |
9,989 | https://devpost.com/software/bot-o-ship | NOTE: In the end I was unable to move the bot to a public domain for some reason even after following the instructions here (
https://aai-covid19-botathon.devpost.com/updates/12930-enterprise-a2019-guidelines
). I have included set of images that show every line in the bot and their setting that can be found in the repository linked to this project.
This submission is for the Travel, Supply Chain & Logistics category.
Inspiration
I experienced a lot of problems with delivery during Covid-19. Many inexperienced delivery people are hired to offset the huge increase in orders. They often lose packages, deliver them incorrectly, or skip your house. The bootstrap shipping method also means I rarely get notified when my package arrives. I wanted a way to help fix this.
What it does
It allows delivery orders to be tracked by just sending an email. The delivery driver takes a picture of where they left the order and sends it by email to the company they deliver for (This means that delivery drivers don't need to install an additional app). From there, an automation anywhere bot gets triggered and downloads the image and the metadata from the email. It is able to extract the gps location from the image metadata, and the order number using OCR. If the product is shipped in the correct location, it sends an email to the customer saying their order is there for pickup. If the location is incorrect, it sends an email to the delivery person that they made a mistake. All of this is updated in a customer order spreadsheet.
How I built it
Automation Anywhere with python scripts to handle the metadata scrape and address to gps coordinate conversion.
Challenges I ran into
Learning the automation anywhere tools and debugging some errors
Accomplishments that I'm proud of
Getting the entire project completed and working at 100%
What's next for Bot-O-Ship
Creating a map to follow the delivery route of the driver to determine if they are doing their job efficiently. This can be done using the gps metadata from the images they take for every order.
Built With
automationanywhere
gps
python
Try it out
github.com | Bot-O-Ship | A bot that helps companies track their deliveries and improve customer experience during Covid-19 | ['Daniel Weisberg'] | [] | ['automationanywhere', 'gps', 'python'] | 35 |
9,989 | https://devpost.com/software/safeapp-1qhtub | Inspiration
Currently there are 12300 persons in institutionalized quarantine and over 10200 people are hospitalized in Romania.
Imagine 336 hours in the life of a COVID-19 suspect, quarantined alone, isolated away from his family, without human interaction and who is constantly measuring every change in his body condition, fearing C-positive.
Imagine >336 hours in the life of a sick person who is lucky enough to not be in the Anesthesia Intensive Care Unit but who is isolated from doctors, family and who is afraid for his own life and needs to communicate more with doctors, a psychologist, state institutions or other people in order to distract himself from his own fears and thoughts.
And now imagine how easy it is to have a mental crisis while in quarantine or in the hospital and at the same time to not have anyone around with sufficient time to see you, hear you, calm you or help you.
SAFEapp is created from these real needs of patients/suspects.
What it does
SAFEapp connects patients/suspects with those who are separated from them by the disease: doctors, psychologists, juridical counselors, state institutions (City Hall, Police, Emergency Situations Department), other hospitalized or quarantined people, all in a MultiChat, full of warmth and color through entertainment options (games, videos, movies, e-books) to increase their well-being, immunity and faster healing. And because our goal is health, we also have a package of options for healthy people: free medical, psychological and legal consultations, e-market offers, COVID hospitals map, positive information, news about NGOs and a space where to attach his contribution to the COVID reality.
The key element of our solution is the construction of the patient's mental map, so that a virtual psychologist (AI) can estimate in advance the appearance of crisis states of the patient or of the COVID suspect.
How I built it
Initially it all started with a quick, simple and targeted solution for patients, suspects and their families (
www.caz-covid.ro
).
Challenges I ran into
In a short period of time the website proved to be too unattractive and too targeted on a single link in a vast system, which determined us to use other channels to reach the targeted group: Facebook, Instagram, press, epidemic communities, etc.
Accomplishments that I'm proud of
The time was too brief and people’s panic was too big to concentrate on other things than the 4000 online consultations and 100 psychological and juridical counselling sessions, lists with material support, applications for financing from a variety of sources.
What I learned
We understood and we haven’t forgotten that we could do it differently, better, more complex, fresher and more positive. That’s why we increased the team with people of various ages (teenagers, bachelors, young people) with different educational backgrounds: IT, arts, psychology, mathematics and computer science. We also introduced the function of virtual psychologist for crisis estimation.
What's next for SAFEapp
So, SAFEapp is the improved version, adapted to both the needs of state institutions to communicate and answer promptly and positively to patients/suspects and also to the needs of patients/suspects to feel safe for themselves and their families. SAFEapp has the governmental version that we will deliver to hospitals, quarantine centers, City Halls, Police and the Emergency Situations Department, as well as the community version for healthy citizens.
We know that this kind of application, inspired by the COVID reality, can be adapted to any other disease/infectious disease or in case of a future different regional epidemic, so we aim to easily adapt it to wider causes and to the requirements of several European states and beyond.
The benefits of implementing the application on a large scale are:
•Public administrations interact more efficiently and promptly with people most affected by the epidemic (patients, suspects and their families).
•The existence of such a vast simultaneous interaction can interconnect not only patients in a transnational network, but also doctors.
•Anticipating the occurrence of psychological crisis situations of patients and suspects.
•Creating a positive environment and framework for patients/suspects.
•Providing a wider range of interactions than family members and virtual network (in which they do not want to expose themselves).
Development: 12 months
Built With
ai
android
css
digitalocean
htm
java
javascript
mysql
php
rocket.chat
wordpress
Try it out
safeapp.caz-covid.ro | SAFEapp | multiCHAT with AI for government sector (hospitals, town halls, police, quarantine centers).A mental map and memory, which connects patients/suspects with state institutions, doctors, psychologists | ['Diana Nitescu', 'Ivan Maria', 'stanciu_georgiana17'] | [] | ['ai', 'android', 'css', 'digitalocean', 'htm', 'java', 'javascript', 'mysql', 'php', 'rocket.chat', 'wordpress'] | 36 |
9,989 | https://devpost.com/software/covid-19-virtual-travel-assistance | Advice Email Request and Response
Automation Flowchart (High Level)
Inspiration
During the initial dates of the lockdown in
India
,
a close relative of neighbors died in a district far away from our city (Mumbai)
, and they had no clue what to do? How they can travel during lockdown? If they apply for travel pass, how many people can travel in a car then? This incident inspired me to create this solution when I came to know about
CoVID-19 Botathon
in the last week of May’20.
What it does
Travelling during this pandemic is not recommended
; however, being social animals, needs arises causing us to travel from a place to another.
CoVID-19 Virtual Travel Advisor
assist us find how safe our travel or commute is!
The Govt. of India
has classified all the districts in the country into
RED\ORANGE\GREEN Zones
. Government has also defined rules for each of the zones. There are special travel related advisories to be followed while traveling through these zones.
CoVID-19 Virtual Travel Advisor BOT
leverages
MapMyIndia Geo APIs
to find the optimal route from
Origin to Destination addresses
fed to the BOT via Email. It then
identifies all the districts
the route passes through. The districts are then classified into
RED\ORANGE\GREEN Zones
using information provided by
the Govt. of India on its CoVID19
dedicated website
www.mygov.in/covid-19
.
The BOT makes the suggestions based upon the findings and provides a report listing all the districts and their CoVID19 zone classification. This can help us plan the travel as per government's advisory for travel in RED\ORANGE\GREEN Zones. This will avoid hurdles we have not planned for.
How I built it
I have used
Emails received in MS Outlook
desktop application as the start point. A rule defined in MS Outlook
moves the request email from Inbox to a dedicated folder
when an email with a defined subject arrives. The BOT iterates through each email when manually invoked.
This BOT is built in
Automation Anywhere’s A2019
(Community Edition). BOT leverages several
Geo APIs from MapMyIndia
in its course of action. It starts the operation with
Geocoding API
converting the Origin and Destination addresses into
geographic coordinates (latitude/longitude)
to be placed in
Routing API
which calculates optimal (used as default calculation type) driving routes between specified locations including via points\intersections. It then uses distinct intersections to be able to find the district in which the intersection are.
Reverse Geocoding
is a process to give
the closest matching address
to a geographical coordinate (latitude/longitude). BOT uses
MapmyIndia’s Reverse Geocoding API
to identify the districts on the intersections in the route. To identify
CoVID19 Zone Classification
of the districts, I have used the information available on
CoVID19
dedicated website
www.mygov.in/covid-19
of
Govt. of India
.
Challenges I ran into
First, I had very less time to work upon on the solution. Secondly, it was my first time to build a complete BOT using
A2019
and very first time to work with
Geo APIs
. Building a working solution in a short period was itself a challenge. Understanding working of
Geo APIs
and decoding
Routing API's result
was the main challenge I faced.
Accomplishments that I'm proud of
The working solution itself is a great accomplishment for me. I am proud of that I have built an end to end solution using Geo APIs.
What I learned
Building BOTs using A2019
and usage of
Geo APIs
What's next for CoVID-19 Virtual Travel Assistance
Initially, I had decided to build
a mobile app
to feed the inputs to the BOT. However, due to very less amount of time to implement the solution along with office work, I have used
MS Outlook
to feed input requests to BOT. We can have
a mobile app integrated with AWS S3
to feed inputs to BOT and receive output. A very sophisticated solution can be developed to provide travel advisories.
Also, it is currently implemented for
India
only.
The idea was to show how BOTs can help humans in safeguarding their travels.
The solution has potential to serve peoples from other countries\regions.
Built With
a2019
email
geocoordinates
mapmyindiaapi
maps
mygov.in
outlook | CoVID-19 Virtual Travel Advisor | CoVID-19 Virtual Travel Advisor finds how safe travel or commute is based upon the districts route passes through! This can help us plan as per government's travel advisory in RED\ORANGE\GREEN Zones. | ['Akif Patel'] | [] | ['a2019', 'email', 'geocoordinates', 'mapmyindiaapi', 'maps', 'mygov.in', 'outlook'] | 37 |
9,989 | https://devpost.com/software/covid-19-workplace-health-safety-plan | Bot Making Call if Person not wearing mask or Maintaing Social Distance
A2019 working as Bridge For integrating Computer Vision and Chatbot and Phone Call and creating E2E Solution
Chatbot For Helping Employess for increasing there productivity and safety
Mandatory Wearing Mask and keeping Social Distance # Stay Safe
Inspiration
As We All know Everyone in the world is talking about new Normal During or Post Covid-19 Situation and Government allowed to open Factories, Offices, Malls, Supermarkets with limited no of people. As Social Distancing is must for Employees as well as Employer Safety and we know it's not possible for the Employer to detect all employees all time whether they are wearing mask or maintain social distance or If Max number crossed. And there is no way employees can check before going in Public area whether it's free or not.
we all should realize by now why china, Germany , Italy & Iran had flattered their curve , it just because they started following the social distancing & Wearing Face mask .Its important to us to follow the same , so this is the Bot does this job on behalf of man power.
What it does
1.This Automation Anywhere Bot will keeps on monitoring live CCTV Footage inside organization. And if it will find any employee not wearing Mask it will perform Facial Recognition and fetch Employee details from the Employee Database and Call Employee at his Phone and SMS as well for alerting for wearing mask.
Bot will also call admin at his phone if people are not maintaing Social Distancing and give him area details so that he can take action.
Bot will also call admin at his phone if Max Number reached inside area and give him area details so that he can take action.
This Solution Provides Chatbot for employees using which Employee can check before accessing free areas like Cafeteria, Smoking Zone, Etc.
How I built it
I built this bot using Technologies:-
Automation Anywhere
Computer Vision
OpenCv
Python 3
Twilio (For Making Phone Call)
IBM Watson (Chatbot, Discovery, NLU)
Challenges I ran into
Integration of multiple technologies.
Accomplishments that I'm proud of
I created a solution which will help not only Factories or Corporate Office for caring about there Employees Safety even it will be use in Supermarkets, Malls, Schools, Government Offices.
What I learned
re-invent the new wheel…utilize the existing
Integration of multiple Technologies for creating single solution for battling against Covid 19.
What's next for Covid 19 Workplace Health & Safety Plan
Creating Mobile Application and Web portal for creating Touch less Environment.
Built With
automationanywhere2019
computervision
html5
ibm-watson
keras
opencv
python
sklearn
tensorflow
twilio
Try it out
github.com
github.com
github.com | Covid-19 Workplace Health & Safety Plan | Bot monitor live CCTV in any Factory/Office if person not wearing mask or maintaining Social Distance or Max count reached in area It will make call doing facial recognition.Chat using Covid19 Chatbot | ['tanya Lakhotiya'] | [] | ['automationanywhere2019', 'computervision', 'html5', 'ibm-watson', 'keras', 'opencv', 'python', 'sklearn', 'tensorflow', 'twilio'] | 38 |
9,989 | https://devpost.com/software/deployment-automation | Process Flow Diagram of Deployment Automation
Inspiration
I got an inspiration, when I started deployment manually and when there is the unavailability of the workforce. It becomes a very tedious task and time-consuming.
What it does
The "Deployment Automation" has the capability to timely deploy continuous software deliveries at the onsite environment and offshore environments. It picks the ". properties file from an absolute path and perform tasks accordingly. After deploying the packages to the offshore environment, it creates the docker image of the whole application from the dockerfile and then pushes the image to the docker hub, from where the client site, pull the image and run it as a container.
How I built it
I create a shell script, which read ". properties" file. This file includes artifactory link of packaged deliveries, environments name(where to deploy) and it's IP with defined variables respectively. I create jobs in Jenkins with "init" job as a starting job and schedule it every 2 min. This init job read variables from ". properties" file. And, deploy packaged deliveries in respective environments.
Challenges I ran into
The challenge is how to append incremental files in the complete files in different environments. Since each incremental files have a different format of representation. So, I need to find out the pattern that definitely looks out for incremental file and append accordingly.
Accomplishments that I'm proud of
I made the whole manual deployment to automation deployment. I feel happy now since I do not need to remain online for deployment. The job picks the PDN(Processed Definition Number) file which includes artifactory path server name, and user and does the processing as required. And, using the docker image, the whole application will get deployed at onsite without doing manual deployment at onsite. This also enables offshore environment in sync with the onsite environment.
What I learned
I learned shell scripting, Jenkins, Git, SVN, Docker. And, more important I learned how to make a designed process and workflow for automation.
What's next for Deployment Automation
That depends on business needs and new updates.
Built With
docker
git
jenkins
shell-scripting
svn | Deployment Automation | The idea is to automate the continuous software deliveries at onsite environment and in different offshore environments.Since,in the COVID-19, workforce can't available all time for manual deployment. | ['Shubham Tomar'] | [] | ['docker', 'git', 'jenkins', 'shell-scripting', 'svn'] | 39 |
9,989 | https://devpost.com/software/aayushman-ai-powered-smart-multi-purpose-covid-19-bot | Home Page
Screening / Diagnosis
Prediction
Psychiatric Therapy
Employee Checkin
Diagnostic Report
Geo fencing
Common Questions
Facebook Messenger bot
Whatsapp bot
Inspiration
My brother is a Frontline Health Worker who treats Covid-19 patients in Bangalore, India. Everyday my family and me constantly pray nothing happens to him because he is constantly under risk of getting infected with Covid-19. In order to solve this problem that effects millions of brave hearted people who sacrifice their lives to stop this pandemic all over the world, AAYUSHMAN was built. "AAYUSHMAN" in Sanskrit means Safe and Healthy.
What it does
Features / Functionalities :
Comprehensive Covid-19 Screening / Diagnosis with Prediction & Diagnostic Reports.
Geo Fencing Based Nearest Covid-19 Home Quarantined Person's Information Notification.
Answers to Hundreds of Covid-19 related Queries & FAQ's.
Virtual Psychiatric Therapy to Combat Loneliness / Depression.
Employee Checkin for Companies to Track and Monitor.
Voice Controlled Dashboard for Covid-19 Healthcare Professionals for Easy Data Monitoring.
AAYUSHMAN also Deployed in WhatsApp & Facebook Messenger Platforms.
How we built it
Using Dialogflow Framework to create Google Cloud deployed Bot that is also be deployed over multiple platforms such as Whatsapp and Facebook Messenger for Feasibility and Vibrancy.
We used Node.js for the frontend and backend.
We used NLP for voice/speech recognition.
Challenges we ran into
In training our bot to process speech accurately.
Deployment in other platforms.
Accomplishments that we're proud of
We have successfully deployed our bot in Google, Whatsapp and Facebook Messenger Platform after elaborate beta testing and is ready for use.
What we learned
Apart from experience in learning new technologies and frameworks. We learned to leverage technology for the good that can impact people well. We learned to Innovate for the society and we are now obsessed with it. We look to develop products in the future that can help and save humanity.
What's next for AAYUSHMAN - AI Powered Smart Multi - Purpose Covid-19 Bot
Especially in India where the Medical System still lacks advanced technology as a result people still practice traditional screening and testing. Our bot could certainly eliminate this making it faster and safer. Hence we would like to see AAYUSHMAN being utilised in Public and Private Hospitals. This would certainly eliminate the risk factor for Health workers to an extent.
Built With
dialogflow
google-cloud
natural-language-processing
node.js
Try it out
github.com | AAYUSHMAN - AI Powered Smart Multi - Purpose Covid-19 Bot | It Assists & Helps the Novel Corona Virus Frontline Health Workers, Healthcare Providers & the Common Man. | ['nihal konan'] | [] | ['dialogflow', 'google-cloud', 'natural-language-processing', 'node.js'] | 40 |
9,989 | https://devpost.com/software/call-center_outboundcalls_automation_planchange_a2019 | Inspiration
To help Society and Business in COVID situation by providing an immediate solution that serves a business need and so business can serve Customer/society better
Real need for Solution to solve Contact Center Customer challenges. Talking to big heads driving BPOs like Accenture, TCS, CST, firmed our idea.
Build Production Ready solution that supports
Business to continue following the same process from the office laptop/desktop which is now at home.
Data Privacy and Security.
Keep the Agent productivity & monitoring intact
Automated solution with Cloud Telephony platform integration
What it does
Agent to use Interactive Forms in A2019 and deploy a bot via WLM technology on Remote Runner Machine.
The Bots are integrated with the IVR and ACD systems.
Telephony and CTI integrations with leading contact center vendors available.
Single pane view of all customer data on one screen, using interactive forms.
Agent triggers bot to provide more information or update fields across multiple applications
Next-step-guidance is presented to the agent, to eliminate errors and fraud, and improve upon training.
The bot auto-completes the after-call work by setting reminders SMS, sending emails, and updating multiple systems.
How I built it
We used latest web based AA platform A2019.
Integrated with Cloud Telephony platform Exotel (trial version) with A2019 – using Google Suite Script and AA APIs
Covered end to end flow , like Self Service Module, In Call Guidance, Post Call Automation and Performance and QC dashboard using Bot Insight
We built a Custom Command pkg for WLM Work item creation.
We used few APIs to automate Work Queue creations & device association as soon as Agent executes the bot.
Solution helps executing bot on remote runner machine and provide interaction between bot & human to support any process need Human-bot collaboration.
## Challenges I ran into
Choosing right Cloud Telephony platform that allows to automate end to end flow. (we used trial of Exotel)
Design integration of Exotel with A2019.
Aspects to be covered to serve Pre Call Transfer, Post Call transfer and Post call Completion activities.
No inbuilt mechanism to execute a bot on Remote machine. (we achieved using WLM technology).
No inherent ability to automate WLM, so to reduce Operation Overhead creating WLM queues/workitems for thousands of Agents. (we automated it 92% to 95%, remaining 5% to 8% is one time Job)
Accomplishments that I'm proud of
We could build Solution that is:
Most suitable for Contact Centers need and support business Continuity.
Helps companies supporting/helping their Customers & society, in adverse time like COVID - 19.
Industry/domain agnostic. Be it Healthcare, Finance, Banking, Logistic, Supply chain etc, it works.
Saleable & scalable and support all aspects e.g. Security/Scalability/Performance/HA-DR etc
Fully Automated, reduce Manual/operation overhead.
Production Ready.
What I learned
Business:
Support Business Continuity is the most important factor even in COVID like situation.
Forecasting problems and start building solutions to support business and the whole society.
Pick a right problem as there is always a way to solve the problems.
Technical:
IVR and ACD systems.
Better way of utilizing powerful web based Automation Anywhere platform A2019.
How helpful Custom Command Package & AI Senses features have been.
How individual components can be integrated to derive a solution to support Business Continuity.
What's next for Call Center Solution
We would like to try fit in the solution for other Call Center use cases
Try to integrate with few more IVR platforms.
Built With
a2019
exotelapi
googleappscript
Try it out
github.com | Call Center_OutBoundCalls_Automation_PlanChange_A2019 | How COVID-19 is presenting an opportunity to combat operational challenges in call center by integrating IVR and ACD system that helps boost productivity | ['Ankit Thakkar'] | [] | ['a2019', 'exotelapi', 'googleappscript'] | 41 |
9,989 | https://devpost.com/software/precon-prevent-contagious-ar-ar-training-simulation | Inspiration
The inspiration comes when I see a lot of peoples still acting improperly to current situation (COVID-19). Many of them still forgot about this viruses and act like this is nothing, they didn't wash their hand, touching carelessly, etc
What it does
With this AR application, we can simulate the event in daily life, what should we do and shouldn't. So people can learn and remember what exactly action should be taken when it comes to prevent contagious of COVID-19. And more importantly, Using AR for training simulation is the one of many ways to do a safe simulation, without being infected from the virus. It can helps other people for keep their self healthy from viruses based on their reaction.
How I built it
I'm using one of the common game engine, Unity, and AR Foundation for the AR part. I'm combining the 3D assets and make the simple training simulation. I'm also trying echoAR for 3D cloud services but not fully implemented.
Challenges I ran into
I need to find more information about Augmented Reality also do trial and error, sometimes makes me dizzy. Also, this is the first time using echoAR services. Got some problem about the limitation for using it's API, since currently I'm using free version.
Accomplishments that I'm proud of
This project actually. Somehow proud that I can be part of "helping others" in this pandemic with my own way. Especially helping medical team to prevent other people being infected. Helping people with Extended Reality technologies are something that really change the views of AR/VR/MR application.
What I learned
From this project, I'm more learn new things about AR, how to solve problem, how to adapt to the new things, also more exploring about COVID19 also for my self I'm learning more about what should we do and should't. More exploring some advice for being healthy during this pandemic.
What's next for test project
Maybe if I can really continue with this project, I hope can upgrade more simulation regarding COVID19, and maybe will try to do Virtual Reality Training Simulation, so it can be more immersive to do a training.
Built With
android
arcore
arfoundation
c#
echoar
unity-technologies
Try it out
precon.rgplays.com | PreCon (Prevent Contagious) AR - AR Training Simulation | Educate people using Augmented Reality, more like training simulation about how to react to this current situation, to keep them healthy by give them example, virtually. This way can be more safety. | ['Kaustik Bhabbur'] | [] | ['android', 'arcore', 'arfoundation', 'c#', 'echoar', 'unity-technologies'] | 42 |
9,989 | https://devpost.com/software/call-center_automation_covid-19_creditcard_replacement_a2019 | Inspiration :
1 To help Society and Business in COVID situation by providing immediate solution that serve business need and so business can serve Customer/society better
2 Real need for Solution to solve Contact Center Customer challenges. Talking to big heads driving BPOs like
3 Accenture, TCS, CST, firmed our idea.
4 Build Production Ready solution that supports
5 Business to continue following the same process from the office laptop/desktop which is now at home.
6 Data Privacy and Security.
7 Keep the Agent productivity & monitoring in tact
8 Automated solution with Cloud Telephony platform integration
What it does :
1 Agent to use Interactive Forms in A2019 and deploy a bot via WLM technology on Remote Runner Machine.
2 The Bots are integrated with the IVR and ACD systems.
3 Telephony and CTI integrations with leading contact center vendors available.
4 Single pane view of all customer data on one screen, using interactive forms.
5 Agent triggers bot to provide more information, or update fields across multiple applications
6 Next-step-guidance is presented to the agent, to eliminate errors and fraud, and improve upon training.
7 The bot auto completes the after-call work by setting reminders SMS, sending emails, and updating multiple systems.
8 Enforce data privacy and Standard Operating procedures (SOP) i.e. Agent will receive only Non-PII data from Bot for Validation and further usage.
9 Provides Real time analysis of transactions/tickets processed by Agent in one single Dashboard – using Bot Insight
How I built it:
1 We used latest web based AA platform A2019.
2 Integrated with Cloud Telephony platform Exotel (trial version) with A2019 – using Google Suite Script and AA APIs
3 Covered end to end flow , like Self Service Module, In Call Guidance, Post Call Automation and Performance and QC dashboard using Bot Insight
4 We used Interactive Form feature to gives single pane view for Agent.
5 We built a Custom Command pkg for WLM Work item creation.
6 We used few APIs to automate Work Queue creations & device association as soon as Agent executes the bot.
7 Solution helps executing bot on remote runner machine and provide interaction between bot & human to support any process need Human-bot collaboration.
Challenges I ran into :
1 Choosing right Cloud Telephony platform that allows to automate end to end flow. (we used trial of Exotel)
2 Design integration of Exotel with A2019.
3 Aspects to be covered to serve Pre Call Transfer, Post Call transfer and Post call Completion activities.
4 No inbuilt mechanism to execute a bot on Remote machine. (we achieved using WLM technology).
5 No default capability to let Human and Remote bot collaborate (exchanging information) with each other. (we used Interactive Form and WLM)
6 No inherent ability to automate WLM, so to reduce Operation Overhead creating WLM queues/workitems for thousands of Agents. (we automated it 92% to 95%, remaining 5% to 8% is one time Job)
Accomplishments that I'm proud of :
We could build Solution that is:
1 Most suitable for Contact Centers need and support business Continuity.
2 Helps companies supporting/helping their Customers & society, in adverse time like COVID - 19.
3 Industry/domain agnostic. Be it Healthcare, Finance, Banking, Logistic, Supply chain etc, it works.
4 Salable & scalable and support all aspects e.g. Security/Scalability/Performance/HA-DR etc
5 Fully Automated, reduce Manual/operation overhead.
6 Production Ready.
What I learned:
Business:
1 Support Business Continuity is the most important factor even in COVID like situation.
2 Forecasting problems and start building solutions to support business and the whole society.
3 Pick a right problem as there is always a way to solve the problems.
Technical:
1 IVR and ACD systems.
2 Better way of utilizing powerful web based Automation Anywhere platform A2019.
3 How helpful Custom Command Package & AI Senses features have been.
4 How individual component can be integrated to derive a solution to support Business Continuity.
What's next for Call Center Solution -
1 We would like to try fit in the solution for other Call Center use cases
2 Try to integrate with few more IVR platforms.
3 Try Outbound Call type use case.
Built With
a2019
acd
aht
attended
creditcard
interactiveform
ivr
unattedned
wlm
Try it out
github.com | Call Center_Automation_COVID 19_CreditCard_Replacement_A2019 | To combat operational challenges in call center (Bank)by integrating IVR and ACD systems with RPA A2019 that helps to enhance security to access PII data and boost productivity, during COVID pandemic | ['Prashant Kumar'] | [] | ['a2019', 'acd', 'aht', 'attended', 'creditcard', 'interactiveform', 'ivr', 'unattedned', 'wlm'] | 43 |
9,989 | https://devpost.com/software/call-center_automation_covid-19_hold-order_a2019 | Inspiration :
1 To help Society and Business in COVID situation by providing immediate solution that serve business need and so business can serve Customer/society better
2 Real need for Solution to solve Contact Center Customer challenges. Talking to big heads driving BPOs like
3 Accenture, TCS, CST, firmed our idea.
4 Build Production Ready solution that supports
5 Business to continue following the same process from the office laptop/desktop which is now at home.
6 Data Privacy and Security.
7 Keep the Agent productivity & monitoring in tact
8 Automated solution with Cloud Telephony platform integration
What it does :
1 Agent to use Interactive Forms in A2019 and deploy a bot via WLM technology on Remote Runner Machine.
2 The Bots are integrated with the IVR and ACD systems.
3 Telephony and CTI integrations with leading contact center vendors available.
4 Single pane view of all customer data on one screen, using interactive forms.
5 Agent triggers bot to provide more information, or update fields across multiple applications
6 Next-step-guidance is presented to the agent, to eliminate errors and fraud, and improve upon training.
7 The bot auto completes the after-call work by setting reminders SMS, sending emails, and updating multiple systems.
8 Enforce data privacy and Standard Operating procedures (SOP) i.e. Agent will receive only Non-PII data from Bot for Validation and further usage.
9 Provides Real time analysis of transactions/tickets processed by Agent in one single Dashboard – using Bot Insight
How I built it:
1 We used latest web based AA platform A2019.
2 Integrated with Cloud Telephony platform Exotel (trial version) with A2019 – using Google Suite Script and AA APIs
3 Covered end to end flow , like Self Service Module, In Call Guidance, Post Call Automation and Performance and QC dashboard using Bot Insight
4 We used Interactive Form feature to gives single pane view for Agent.
5 We built a Custom Command pkg for WLM Work item creation.
6 We used few APIs to automate Work Queue creations & device association as soon as Agent executes the bot.
7 Solution helps executing bot on remote runner machine and provide interaction between bot & human to support any process need Human-bot collaboration.
Challenges I ran into :
1 Choosing right Cloud Telephony platform that allows to automate end to end flow. (we used trial of Exotel)
2 Design integration of Exotel with A2019.
3 Aspects to be covered to serve Pre Call Transfer, Post Call transfer and Post call Completion activities.
4 No inbuilt mechanism to execute a bot on Remote machine. (we achieved using WLM technology).
5 No default capability to let Human and Remote bot collaborate (exchanging information) with each other. (we used Interactive Form and WLM)
6 No inherent ability to automate WLM, so to reduce Operation Overhead creating WLM queues/workitems for thousands of Agents. (we automated it 92% to 95%, remaining 5% to 8% is one time Job)
Accomplishments that I'm proud of :
We could build Solution that is:
1 Most suitable for Contact Centers need and support business Continuity.
2 Helps companies supporting/helping their Customers & society, in adverse time like COVID - 19.
3 Industry/domain agnostic. Be it Healthcare, Finance, Banking, Logistic, Supply chain etc, it works.
4 Salable & scalable and support all aspects e.g. Security/Scalability/Performance/HA-DR etc
5 Fully Automated, reduce Manual/operation overhead.
6 Production Ready.
What I learned:
Business:
1 Support Business Continuity is the most important factor even in COVID like situation.
2 Forecasting problems and start building solutions to support business and the whole society.
3 Pick a right problem as there is always a way to solve the problems.
Technical:
1 IVR and ACD systems.
2 Better way of utilizing powerful web based Automation Anywhere platform A2019.
3 How helpful Custom Command Package & AI Senses features have been.
4 How individual component can be integrated to derive a solution to support Business Continuity.
What's next for Call Center Solution -
1 We would like to try fit in the solution for other Call Center use cases
2 Try to integrate with few more IVR platforms.
3 Try Outbound Call type use case.
Built With
a2019
acd
aht
attended
interactiveform
ivr
sap
sfdc
telephony
unattended
Try it out
github.com | Call Center_Automation_COVID 19_Hold Order_A2019 | How COVID-19 is presenting an opportunity to combat operational challenges in call center by integrating IVR and ACD system that helps to enhance security to access PII data and boost productivity | ['Prashant Kumar'] | [] | ['a2019', 'acd', 'aht', 'attended', 'interactiveform', 'ivr', 'sap', 'sfdc', 'telephony', 'unattended'] | 44 |
9,989 | https://devpost.com/software/dis-cretion-cnhlfw | Log in to the unparalleled experience of decision making on employee request
The Request Dashboard
Review request details, alongside specific policy information, anonymised historic requests and areas of considerations highlighted for you
See the anonymised historic requests
Look out for the latest changes of guidance
Highlight the changes for you to review
Inspiration
Many organisations couldn’t process a large number of employee queries timely during the COVID-19.
There are evolving policies and guidance from all directions that HR practitioners need to maintain.
Employees and Managers exhaust their time and efforts on searching for the right information.
Many decisions on employee requests are not consistent across the business. Discretionary decisions are likely to be made using previous experience. Junior HR practitioners can be inexperience in making discretionary decisions, hence the discretion offering may not be at the optimal level.
What it does
Dis-cretion is a tool to empower staff to make informed decisions on employee requests efficiently and consistently.
It highlights specific internal policies, external resources (e.g. government guidance), anonymised historical requests, and areas of consideration.
How it works
An employee submits a request, which is sent to the line manager to review.
The manager sees the dashboard of requests and can review the details of them.
Dis-cretion presents specific policy information that is relevant to the request.
It also shares anonymised summary of some relevant historical requests.
Dis-cretion encourages structured, constructive discussions between manager and employee by suggesting areas of consideration and topics to both of them.
The manager can now make an informed decision.
The automation anywhere Email bot is triggered to send a customised update on behalf of the manager to the individual.
Decision and rationale are fed back to the repository.
Challenges we encountered
Limited backend capacity to run the machine learning model - need manual refreshing
Next steps
Look into alternative ways to capture employee requests, e.g. use chatbot or other major HR systems
Contribute to smarter Business Continuity Planning
Built With
adobe-xd
google-cloud
heroku
javascript
machine-learning
python
react
typeform
Try it out
dis-cretion.herokuapp.com
hellodiscretion.typeform.com
github.com
github.com | Dis-cretion | A tool to empower staff to make informed decisions on employee requests efficiently and consistently | ['Faith Chung', 'Monique Ho', 'Samuel Shum', 'Adrish Dey'] | [] | ['adobe-xd', 'google-cloud', 'heroku', 'javascript', 'machine-learning', 'python', 'react', 'typeform'] | 45 |
9,989 | https://devpost.com/software/bpo-work-from-home-solution-a2019 | Inspiration :
To help Society and Business in the COVID situation by providing an immediate solution which leverages Automation Anywhere’s wen native A2019 platform which serves an enterprise’s need and so they can serve their Customer/society better
Real need for Solution to solve challenges which a BPO’s customer face. Talking with senior leadership at BPOs like Accenture, TCS, CST, firmed our idea.
Build Production Ready solution that supports
Business Continuity Plan
- Business to continue following the same process (workflow, rdp, citrix login, etc.) from the office laptop/desktop which is now at home.
Data Privacy and Security.
Keep the Agent productivity & monitoring intact
What it does :
Provides a single pane view to Agent, for all customer data on one screen, using Interactive Forms.
Agent to use Interactive Forms and deploy a bot via WLM technology on Remote Runner Machine, so Agent does not access the target application at all (if the use case demands). Alternatively, the agent can trigger the bot on a target application on a local machine as well.
Remote bot takes Agent’s input and perform actions on Target application (e.g. SAP as XenApp or XenDesktop) reside on Citrix machine.
AI Sense 2.0 (A2019) helps performing actions accurately even with screen Resolution changes.
Provides Real-time analysis of transactions/tickets processed by Agent in one single Dashboard – using Bot Insight
Remote bot validates PII data on the remote machine itself.
Only Non-PII data are sent back on the Agents Form view for further updates/validation.
Solution Reduces WLM Operational Overhead by 92% to 95%, creation of Work Queues/Device assignment/Work item creation etc as we have Automated the whole concept.
As an instance :
Agent = 500
Steps/Process = 5
Execution/Day = 100
Total Manual efforts is [(500) Work Queue creation + (500 Agent x 100 Runs x 5 steps) Work Items creation]
All of above is Automated.
How I built it:
We used latest web-based AA platform A2019.
We used Interactive Form feature to gives a single pan view for Agent.
We built a Custom Command pkg for WLM Work item creation.
We used few APIs to automate Work Queue creations & device association as soon as Agent executes the bot.
Solution helps executing bot on remote runner machine and provide interaction between bot & human to support any process need Human-bot collaboration.
BPO customers do not allow Citrix Agent to be install, so we used AI Sense 2.0 (AI in true sense) to perform Image base Automation accurately, even works on various machine resolutions.
Bot Insight for Realtime Dashboarding.
Challenges I ran into :
No inbuilt mechanism to execute a bot on Remote machine. (we achieved using WLM technology).
No default capability to let Human and Remote bot collaborate (exchanging information) with each other. (we used Interactive Form and WLM)
No inherent ability to automate WLM, so to reduce Operation Overhead creating WLM queues/workitems for thousands of Agents. (we automated it 92% to 95%, remaining 5% to 8% is one time Job)
Right approach to design Work Queue, Per Users or Per Steps. (we finally created User-based Work Queue for smooth and consistent results)
Right approach to design Remote Bot Creation/Execution flow. Because One WLM Queue can associate only One Bot, but Agent has to execute multiple Bots (workitems) to complete the whole process. (we created a Master Bot and conditioned it based on parameters passed from Agent (via workitems) and executes right Child Bot and also pass Child Bot output to Agent)
Citrix Agent is not allowed as a BPO practice, challenge was to automate target application (SAP) using IR/OCR and make it work even when screen resolution changes. (We used AI Sense 2.0)
Accomplishments that I'm proud of :
We could build Solution that is:
Most suitable for BPOs & Contact Centers, and support business Continuity.
Helps companies supporting/helping their Customers & society, in adverse time like COVID - 19.
Industry/domain agnostic. Be it Healthcare, Finance, Banking, Logistic, Supply chain etc, it works.
Saleable & scalable and support all aspects e.g. Security/Scalability/Performance/HA-DR etc
Help driving Sales and build Customer trust until an inbuilt capability comes in to A2019.
Fully Automated, reduce Manual/operation overhead.
Production Ready.
What I learned:
Business:
Support Business Continuity is the most important factor even in COVID like situation.
Forecasting problems and start building solutions to support business and the whole society.
Pick a right problem as there is always a way to solve the problems.
Agents get bogged down by juggling multiple screens and repetitive tasks. AHT and NPS suffer as a direct result. RPA can free the agent up to do more judgment based/non-repetitive work. Resolve calls faster and improve customer experience.
Remote agents need virtual setup and training. RPA gets them started faster. Reduce setup and training time.
Expensive to integrate systems for an omnichannel customer engagement experience. RPA reduces the time, effort and dollar investment to get you the same experience, faster.
Technical:
Better way of utilizing powerful web based Automation Anywhere platform A2019.
How helpful Custom Command Package & AI Senses features have been.
How individual component can be integrated to derive a solution to support Business Continuity.
What's next for BPO Work from Home Solution -
Considering wide usage of Excel, we would like to extend the solution using Excel Productivity plugin, by creating Forms in Excel, using Macros etc.
Enhance easiness by creating more Custom command pkgs, so one Command can server multiple actions.
To extend the solution for Contact Centers along with IVR/CTI integrations to support Self Service, Post Call transfer to Agent and Post call Complete, activities.
Built With
aisense
automationanywherea2019
botinsight
citrix
interactiveforms
sap
wlmapi
Try it out
github.com | BPO Work from Home Solution - A2019 | At home,there are no physical security measures that can be enforced, results in agents’ having access to PII Data which leads to security breach.This solution secures PII Data & increase Productivity | ['Ankit Thakkar'] | [] | ['aisense', 'automationanywherea2019', 'botinsight', 'citrix', 'interactiveforms', 'sap', 'wlmapi'] | 46 |
9,989 | https://devpost.com/software/smart-care-2-0 | Inspiration
As of May 31, 2020, 103,700 Americans have died from Covid-19. 62,000 doctors, nurses and health care providers have been infected and about 300 have died. Around the world, covid-19 has presented a number of challenges from absence of a vaccine to shortages of personal protective equipment (PPE). Healthcare providers are risking their lives to test and save others, but there is a safer method to test patients while protecting healthcare professionals.
What it does
Smart Care leverages EOSIO blockchain technology and smart contracts with facial recognition to automate the process of testing for Covid-19. To start, patients enter basic health screening questions and a computer screen with a webcam watches as they swab themselves. The patient must turn sideways to show a side profile. A good specimen is calculated after the swab has reached 50% of the diameter of the patient's head. To show that a good specimen has been collected the border around the screen changes from red to green. That information is then stored on the blockchain and sent to a doctor or other healthcare professional to notify them that a good specimen is collected at which time healthcare professionals can report the findings of the Covid-19 test.
How I built it
A lot of EOSIO smart contracts, tensorflow, opencv, blockchain.
Challenges I ran into
This is actually my first time using blockchain. I went from knowing close to nothing about blockchain to making my own blockchain with EOSIO. Understanding the concepts of blockchain proved to be the hardest part of the project. A
Accomplishments that I'm proud of
Coming up with and developing an application that could save thousands of lives.
Whats next for Smart Care
I would like for this to also be an app so that patients can pick up swabs from a safe location and swab themselves from their home or car without ever having to enter a medical facility, infecting themselves or others.
Built With
eosio
javascript
tensorflow
Try it out
github.com | Smart Care 2.0 | Leveraging blockchain and AI to safely test for Covid-19 and Influenza | [] | [] | ['eosio', 'javascript', 'tensorflow'] | 47 |
9,989 | https://devpost.com/software/chatbot-micro-coaching-for-employees-via-teams-slack | Remote work is a big change for most companies from the usual face to face business. The emotional toll, challenging environment, adoption of digital tools, prioritization, new way to lead people and self-management all make remote work a nightmare.
Remote work transition (and especially 100% work from home) can be tough for employees. It disrupts collaboration, makes people lonely, requires new processes and remote leadership style. We hope to support thousands of people whose performance suffers. We empower key people to manage themselves better, gain clarity, collaborate effectively, and develop as remote leaders.
Traditional coaching is a powerful tool that supports change. Panda’s micro-coaching solution brings it a step further by (a) making coaching scalable and affordable, and (b) allowing everyone to be aware of what’s going on in the company through knowledge sharing and data collection. All this made possible by utilizing both human expert-led coaching via text/Teams/Slack and AI chatbot tech.
We hope to support thousands of people whose performance suffers. We believe we can support them emotionally, help them become more productive, communicate better and generally solve personal and professional challenges.
50K EUR revenue last year. working with Universal Pictures (in LA), Bayer, Posti, Cramo, SAP and a few smaller firms like Futurice, Gofore, Vastuu Group. Won in Latvian HackForce COVID hackathon, recognized by Microsoft, Swedbank, Startup Wise Guys.
Expressed desire to pilot, looking for a project: Ramboll, Comcast, KONE, Finnair, UN, Stora Enso, S-Group, KPMG. Built chatbot product MVP. Built a podcast with following in Finland and sponsors. Built a network of freelance coaches we use for our projects.
Won 2 hackathons: DigiEduHack in the category "The future of work" and Sanako EdTech hackathon. The product is 1 year old, the company is 4 years old - pivoted.
The main challenge we have ran into was clarifying our value proposition. The problem is very diverse and people have different takes on it. We ended up with the conclusion that the management seems to care the most about the performance of the employees and the data about how their people are doing. On the tech side, chatbot integration with Teams has been challenging (especially authorization) but we solved it with Botkit.
Tech-wise, the solution is ready. What we need is to develop the content for the free chatbot trial package and nail the go-to-market strategy. That's why we worked hard on signing up organizations to test our solution: we will interview their people and then let them use the solution before releasing it out to the world. We been signing up test users and organizations who want to spread the word. It's been a huge unexpected success with people signing up from Google, United Nations, Cisco, Innova (Swedish innovation agency), City of Detroit, Solvay, Bluehealth Innovation Center (part of Microsoft), ITMO University, Tampere University, Sofigate, Rigilog, NurseBuddy, Redbridge, Dutch chamber of commerce and 30 more organizations!
Built With
amazon-web-services
express.js
jquery
node.js
react
Try it out
www.fibofy.com | Chatbot micro-coaching for employees via Teams/Slack | Chatbot micro-coaching for employees via Teams/Slack to empower key people, facilitate communities of practice and use data to diagnose processes and employee wellbeing. | ['Dima Syrotkin'] | [] | ['amazon-web-services', 'express.js', 'jquery', 'node.js', 'react'] | 48 |
9,989 | https://devpost.com/software/social-distancing-screen | Social Distancing Screen
Inspiration
I was inspired by World Hackathon Day for COVID19 Emergency Response.
What it does
It's a hologram camera 3d screen application. It can act like a toll-booth, and make suggestions like, "tap your phone" or "tap your card".
How I built it
I got a projection screen from Amazon and downloaded software from AIY Projects Cube with Google.
https://aiyprojects.withgoogle.com/vision/
Challenges I ran into
Like anything, I have to try and try again until I make a sale.
Accomplishments that I'm proud of
Well, it enables customers to interact with a safe Artificial Intelligence that could never be infected or dangerous.
What I learned
I learned that we can indeed, imagine and deploy solutions at the speed of thought. It's no longer a barrier, it's a portal or window... from the friendshipcube edge, to the 22core optical neural network, and into the hybrid cloud.
What's next for Social Distancing Screen
Sales and installations in a reliable partnership.
Built With
3d
camera
distancing
hologram
screen
social
Try it out
aiyprojects.withgoogle.com
www.developers.google.com
www.github.com | Social Distancing Screen | turning the sneeze guard cough screen into a hologram camera 3d portal. | ['https://www.bitchute.com/channel/friendshipcube/', 'Graeme Kilshaw'] | [] | ['3d', 'camera', 'distancing', 'hologram', 'screen', 'social'] | 49 |
9,989 | https://devpost.com/software/smart-tourist | Inspiration
COVID-19 pandemic has brought the world into a halt. People were forced to stay at home. But, there would be a time when people will go out after the pandemic is over.
But, travel in post-pandemic era would be harder. It requires longer hour, many health-related checking and a lot of documents.Therefore, a simpler way for checking in the post-pandemic travel would be crucial.
What it does
SMART helps travelers to go abroad safer in a post-pandemic era by utilizing blockchain and machine learning. Documents that would be needed for travel could be placed in blockchain and machine learning could be utilized to understand itinerary data.
How I built it
SMART is built using blockchain for cross distributed document-checking.
Challenges I ran into
Implement blockchain for cross distributed document-checking
Integrate machine learning into the project
Accomplishments that I'm proud of
What I learned
We learn how to use blockchain, deploy machine learning models, and integrate it into our application.
What's next for SMART
Smart contract development; testing; fine-tuning; improve application
Built With
amazon-web-services
blockchain
Try it out
smart.acacio.my.id | SMART | Blockchaih-Based Passport for Post-Pandemic Travelling | ['Tri Labs'] | [] | ['amazon-web-services', 'blockchain'] | 50 |
9,989 | https://devpost.com/software/mvhealthbot | Inspiration
Health care systems have to be improved and gain some cleverness in the area of big data management , analyses and predictions using well-trained AI models.
What it does
MvHealthBot is providing predictive health services by using LinearRegression AI models and NLP for identifying Covid19, diagnose diseases based on symptoms and alert the patient in case of disorders. MvHealthBot also simulates the process of fetching data from a public health API using a patient's medical ID and provides a diagnosis via the well trained AI model that has been built for the purposes of the app.
How I built it
I used python and google big query for the AI models creation and training. The models were published as APIs using google AI platform and cloud functions. Dialogflow has been used for the NLP part, in order to identify free text sentences context and intents. Google cloud functions have been used as the api layer. Node.js has been used for the backend api services. Fire base database and big query for data storage. Google cdn for content management.
Challenges I ran into
Model training and accuracy was a big challenge
Accomplishments that I'm proud of
MvHealthBot could be used in the health sector and help people get faster diagnosis and results
What I learned
To never give up
What's next for MvHealthBot
MvHealthBot is a prototype now. I would like to find funds and traction to extend it in order to be used in the health sector.
Built With
ai
angular.js
dialogflow
firebase
gcp
google-bigquery
ionic
node.js
python
Try it out
mvhealthbot-883e9.web.app | MvHealthBot | MvHealthBot is providing predictive health services by using LinearRegression AI models and NLP for identifying Covid19, diagnose diseases based on symptoms and alert the patient in case of disorders. | ['Maria Vasiliou'] | [] | ['ai', 'angular.js', 'dialogflow', 'firebase', 'gcp', 'google-bigquery', 'ionic', 'node.js', 'python'] | 51 |
9,989 | https://devpost.com/software/covi_fight | Inspiration
The virus has affected humanity in various ways, be it our economy, our freedom of movement, and the loss of loved ones. Then how do we live on, comfortably, and safely with this virus around?
Even after the lockdown is over, there is a massive possibility that traces of the virus will remain, and it can spread again.
We wanted to bring people back their mobility and keep them safe at the same time. We wanted people to know about their status while they leave their houses.
What it does
CoviFight alerts me about the risks of catching the virus if I have come in
contact with an infected person
within the past three weeks. It also informs the healthcare system accurately about the spread of infection.
CoviFight also generates a
map with hotspots for what places have virus traces
, so that people can prevent travelling at these places and authorities can sterilize or lockdown these places efficiently rather than having a complete lockdown of a country.
How we built it
We develop a three-tier app:
• A user's app
• A provider's app
• An official's portal.
While utilizing
Bluetooth and GPS
of your phone, CoviFight makes sure that the confidentiality of every individual is secured and can not be compromised. Data is encrypted using a secret key, and no one can view it without your permission. It only traces the past data of positively tested patients. This way, CoviFight also meets the
GDPR compliance.
By using
Geo-fencing and Machine Learning
, we predict your chances of catching the infection so that you can take preventive measures.
A provider's app for aggregation points like shops, restaurants, and public transport synchronizes with the nearby user app. This interface is the key to the detection of infection points, be it
a stationary workplace or a moving vehicle
. If McDonald's installed CoviFight and had an infected customer in the past 15 days, all the customers after the positive tested patient would get alerted, and hence the restaurant can be sterilized.
Only the medical system may update a person's status over the official's portal, and the
authenticity
of the app is maintained hence preventing
false positives
or self-reporting, which might lead to falsification of records.
So, with the help of our app, people can move around while being alerted about their status, stay away from the virus, and be free from the worry of their privacy maintenance at the same time.
Take a look at our demo by clicking
here
Challenges we ran into
To maintain the authenticity of the predictions and analysis, we were initially in a fix as to how to update a person's status as positive or negative. Then we decided to come up with a three-tier system, and we developed a Doc App or official's portal, which is only accessed by the medical system so that the authenticity is maintained.
No one else can manipulate the data.
Accomplishments that we're proud of
• We have made sure that the
privacy
of every individual is maintained and can not be compromised. The encryption algorithms meet the standards of the leading social networking apps existing in the market.
• CoviFight not only alerts people about their own risks but provides heatmaps of the traces of the virus too. CoviFight also shows what
specific restaurant or public transport( like a bus or a train) may be infected
precisely.
• We do not need to compare data between people, thus making
computation very cheap and exponentially faster and efficient.
Our Journey So Far
•
Winners( Runner up) in the #EUvsVirus, a Pan-European Hackathon
Organised by the European Innovation Council to counter COVID-19 pandemic with more than 9k participants and 2000 teams. We stood second in the Real time Communication and Prevention challenge.
•
Top 6 finalists of The Global Hack, by Garage48, April 2020
The Global Hack is a hackathon designed to share and rapidly develop ideas for urgently needed solutions in the face of the COVID-19 crisis, and to build resilience post-pandemic, with over 12k participants from 100+ countries. The team developed a mobile application solution for the containment and tracking of this virus. We were in the top 6 teams in the Crisis Response Track.
•
We were also in the Top 23 Student Innovators in COVID-19 SAMADHAN MHRD( Ministry of Human Resource Development, India) Mega Online Challenge
What we learned
It has been an enjoyable experience to work with people who have not even met each other before and still successfully develop this amazing app. We learned a lot through the hackathon, from interacting with the mentors and getting their guidance, to develop the app.
What's next for CoviFight
We plan
to get this deployed
at its earliest so that people may get their
safe mobility
back. We plan to deploy this on the Play Store and make a version for iOS as soon as we can.
We are also in touch with the Indian Government and we might be able to save lives in India also.
The necessities to continue the project:
• Approval from government authorities to implement and track data.
• Participation from Hospitals/government bodies to update the status of a patient so that system can generate realtime alerts and mark hotspots.
• Cloud resources to scale up the project. Currently limited by the free tier of cloud infrastructure.
The value of our solution after the crisis:
• This application can be used for any contagious disease management.
• It can be used in disaster management to understand the right victims and relief reaches all rightful beneficiaries( such as in the case of floods and storms).
• It can be used by Providers such as McDonald's and Public transport systems to implement targeted location-based marketing complying with data collection practices.
What we have done till now.
• Implemented masked identities for users to comply with GDPR and privacy requirements.
• Identification of hotspots in realtime based on the patient status update.
• Fixed bugs in the flow and to make it work E2E.
• Produced a product demo.
New Technology introduces
• Blockchain to manage user identification data(making it immutable), adding the security of ECC digital signature
• Moving from NoSQL mogoDB to a hybrid of BlockChain and GraphDB for better analysis and prediction while keeping the user's id secrete on the Graph
• Use of Kubernetes for creating multiple threads for gaining concurrency
•Adding caching mechanism to mobile devices to handle any kind of network failure.
Built With
firebase
google-directions
har
java
machine-learning
maps
python
Try it out
github.com
sidhantha.medium.com | CoviFight | A source - contact tracing app, CoviFight is a 3-tier solution that uses geo-fencing and machine learning to trace and track the COVID-19 spread | ['Shikhar Mathur', 'Anshuman Saboo', 'MANIT BASER', 'vishwas puri', 'Sidhantha Poddar', 'Yash Bhagat', 'Neil araujo', 'Navdeep Chawla'] | ['2nd Place Overall Winners', 'The Wolfram Award'] | ['firebase', 'google-directions', 'har', 'java', 'machine-learning', 'maps', 'python'] | 52 |
9,989 | https://devpost.com/software/messenger_assistant | First Aid Kit
Inspiration
Chronic diseases are defined broadly as conditions that last 1 year or more and require ongoing medical attention or limit activities of daily living or both. Chronic diseases such as heart disease, cancer, and diabetes are the leading causes of death and disability in the United States. They are also leading drivers of the nation’s $3.5 trillion in annual health care costs.
https://www.cdc.gov/chronicdisease/about/index.htm
What it does
dealing with an attack for chronic disease
How I built it
https://developers.facebook.com/
https://dialogflow.com/
Challenges I ran into
learn how to manage more than theology in one project Facebook & google cloud
Accomplishments that I'm proud of
that is my first chatbot
What I learned
“ANYONE WHO STOPS LEARNING IS OLD, WHETHER AT TWENTY OR EIGHTY.” —HENRY FORD
What's next for First Aid Kit
add more diseases to deal with
Built With
api
developers.facebook
dialogflow
google
webhooks
Try it out
www.facebook.com | First Aid Kit | trying to build a virtual assistant in messenger, and can assist in chronic disease | ['Abdelrazek Rizk'] | [] | ['api', 'developers.facebook', 'dialogflow', 'google', 'webhooks'] | 53 |
9,989 | https://devpost.com/software/internet-speed-analyzer | Inspiration
Once we started working from home, our daily video stand-up ran into internet speed issues. Teammates would complain about the internet speed and we had to turn off the camera or drop and join back. Most of the team faced issues while having screen share meetings because of a drop in audio and video quality.
Eventually, many of us realised that we need to switch to a different provider, upgrade our plan or change our meeting to a different time of the day. The solution was to have the speed data statistics over time and other analysis done regarding internet speed. Our project theme is
Employee Care & Productivity
.
What it does
Recommends if
current internet speed plan works
for the customer.
Suggest upgrade plan details from the
same provider.
Provides
top 5 alternate internet providers
and plans based on the customer’s zip code.
Checks if any
unknown devices
are stealing the wifi.
Reports the
number of devices connected
to wifi every hour.
Proposes the
best and worst time
for download and upload in 3 distinct shifts.
Notes the
highest and lowest
download and upload speed over a fixed period.
Summarizes the information in
tables, graphs and emails
to the customer in a readable format.
How we built it
Bot logs into customer’s internet provider account to capture speed plan and customer’s zip code details. For the botathon we have designed a UI for internet service provider website using google sites
Truefast
Configurable bot will perform the speed test by running every 30 minutes over a period of 1 to 3 days and capture the download and upload speed.
The captured date will be put in excel sheet for consolidation and calculation.
Based on the hourly average speed collected, bot will calculate the best download and upload speed in 3 distinct shifts and generate a graph (please check the email in the video).
Speed is deemed acceptable if the average speed is above 80% (configurable) of plan speed.
Bot emails the user if the internet speed is acceptable.
Bot will search for top 5 internet providers and plans based on the customer zip code. This is done by logging into
Broadband Search
website and searching the best internet providers for the extracted zipcode.
Scheduled bot will log into software “Who is on my wifi” and identify any unknown/suspicious devices is stealing the wifi and number of devices connected.
Reducing the number of devices connected to wifi will help in improving the speed. Bot will generate a graph on number data connected for the desired time interval.
Email the consolidated data to the customer after the scheduled processes are completed.
Challenges we ran into
Design solution on how to develop a configurable bot which can capture internet speed over 1 to 3 days.
We spent time in figuring out how to test the prototype without waiting for scheduled bot.
Explain the complete process and feature in less than 3 minutes in a video. It was a tough to decide on what features should we include and what feature should we drop from the timed video.
Applying excel formulas for calculation.
Accomplishments that we're proud of
Come up with an idea for a common problem and then add various features to it.
Started as a novice RPA developer for A2019 version but this botathon has encouraged us to explore more in Automation Anywhere.
Providing different options to the customer to make him aware of all possible issues and fixes.
Configurable design.
What we learned
Exploring the advance options of A2019 and Microsoft excel.
Botathon is a fun way to learn and give us liberty to implement ideas and explore the tool.
Decision making and problem solving.
What's next for Internet Speed Analyzer
In case the speed issues are found, request a router reset time to the customer.
Bot to reset the router from command prompt.
Check the internet latency.
Provide online tips on how to improve the internet speed.
Built With
aa
excel
google-sites
html
rpa
Try it out
drive.google.com
sites.google.com | Need for Speed | Covid has made us more reliant on internet speed. We are trying to fix the internet speed problem. Need for speed is RPA speed detective bot which helps to plan, recommend & analyse internet speed. | [] | [] | ['aa', 'excel', 'google-sites', 'html', 'rpa'] | 54 |
9,989 | https://devpost.com/software/chattering-space | WE ARE MAKING YOU AWARE OF COVID19
THIS COVID19 HAS BEEN SPREAD IN THE WHOLE WORLD
Inspiration
WE CAN DO THE PEOPLE AWARE OF COVID19 BY CREATING APP
What it does
IT AWARES THE PEOPLE HOW TO PROTECT YOURSELF FROM COVID19
How I built it
I BUILT IT USING BLOCK PROGRAMMING
Challenges I ran into
NOTHING
Accomplishments that I'm proud of
IT IS VERY CLEAR
What I learned
NOTHING IS IMPOSSIBLE
What's next for Chattering space
Built With
javascript
Try it out
studio.code.org | COMBAT WITH COVID19 | PREVENTION IS BETTER THAN CURE | ['Raman Goel'] | [] | ['javascript'] | 55 |
9,989 | https://devpost.com/software/germ-blocker | Thumbnail
Pulley System
The circuit
The box
Inspiration
My family gets
takeout
a lot. At our popular local pizza parlor, during the
COVID-19 lockdown
, employees typically stand outside rain or shine
delivering takeout food
to your car. The problem is that this isn't truly
contact-free
pick-up of food. We are still interacting with people who could be infected without knowing and surfaces that they have touched potentially increasing the
spread of the virus
.
What it does
Instead of handing the food/drinks for restaurant takeout, the people in the restaurant place the food/drinks in a box, then visit a link with a password
(like restaurant.com/pass1)
, making the box closed and secure with ultraviolet light killing all germs on the takeout containers. Then they send another password
(like pass2)
to a customer when they order takeout. When the customer comes, they go to the box and visit another link
(like restaurant.com/pass2)
, making the box open again. Then, they could pick up the food and go on their away. This process
reduces the risk of transmission
in takeout significantly and reduces the amount of people who need to be actively managing the pickup process, allowing restaurants to better allocate employees.
How I built it
I used an
Arduino MKR1010
, a step motor, a box, leds, breadboard, and a few other miscellaneous parts to build it. I programmed it using C++. The Arduino creates a web server, and when the user makes a get request to the server by visiting a link, the box opens or closes using the stop motor and a pulley system with threads.
Challenges I ran into
I was
limited
to the supplies that I had in my house so I created a pulley system powered a step motor to open and close the door. The threads often got
tangled up
when the motor was pulling them because I was only using 1 motor and it was opening and closing a big door. For a better prototype, I would create
automated hinges
to open and close the door.
Accomplishments that I'm proud of
I was able to open and close a physical box using
the internet
.
What I learned
I now know how to use a step motor with Arduino and create a web server with my Arduino.
What's next for Quarantine Pickup
I'd like to increase the quality of my prototype using better materials and redesign the open/close mechanism. I also can make a more secure, and user friendly website for customers to interact with, and restaurant employees to administer. I believe that as well as reducing contact during pickup this also has the potential to
increase efficiency
for a restaurant after lock-down since
less people
will need to manage the pick-up process.
Built With
arduino
c++
iot
Try it out
github.com | Quarantine Pickup | It uses a lockbox which can be opened or closed using the internet containing a UV light to drastically reduce the risk of transmission of germs and viruses during restaurant takeout pickup. | ['ram potham'] | ['Honorable Mention', 'Best Community Impact'] | ['arduino', 'c++', 'iot'] | 56 |
9,989 | https://devpost.com/software/healing-frequencies-mix | Electromagnetic frequency healing for coronavirus(covid-19)
Inspiration Audio frequencies mixing
What it does Helps healing of Covid-19.
How I built it Mixing audio frequencies using Mozilla and audacity to record.
Challenges I ran into Choosing the correct frequencies.
Accomplishments that I'm proud of The mix is high quality and all the frequencies can be heard. .
What I learned How to record in high quality sound without distortion of frequencies.
What's next for Healing frequencies mix I hope many people will find it useful to fight the infection.
Built With
audacity
mozilla
Try it out
audiomack.com | Electromagnetic frequency healing for coronavirus(covid-19) | Listen to this mix everyday to reduce the risk of coronavirus infection. | ['Radostin Peev'] | [] | ['audacity', 'mozilla'] | 57 |
9,989 | https://devpost.com/software/stay-home-stay-safe-self-protection | Regularly and thoroughly clean your hands with an alcohol-based hand rub or wash them with soap and water. Why? Washing your hands with soap and water or using alcohol-based hand rub kills viruses that may be on your hands.
Maintain at least 1 metre (3 feet) distance between yourself and others. Why? When someone coughs, sneezes, or speaks they spray small liquid droplets from their nose or mouth which may contain virus. If you are too close, you can breathe in the droplets, including the COVID-19 virus if the person has the disease.
Avoid going to crowded places. Why? Where people come together in crowds, you are more likely to come into close contact with someone that has COIVD-19 and it is more difficult to maintain physical distance of 1 metre (3 feet).
Avoid touching eyes, nose and mouth. Why? Hands touch many surfaces and can pick up viruses. Once contaminated, hands can transfer the virus to your eyes, nose or mouth. From there, the virus can enter your body and infect you.
Built With
advise
care | Stay home stay safe self protection | We need to maintain social distancing and stay with clean | ['Armeen Menon'] | [] | ['advise', 'care'] | 58 |
9,989 | https://devpost.com/software/myfacemaskapp | Prototype model 1 "Dany" pink opaque
Prototype model 1 "Dany" white opaque
AiRFace.it (App)
A new customizable, economic and ecological mask tailored to you
Millions of disposable masks are thrown out every day, which in addition to having a significant environmental impact on nature also have a high monetary expenditure.
To meet all these needs, the
AiRFace.it App
team has developed a project that allows the customization of the mask or the creation of transparent masks that can adapt to the features and therefore customizable by scanning the face in 3D.
This is
AiRFace.it App
, a mobile application that can be downloaded free on IOS and Android devices.
The scanning process is quick and easy: it happens through the use of the mobile phone camera.
In addition, the material used in the production of the masks, biodegradable and hypoallergenic allows a repeated use, being able to sterilize the washing at high temperatures .
The mask is therefore ergonomic and environmentally friendly, because you just need to change the filters.
The 3D model can also be printed from the comfort of the house without leaving. The advantage is that, being custom-built, the signs released by normal masks after hours of use will be reduced.
Considering the difficult and delicate situation we are experiencing,
AiRFace.it App
would ensure protection and prevention with zero impact on the environment and would meet individual needs.
It would be an optimal solution, without going out to buy it if you already have a 3D printer or otherwise we print and deliver directly to your home! The App is free as well as the availability of the various basic 3D models.
Ergonomic
My face mask with its 3D scanning process, allows you to create ergonomic masks suitable for every feature of your face. This custom adaptation will allow you to reduce the marks released by normal masks after hours of use.
3d Printer
The realization of the 3D masks allows anyone to create them independently.
In fact, a 3D printer and a mobile phone are enough to quickly create personalized templates based on the desired quantity.
Ecological
The material of these masks is absolutely ecological, a very important feature if you consider high consumption
daily, especially in
some sectors.
In fact, these masks can
be reused several times later
washing at high temperatures which allows sterilization.
Trasparent
One of the main features of AiRFace.it is transparency.
The idea of making these masks with a transparent material was born mainly from the awareness of the importance of lip reading for deaf people.
Privacy
For us your privacy comes first, that's why AiRFace.it complies with all Gdpr (
https://gdpr.eu
) regulations and no personal data will be transmitted.
The problem solved by the project
With AiRFace.it App we want to find the solution to the problem of the availability of personal protection devices for everyone, in fact thanks to this app anyone can print his mask, following our guidelines for the use of safe and biodegradable materials, with their own 3D printer,only if you are certificated member of our network to ensure the quality and safety of the mask produced according to all applicable regulations, so that you have a mask for you and your family that can last for all this complicated period that we are living.
The solution you bring to the table
AiRFace.it is installable for free on all iOS and Android devices that have compatibility requirements and in a simple automated way and can create your own 3D mask and send it directly to the 3d printer certificated
The impact of the solution on the crisis
The idea behind this project is to create a safe, cost-effective product that respects nature for us and future generations
The needs to continue the project
This project needs funds in order to create the best mask with the best materials and for this a significant investment in research and development in addition to wanting to make and print masks to those who do not have the opportunity to have their own 3D printer
The value of your post-crisis solutions
We believe a lot in this project because it is a valuable help to anyone who does not have the opportunity to always have a disposable mask and this mask can be reused even after this crisis (hopefully it ends as soon as possible) in any sector that needs personal protection devices
The AiR net blockchain
We are creating a network of certified makers to be able to print masks for doctors and nurses for free to thank them for their valuable help.
We are working with other startups to create a network of certified makers using the Ethereum blockchain to create smart contracts in order to be able to transparently verify the entire network.
We are creating a decentralized system that is based on blockchain eos to ensure the total transparency of certification of the materials used to print the masks.
Currently our team also collaborates in the creation of protective equipment for doctors and nurses to thank them for their difficult work.
Built With
blockchain
c#
html5
java
javascript
kotlin
objective-c
python
swift
Try it out
airface.it
bitbucket.org | AiRFace.it App | A new customizable and ecological mask tailored for you | ['Massimiliano Pizzola', 'Daniela Tabascio'] | [] | ['blockchain', 'c#', 'html5', 'java', 'javascript', 'kotlin', 'objective-c', 'python', 'swift'] | 59 |
9,989 | https://devpost.com/software/patient-health-history-record-system-f8iyxt | Screens Maps
Control of epidemics - Patient Control - Control of Vaccination Campaigns - Expert needs control by location - More reliable and secure data according to the new personal data protection law - More objective targeting of public health policy - Faster reaction to public health emergencies - Doctors with access to all health history and with more accurate patient information including emergency care - Patients with an updated and accessible health history when they need medical care - Public authorities using mathematical models to make projections with greater reliability - Patients using mathematical models to make projections and personalized predictions - Access to vulnerable population to technologies given only to people with private health insurance - Access to information of people using private health insurance by the government - People who have a private health plan and switch to the public health system without losing data - More accessible and reliable data than in DATA SUS - Data held by patients - Data released only for those patients who wish to access - Health History x Digital Health Record - Simplification of the database used today using data lake methodology
Built With
datalake
flutter
ionic
react
Try it out
github.com | Patient Health History Record System | We have developed a project for the public health area that aims to serve the poorest population. | ['Jose Alexandro Acha Gomes'] | [] | ['datalake', 'flutter', 'ionic', 'react'] | 60 |
9,989 | https://devpost.com/software/masked-ai-masks-detection-and-recognition | Platform Snapshot
Input Video
Model Processing
Model Processing
Output Video Saved
Output Video Snapshot
Output Video Snapshot
Output Video Snapshot
Output Video Snapshot
Output Video Snapshot
Output Video Snapshot
Inspiration
The total number of Coronavirus cases is 5,104,902 worldwide (Source: World o Meters). The cases are increasing day by day and the curve is not ready to flatten, that’s really sad!! Right now the virus is in the community-transmission stage and taking preventive measures is the only option to flatten the curve. Face Masks Are Crucial Now in the Battle Against COVID-19 to stop community-based transmission. But we are humans and lazy by nature. We are not used to wear masks when we go out in public places. One of the biggest challenges is “People not wearing masks at public places and violating the order issued by the government or local administration.” That is the main reason, we built this solution to monitor people in public places by Drones, CCTVs, IP cameras, etc, and detect people with or without face masks. Police and officials are working day and night but manual surveillance is not enough to identify people who are violating rules & regulations. Our objective was to create a solution that provides less human-based surveillance to detect people who are not using masks in public places. An automated AI system can reduce the manual investigations.
What it does
Masked AI is a real-time video analytics solution for human surveillance and face mask identification. Our main feature is to identify people with masks that are advised by the government. Our solution is easy to deploy in Drones and CCTVs to “see that really matters” in this pandemic situation of the Novel Coronavirus. It has the following features:
1. Human Detection
2. Face Masks Identification (N95, Surgical, and Cloth-based Masks)
3. Identify human with or without mask in real-time
4. Count people each second of the frame
5. Generate alarm to the local authority if not using a mask (Soon in video demo)
It runs entirely on the cloud and does detection in real-time with analysis using graphs.
How we built it
Our solution is built using the following major technologies:
1. Deep Learning and Computer Vision
2. Cloud Services (Azure in this case)
3. Microservices (Flask in this case)
4. JavaScript for the frontend features
5. Embedded technologies
I will be breaking the complete solution into the following steps:
1. Data Preparation:
We collected more than 1000 good quality images of multiple classes of face masks (N95, Surgical, Clothe-based masks). We then performed data-preprocessing and labeled all the images using labeling tools and generated PASCAL VOC and JSON after the labeling.
2. Model Preparation:
We used one of the famous deep learning-based object detection algorithm “YOLO V-3” for our task. Using darknet and Yolo v-3, we trained the model from scratch on 16GB RAM and Tesla K80 powered GPU machine. It took 10 hours to train the model. We saved the model for deploying our solution to the various platforms.
3. Deployment:
After training the model, we built the frontend which is totally client-based using JavaScript and microservice “Flask”. Rather than saving the input videos to our server, we are sending our AI to the client’s place and using Microsoft Azure for the deployment. We are having on-premise and cloud solutions prepared. At the moment, we are on a trail so we can’t provide the link URL.
After building the AI part and frontend, We integrated our solution to the IP and CCTV cameras available in our house and checked the performance of our solution. Our solution works in real-time on video footage with very good accuracy and performance.
Challenges we ran into
There are always a few challenges when you innovate something new. The biggest challenge is “The Novel Coronavirus” itself. For that reason, we can’t go outside the home for the hardware and embedded parts. We are working virtually to build innovative solutions but as of now, we are having very limited resources. We can’t go outside to buy hardware components or IP & CCTV cameras. One more challenge we faced was that we were not able to validate our solution with drones in the early days due to the lockdown but after taking permission from the officials that problem was not a deal anymore.
Accomplishments that we're proud of
Good work brings the appreciation and recognition. We have submitted our research paper in several conferences and international journals (Waiting for the publication). After developing the basic proof-of-concept, We went on to the local government officials and submitted our proposal for a trial to check our solution for better surveillance because the lockdown is near to be lifted. Our team is also participating in several hackathons and tech event virtually to showcase our work.
What we learned
Learning is a continuous process. We mainly work with the AI domain and not with the Drones. The most important thing about this project was “Learning new things”. We learned how to integrate “Masked AI” into Drones and deploy our solution to the cloud. We added embedded skills in our profile and now exploring more features on that part. The other learning part was to take our proof of concept to the local administration for trails. All these “Government Procedures” like writing Research Proposal, Meeting with the Officials, etc was for the first time and we learned several protocols to work with the government.
What's next for Masked AI: Masks Detection and Recognition
We are looking forward to collaborating with local administrative and the government to integrate our solution for drone-based surveillance (that’s currently in trend to monitor internal areas of the cities). Parallel, The improvement of model is the main priority and we are adding “Action Recognition” and “Object Detection” features in our existing solution for even robust and better solution so decision-makers can make ethical decisions as because surveillance using Deep Learning algorithms are always risky (bias and error in judgments).
Built With
azure
darknet
flask
google-cloud
javascript
nvidia
opencv
python
tensorflow
twilio
yolo | Masked AI: AI Solution for Face Mask Identification | Masked AI is a cloud-based AI solution for real-time surveillance that keeps an eye on the human who violates the rule by not using face masks in public places. | [] | [] | ['azure', 'darknet', 'flask', 'google-cloud', 'javascript', 'nvidia', 'opencv', 'python', 'tensorflow', 'twilio', 'yolo'] | 61 |
9,989 | https://devpost.com/software/covidcentral-u21txv | Landing Page
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Content Summarizer
Comparison of 4 Types of Content Summarizer
Text Insights
Preprocessing
Inspiration
This year has been really cruel to humanity.
Australia is being ravaged by the worst wildfires seen in decades, Kobe Bryant’s passing
, and now this pandemic due to
the Novel Coronavirus
originated from the Hubei province (Wuhan) of China. Coronavirus disease (COVID-19) is an infectious disease caused by a newly discovered coronavirus.
More than 3 million people
are affected by this deadly virus across the globe (Source: World O Meters). There have been around 249,014 deaths already and it’s counting. 100+ countries are affected by this virus so far. This is the biggest health crisis in the last many years.
Artificial Intelligence
has proved its usefulness in this time of crisis. The technology is one of the greatest soldiers the world could ever get in the fight against coronavirus. AI along with its subsets (Machine Learning) is leveraging significant innovation across several sectors and others as well to win against the pandemic. After
Anacode releases “The Covid-10 Public Media Dataset”
, we took this as an opportunity to use Natural Language Processing on those data composed of Articles. According to Anacode “It is a resource of over 40,000 online articles with full texts which were scraped from online media in the timespan since January 2020, focussed mainly on the non-medical aspects of COVID-19. The data will be updated weekly”. Anacode further says “We are sharing this dataset to help the data community explore the non-medical impacts of Covid-19, especially in terms of the social, political, economic, and technological dimensions. We also hope that this dataset will encourage more work on information-related issues such as disinformation, rumors, and fake news that shape the global response to the situation.”
Our team leveraged the power of NLP and Deep Learning and built
“CovidCentral”
, a PaaS
(Platform as a Service)
. We believe our solution can help media people, researchers, content creators, and everyone else who is reading and writing articles or any kind of content related to the COVID-19.
What it does
Our tagline says
“Stay central with NLP powered text analytics for COVID-19”. CovidCentral is one of its kind NLP driven platform for fast and accurate insights. It generates a summary and provides analytics of large amounts of social and editorial content related to COVID-19. STAY CENTRAL INSHORTS.
It does three things:
1.
CovidCentral platform can help to
understand large contexts related to COVID-19 in a matter of minutes.
Through the platform, Get actionable insights from hundreds of thousands of lines of texts in minutes. It generates an automated summary of large contents and provides word-by-word analytics of the texts from total word count to the meaning of each word. The user can either enter an URL to summarize and getting insights or enter the complete content directly into the platform.
2.
The large content of text data is hard to analyze. It is very difficult to analyze the large content of texts. CovidCentral can help people to get insights within minutes. Manual analysis of texts leads to a number of hours. Media people, researchers, or anyone who is having the internet can access our platform and
get the insights related to the COVID-19.
3.
Humans are lazy in nature and people want to save time. This platform can generate content’s summary within minutes via a single URL. CovidCentral uses NLP and Deep Learning technologies to provide an automated summary of texts. Very helpful for getting short facts related to the COVID-19.
Why Use CovidCentral?
1. Fast
2. Ease of Use (User-friendly)
3. High Accuracy
4. Secure (No content or data will be saved in the server rather we are sending NLP to you at the frontend.)
How we built it
We built CovidCentral using AI technologies, Cloud technologies, and web technologies. This platform uses NLP as a major technique and leverages several other tools and techniques. The major technologies are:
a. Core concept:
NLP (Spacy, Sumy, Gensim, NLTK)
b. Programming Languages:
Python and JavaScript
c. Web Technologies: HTML, CSS, Bootstrap, jQuery ( JS)
d. Database and related tools:
SQLITE3 and Firebase
(Google's mobile platform)
e. Cloud:
AWS
Below are the steps that will give you a high-level overview of the solution:
1. Data Collection and Preparation:
CovidCentral is built on mainly using “Covid-19 Public Media Dataset” by Anacode. A dataset for exploring the non-medical impacts of Covid-19. It is a resource of over 40,000 online articles with full texts related to COVID-19. The heart of this dataset are online articles in text form. The data is continuously scraped from a range of more than 20 high-impact blogs and news websites. There are 5 topic areas - general, business, finance, tech, and science.
Once we got the data, the next step is obviously “Text Preprocessing”. There are 3 main components of text preprocessing:
(a) Tokenization (b) Normalization (c) Noise Removal.
Tokenization
is a step that splits longer strings of text into smaller pieces, or tokens. Larger chunks of text can be tokenized into sentences, sentences can be tokenized into words, etc. Further processing is generally performed after a piece of text has been appropriately tokenized.
After tokenization, we performed
“Normalization”
because, before further processing, the text needs to be normalized. Normalization generally refers to a series of related tasks meant to put all text on a level playing field: converting all text to the same case (upper or lower), removing punctuation, converting numbers to their word equivalents, and so on. Normalization puts all words on equal footing and allows processing to proceed uniformly.
In the last step of our Text preprocessing, we performed
“Noise Removal”
. Noise removal is about removing characters digits and pieces of text that can interfere with your text analysis. Noise removal is one of the most essential text preprocessing steps.
2. Model Development:
We have used several NLP libraries and frameworks like Spacy, Sumy, Gensim, and NLTK. Apart from having a custom model, we are also using pre-trained models for the tasks. The basic workflow of creating our COVID related NLP based summarizer or analytics engine is like this: Text Preprocessing (remove stopwords, punctuation). Frequency table of words/Word Frequency Distribution – how many times each word appears in the document Score each sentence depending on the words it contains and the frequency table. Build a summary or text analytics engine by joining every sentence above a certain score limit.
3. Interface:
CovidCentral is a responsive platform that supports both i.e. Mobile and web. The frontend is built using web technologies like HTML, CSS, Bootstrap, JavaScript (TypeScript, and jQuery in this case). We have used a few libraries for validation and authentication.
On the backend part, it uses python microservice “Flask” for integrating the NLP models, SQLITE3 for handling the database, and Firebase for authentication and keeping records from the User forms.
4. Deployment:
After successfully integrating backend and frontend into a platform, we deployed CovidCentral on the cloud. It runs 24*7 on the cloud. We deployed our solution on
Amazon Web Services (AWS)
and use an EC-2 instance as a system configuration.
Challenges we ran into
Right now, the biggest challenge is “The Novel Coronavirus”. We are taking this as a challenge and not as an opportunity. Our team is working on several verticles whether it is medical imaging, surveillance, bioinformatics and CovidCentral to fight with this virus.
There were a few major challenges:
Time constraint
was a big challenge because we had very little time to develop this but we still pulled CovidCentral in this short span of time. The data which has more than 40K articles are pretty much messy, so
we got difficulties dealing with messy data
in the beginning but after learning how to handle that kind of data, we eliminated that challenge to some extent. We also got challenges while deploying our solution to the cloud but managed somehow to do that and still testing our platform and making it robust.
Accomplishments that we're proud of
Propelled by the modern technological innovations, data is to this century what oil was to the previous one. Today, our world is parachuted by the gathering and dissemination of huge amounts of data. In fact, the International Data Corporation (IDC) projects that the total amount of digital data circulating annually around the world would sprout from 4.4 zettabytes in 2013 to hit 180 zettabytes in 2025. That’s a lot of data!
With such a big amount of data circulating in the digital space, there is a need to develop machine learning algorithms that
can automatically shorten longer texts and deliver accurate summaries that can fluently pass the intended messages.
Furthermore, applying text summarization reduces reading time,
accelerates the process of researching for information, and increases the amount of information that can fit in an area.
We are proud of the development of CovidCentral and to make it Open Source so anyone can use it for free on any kind of device to get important facts related only to COVID-19.
What we learned
Learning is a continuous process of life, the pinnacle of the attitude and vision of the universe. I tell my young and dynamic team (Sneha and Supriya) to keep on learning every day.
In this lockdown situation, we are not able to meet each other but we learned how to work virtually in this kind of situation. Online meeting tools like Zoom in our case, GitHub, Slack, etc helped all of us in our team to collaborate and share our codes with each other.
We also
strengthen our skills in NLP (BERT, Spacy, NLTK, etc)
and how to integrate our models to the front-end for end-users. We spent a lot of time on the interface so people can use it and don’t get bored. From design to deployment, there were many things that helped us improve our skills technically.
We learn many things around us day by day. Since we are born, we learn many things, and going forward, we will add more relevant features by learning new concepts in our platform.
What's next for CovidCentral
We are adding features like “Fake News Detector” to spam fake news related to the COVID-19 very soon on our platform. CovidCentral’s aim is to help content creators, media people, researchers, etc to
only read that matters the most
in a quick time. APIs to be released soon so anyone who wants to add these features in their existing workflow or website can do it so they won’t need to use our platform rather they can just use our APIs.
We are also in discussion with
some text analytics companies to collaborate
and bring an even more feasible, robust, and accessible solution. In the near future, we will make CovidCentral an NLP powered text analytics platform in general for all kinds of text analytics for anyone, free to use from anywhere on any kind of devices (Mobile, Web, Tablet, etc).
Built With
amazon-web-services
bootstrap
css
firebase
flask
html
javascript
natural-language-processing
nltk
python
sqlite
Try it out
covidcentral.herokuapp.com | CovidCentral | CovidCentral is one of its kind NLP driven platform for fast and accurate insights. It generates a summary and provides analytics of large amounts of social and editorial content related to COVID-19. | [] | [] | ['amazon-web-services', 'bootstrap', 'css', 'firebase', 'flask', 'html', 'javascript', 'natural-language-processing', 'nltk', 'python', 'sqlite'] | 62 |
9,989 | https://devpost.com/software/covnatic-covid-19-ai-diagnosis-platform | Landing Page
Login Page
Segmentation of Infected Areas in a CT Scan
Check Suspects using Unique Identification Number (New Suspect)
Check Suspects using Unique Identification Number (Old Suspect)
Suspect Data Entry
COVID-19 Suspect Detector
Upload Chest X-ray
Result: COVID-19 Negative
Upload CT Scan
Result: Suspected COVID-19
Realtime Dashboard
Realtime Dashboard
Realtime Dashboard
View all the Suspects (Keep and track the progress of suspects)
Suspect Details View
Automated Segmentation of the infected areas inside CT Scans caused by Novel Coronavirus
Process flow of locating the affected areas
U-net (VGG weights) architecture for locating the affected areas
Segmentation Results
Detected COVID-19 Positive
Detected Normal
Detected COVID-19 Positive
Detected COVID-19 Positive
GIF
Located infected areas inside lungs caused by the Novel Coronavirus
Endorsement from Govt. Of Telengana, Hyderabad, India
Endorsement from Govt. Of Telengana, Hyderabad, India
Generate Report: COVID-19 Possibility
Generate Report: Normal Case
Generated PDF Report
Inspiration
The total number of Coronavirus cases is
2,661,506 worldwide
(Source: World o Meters). The cases are increasing day by day and the curve is not ready to flatten, that’s really sad!! Right now the virus is in the community-transmission stage and rapid testing is the only option to battle with the virus. McMarvin took this opportunity as a challenge and built AI Solution to provide a tool to our doctors. McMarvin is a DeepTech startup in medical artificial intelligence using AI technologies to develop tools for better patient care, quality control, health management, and scientific research.
There is a current epidemic in the world due to the Novel Coronavirus and here
there are limited testing kits for RT-PCR and Lab testing
. There have been reports that kits are showing variations in their results and false positives are heavily increasing.
Early detection using Chest CT can be an alternative to detect the COVID-19 suspects.
For this reason, our team worked day and night to develop an application which can help radiologist and doctors by automatically detect and locate the infected areas inside the lungs using medical scan i.e. chest CT scans.
The inspirations are as below:
1. Limited kit-based testings due to limited resources
2. RT-PCR is not as much as accurate in many countries (recently in India)
3. RT-PCR test can’t exactly locate the infections inside the lungs
AI-based medical imaging screening assessment is seen as one of the promising techniques that might lift some of the heavyweights of the doctors’ shoulders.
What it does
Our COVID-19 AI diagnosis platform is a fully secured cloud based application to detect COVID-19 patients using chest X-ray and CT Scans. Our solution has a centralized Database (like a mini-EHR) for Corona suspects and patients. Each and every record will be saved in the database (hospital wise).
Following are the features of our product:
Artificial Intelligence to screen suspects using CT Scans and Chest X-Rays.
AI-based detection and
segmentation & localization of infected areas inside the lungs
in chest CT.
Smart Analytics Dashboard
(Hospital Wise) to view all the updated screening details.
Centralized database (only for COVID-19 suspects) to
keep the record of suspects and track their progress
after every time they get screened.
PDF Reports,
DICOM Supports
, Guidelines, Documentation, Customer Support, etc.
Fully secured platform
(Both On-Premise and Cloud)
with the privacy policy under healthcare data guidelines.
Get Report within Seconds
Our main objective is to provide a research-oriented tool to alleviate the pressure from doctors and assist them using AI-enabled smart analytics platform so they can
“SAVE TIME”
and
“SAVE LIVES”
in the critical stages (Stage-3 or 4).
Followings are the benefits:
1. Real-world data on risks and benefits:
The use of routinely collected data from suspect/patient allows assessment of the benefits and risks of different medical treatments, as well as the relative effectiveness of medicines in the real world.
2. Studies can be carried out quickly:
Studies based on real-world data (RWD) are faster to conduct than randomized controlled trials (RCTs). The Novel Coronavirus infected patients’ data will help in the research and upcoming such outbreak in the future.
3. Speed and Time:
One of the major advantages of the AI-system is speed. More conventional methods can take longer to process due to the increase in demand. However, with the AI application, radiologists can identify and prioritize the suspects.
How we built it
Our solution is built using the following major technologies:
1. Deep Learning and Computer Vision
2. Cloud Services (Azure in this case)
3. Microservices (Flask in this case)
4. DESKTOP GUIs like Tkinter
5. Docker and Kubernetes
6. JavaScript for the frontend features
7. DICOM APIs
I will be breaking the complete solution into the following steps:
1. Data Preparation:
We collected more than 2000 medical scans i.e. chest CT and X-rays of 500+ COVID-19 suspects around the European countries and from open source radiology data platform. We then performed validation and labeling of CT findings with the help of advisors and domain experts who are doctors with 20+ experience. You can get more information in team section on our site. After carefully data-preprocessing and labeling, we moved to model preparation.
2. Model Development:
We built several algorithms for testing our model. We started with CNN for classifier and checked the score in different metrics because creating a COVID-19 classifier is not an easy task because of variations that can cause bias while giving the results. We then used U-net for segmentation and got a very impressive accuracy and got a good IoU metrics score. For the detection of COVID-19 suspects, we have used a CNN architecture and for segmentation we have used U-net architecture. We have achieved 94% accuracy on training dataset and 89.4% on test data. For false positive and other metrics, please go through our files.
3. Deployment:
After training the model and validating with our doctors, we prepared our solutions in two different formats i.e. cloud-based solution and on-premise solution. We are using EC-2 instance on AWS for our cloud-based solution.
Our platform will only help and not replace the healthcare professionals so they can make quick decisions in critical situations.
Challenges we ran into
There are always a few challenges when you innovate something new. The biggest challenge is “The Novel Coronavirus” itself.
One of the challenge is “Validated data” from different demographics and CT machines.
Due to the lockdown in the country, we are not able to meet and discuss it with several other radiologists. We are working virtually to build innovative solutions but as of now, we are having very limited resources.
Accomplishments that we're proud of
We are in regular touch with the State Government (Telangana, Hyderabad Government). Our team presented the project to the Health Minister Office and helping them in stage-3 and 4.
Following accomplishments we are proud of:
1. 1 Patent (IP) filled
2. 2 research paper
3. Partnership with several startups
4. In touch with several doctors who are working with COVID-19 patients. Also discussing with Research Institutes for R&D
What we learned
Learning is a continuous process. Our team learnt
"the art of working in lockdown"
. We worked virtually to develop this application to help our government and people. The other learning part was to take our proof of concept to the local administration for trails. All these “Government Procedures” like writing Research Proposal, Meeting with the Officials, etc was for the first time and we learned several protocols to work with the government.
What's next for M-VIC19: McMarvin Vision Imaging for COVID19
Our research is still going on and our solution is now endorsed by
the Health Ministry of Telangana
. We have presented our project to
the government of Telangana for a clinical trail
. So the next thing is that we are looking for trail with hospitals and research Institutes. On the solution side, we are adding more labeled data under the supervision of Doctors who are working with COVID-19 patients in India. Features like
Bio-metric verification, Trigger mechanism to send notification to patients and command room
, etc are under consideration. There is always scope of improvement and AI is the technology which learns on top of data. Overall, we are dedicated to take this solution into real world production for our doctors or CT and X-rays manufacturers so they can use it to fight with the deadly virus.
Built With
amazon-web-services
flask
google-cloud
javascript
keras
nvidia
opencv
python
sqlite
tensorflow
Try it out
m-vic19.com | M-VIC19: McMarvin Vision Imaging for COVID19 | M-VIC19 is an AI Diagnosis platform is to help hospitals screen suspects and automatically locate the infected areas inside the lungs caused by the Novel Coronavirus using chest radiographs. | [] | ['1st Place Overall Winners', 'Third Place - Donation to cause or non-profit organization involved in fighting the COVID crisis'] | ['amazon-web-services', 'flask', 'google-cloud', 'javascript', 'keras', 'nvidia', 'opencv', 'python', 'sqlite', 'tensorflow'] | 63 |
9,989 | https://devpost.com/software/ar-mask-line-for-covid-19 | line3
line2
line1
line4
Inspiration
When I go out in the morning, there is a line in front of the drugstore that people want masks. I always think it's really dangerous.
What it does
Using smartphone or Hololens, people can put their avatar in the line instead of themselves. So every time, everyone can keep social distance.
How I built it
Using unity with ARCore, I developed the application. See the tutorial of Azure Spatial Anchors (
https://docs.microsoft.com/en-us/azure/spatial-anchors/
). It will help you.
Challenges I ran into
It was difficult to share the avatar with others. However, I implemented using Azure Spatial Anchors. So easy and cool.
Accomplishments that I'm proud of
It can reduce COVID-19 !!!!!
What I learned
The fundamental of AR and the method to share AR objects. Microsoft Learn was really useful.
What's next for AR Mask Line for COVID-19
Build Hololens version and improve quality of design. For now, users can put only one character. I improve that users can create their own original character.
Built With
android
azure
c#
ios
microsoft-hololens
unity
web
Try it out
github.com | AR Mask Line for COVID-19 | During the time, the line in front of drag store is dangerous. You can put your AR avatar instead of yourself and share the avatar with others using Azure Spatial Anchors. | ['Shun Ishii'] | ['Best Use of Microsoft Azure'] | ['android', 'azure', 'c#', 'ios', 'microsoft-hololens', 'unity', 'web'] | 64 |
9,989 | https://devpost.com/software/handsfree-basin | Inspiration
This is pandemic condition. Be a part of mission against a coronavirus
What it does
It will be used in public spaces or slum areas or army/medical camps. Also, useful for isolated people
How I built it
Using arduino, hardware components and sensors, etc and coding
Challenges I ran into
Lack of components or accessories
Accomplishments that I'm proud of
Really helpful
What I learned
Proud to be an Indian, use my knowledge for Nation
What's next for Handsfree basin
Helping others..
Built With
knob
machine-learning
mechanical-parts-like-spring
pedal
Try it out
drive.google.com
github.com | Defender (Handsfree basin and Corona Rakshak) | Restricted the transmission of Coronavirus from infected person to healthy person through surface. | [] | [] | ['knob', 'machine-learning', 'mechanical-parts-like-spring', 'pedal'] | 65 |
9,989 | https://devpost.com/software/auto-health-monitoring-system | Inspiration
We all know that doctors, healthcare workers are trying to do their best to fight against COVID-19.
Being an engineer we also have some responsibility to our society. So in this horrible situation we have to step forward to do something for the society and help people to fight against COVID-19.
Problem statement
As per the guidelines of World Health Organization (WHO), “Home quarantine / Quarantine in non-health care settings is intended for anyone who believes they have been exposed to COVID-19 and are required to be home quarantined to prevent community transmission”.
Now it is not possible to monitor so many people who have mild symptoms or who believes that they have been exposed to COVID-19 during their ‘Home Quarantine’ period. So, if we have an auto monitoring system by which a patient’s health condition can be monitored or recorded by which doctors can come to a decision that if the patient is required to be hospitalize for further treatment or they are safe in other case.
What I have built
What I have planned to build is having a portable or wearable device that patient will be wearing throughout the day. The device will be consisting of sensors to sense the body temperature, blood pressure, heartbeat or other certain parameters. The sensors will generate data and then that sensor data will be captured by a node mcu. We will develop an application that will receive the data sent by node mcu and store it into a database. After consecutive 14 days, our application will make 14 days statistics and plot a graph based on daily recorded data and that will be sent to local hospital or to the doctor. The statistical data or the graph will be able to identify that whether the patient health condition is critical or not or he/she is required to be hospitalized or not for further treatment.
How I built it
First I have planned to make a portable device and connect it to the various sensors to sense the data from human body. Then connect it with a programmable device like node mcu. Now I will build an android app that can receive the data generated by the sensors and sent from the node mcu and store the data into a database. And using Machine Learning models the app will run a productive analysis on the data to predict the patient's health condition.
Challenges I ran into
The availability of the necessary products in the market is a big challange to me.
And also not having a team support is a big problem.
Accomplishments that I'm proud of
I recently grabbed the 6th place on the innovatieve idea competition Eradicate, organized by JIS college of engineering, Kalyani, in association with IIC.
What I learned
Programming and automations using devices like node mcu, developing android app and implementing ML models on it etc.
What's next for Auto health monitoring system
We can further upgrade the functionality of the application where after storing the consecutive 14 day’s data, it can be able to run a predictive analysis on the dataset stored on the database and then it will automatically predict whether the patient health is so critical as to be hospitalized or not.
Built With
android
kotline
nodemcu
sensors
tensorflow | Auto health monitoring system | Auto health monitoring system for people during home Quarantine those who believes they have been exposed to COVID-19 and prediction for the patient's health condition using AI | ['Sandipan Das'] | [] | ['android', 'kotline', 'nodemcu', 'sensors', 'tensorflow'] | 66 |
9,989 | https://devpost.com/software/kishanyojna | kishanyojna
kishanyojna
What it does
How I built it
Challenges I ran into
Accomplishments that I'm proud of
What I learned
What's next for kishanyojna
Built With
former
Try it out
www.kishanyojna.com | kishanyojna | kishanyojna, krishi, dipaartament govt, | ['https://www.youtube.com/channel/UC6FaCGMKmCoY2AXmSjI77_Q', 'PRABHU DEVA'] | [] | ['former'] | 67 |
9,989 | https://devpost.com/software/spark-k6txdh | Inspiration
- Needed a place to track and plan our projects.
- Frustrated over apps that are specialized to do only one thing resulting in having to keep many tabs/apps open at the same time.
- Saw a need for an all-in-one productivity app.
- Believed it had the potential to increase the productivity of those affected by COVID-19.
What it does
- Features: Calendar, Tasks, Team Administration, Project Tracking, Messages, Meetings and Zoom Integration, Discussion Board
- A cumulative productivity app that puts all the apps you need into one
- Assists teams and organizations by improving productivity and tracking the progress of projects
- Highlights team collaboration with SparkRooms to coordinate team members
How we built it
- Written in HTML/CSS/JS, Python
- Written in Visual Studio Code
- Utilized Travis for continuous deployment and autonomous configuration
- Divide and Conquer - Frontend, Backend
- Git, VSCode Live Share, and Discord
Challenges we ran into
- Responsiveness & Mobile compatibility
- Rendering iframes on the dashboard
- Saving arbitrary user data within Firestore
- Git collisions: Committing changes to the same lines at the same time
Accomplishments that we're proud of
- Firebase for hosting, database, and authentication
- Fully functional login system with Google Oauth 2.0 Authentication
- Dashboard to render iframes to show lots of content in a single page
- Travis CI/CD
- Lots of backend and Javascript to process website
What's next for Spark
- Expand Spark for function enterprise and educational usage
- Increase responsiveness of site to enable mobile usage
- Create a way to send personal messages to team members
- Create more tools for users eg. a personal File Storage Method
Built With
bootstrap
css3
flask
fullcalendar
google-cloud
html5
javascript
jquery
node.js
python
travis-ci
Try it out
sparkapp.cf
github.com
docs.google.com | Spark | An intuitive and empowering all-in-one productivity application. | ['Raadwan Masum', 'Rohan Juneja', 'Safin Singh', 'Aadit Gupta'] | ['Wolfram Honorable Mention', 'Track Winner: Work & Economy'] | ['bootstrap', 'css3', 'flask', 'fullcalendar', 'google-cloud', 'html5', 'javascript', 'jquery', 'node.js', 'python', 'travis-ci'] | 68 |
9,990 | https://devpost.com/software/personal-and-family-coping-with-covid-19-in-the-global-south | If you are interested in how you and your family are dealing with the COVID-19 crisis, please complete the following questionnaire
We are a team of Rwandan scientists of the Mental Health and Behaviour Research Group at the University of Rwanda. Momentarily, the COVID-19 crisis is causing relatively few direct health victims, but it is causing already a very real economic disaster in countries that have very few reserves to absorb such shocks. Reading reports from the Global North on how COVID-19 negatively impacts on people's lives, we expect similar negative outcomes to happen in the Global South. As researchers from a Global South University, we felt that we had a responsibility to act and try and help the citizens from the Global South, as we have a unique knowledge about what solutions can be useful in our contexts.
We have developed an online interactive questionnaire that asks people in the Global South how they and their families are coping with the COVID-19 crisis and we give personalized feedback and advice on how they can deal with the situation. We ask people a number of questions (using standardized validated scales) on how COVID-19 impacts on their daily life, their overall well-being, their social situation, their relationship (in case they are in a relationship), parenting issues (in case they have children), their alcohol use and their level of worry. Importantly, we compare their scores to other people in their country and give personalized feedback on these issues (disclaimer; the psycho-educational materials are developed and validated by a group of Rwandan scientists, and are now being programmed).
We constructed the questionnaire firstly by deciding what indicators we felt were relevant and after looked up standardized validated surveys, with a preference for those previously used in the Global South. After, using authoritative psycho-social advice resources from WHO, MHPPS and others, combined with expertise available in our local research team, we developed the psycho-educational advice materials and developed the system of how we present to offer feedback in a personalized way.
The key to the whole project is to be able to provide personalized feedback to the people who complete the questionnaire. We did not want our research to be extractive, but on the contrary offer real and direct help to people who might need it. We believe that the strength of our health messaging is the fact that people themselves solicit for the feedback and advice, as it is they who freely decide to take the online questionnaire. Research has convincingly showed that people are much more receptive to advice when they look for it, compared to when it is pushed on to them. Secondly, getting personalized feedback touches people more deeply, as they cannot so easily ignore the feedback. For example, reading that you use 'much more/more/about the same/less/much less' alcohol compared to other people from your gender group in your country, might be eye-opening. This effect is further strengthened by visually displaying this information as you belonging to a 20% interval group. We again have good reasons to believe that this leads to higher receptiveness for our (very hands-on) psycho-educational messages. Interestingly, we are capable of measuring the impact of our intervention (i.e., the psycho-educational messages), through people who complete the questionnaire multiple times.
A major challenge was to find the right platform that would allow us to give the personalized feedback and advice. We struggled to find a good system, until we started collaborating with the University of Antwerp, Belgium who were so generous to share with us the platform they developed for a different COVID-19 related questionnaire. These technical challenges set us back for almost two weeks.
We are very ambitious about this project. We started reaching out through our networks to have research teams support the project and use the questionnaire and feedback/advice messages in other Global South countries. Recently, we came in contact with the University of Antwerp who allowed us to use the platform they developed and our now assisting us in reaching out to twenty more Global South Countries. Through our own networks, we intend to reach out to even more countries.
In conclusion, we hope that this project will actively help people coping with aggression control, alcohol control and other issues during this COVID-19 crisis. We also want to demonstrate how South Universities contribute to solutions for the Global South. This entire project is running without any funding whatsoever for the time being, but it is very strongly alive through the engagement and efforts of so many of our colleagues in other Global South countries.
Built With
online
questionnaire
Try it out
www.icpcovid.com | Personal and family coping with COVID-19 in the Global South | We are interested in how people and families in the Global South are coping with the COVID19 crisis and to give people tailored personalized feedback and advice on how they can deal with the situation | ['Bob Colebunders', 'Epaphrodite NSABIMANA', 'Prof. Vincent Sezibera', 'Stefan Jansen', 'Ruth Byukusenge'] | [] | ['online', 'questionnaire'] | 0 |
9,990 | https://devpost.com/software/coronator | Inspiration
I am mechanical engineer and teacher for Methods of construction and design on a technical highschool.
First time I became aware of the danger of virus / pandemia was during my military service – I was educated as a ABC – soldier (Atomar – Biological – Chemical weapons).
I am sad about all the victims, those who are suffering and that we are facing the biggest challange since 2nd World War to protect our society , social life and economics.
Since we have the global lockdown – the only solutions to avoid exponatial growths of infections is to seperate people (social distancing with all negative impacts on social and economical life) and create a high standard on hygienic behaviour.
What it does
Goal is to kill the virus or get resistant.
Today , killing the virus is only based on medical solutions (vacintion or medication for people who are suffering)
Another method to fight the virus , ist o avoid that he is entering the mouth / nose / eyes channel. So it is crucial to seperate the face from contact with fingers and aerosols which are contaminated with virus particles and avoid that air with contaminated aerosols will be breath in.
The actual used masks (self-made or FFP x – mask) are limited in protection . They have leakages or are only usable for a short time.
How I built it
I created a mask , with the following working principle - it will kill the virus in a 3 – Step Filter System:
Step: Filter by an Filament / Electrostatical part (realized in the Prototyp with a Swiffer to clean your home from Dust)
Step : Destroy the Virus in heated part (Mini electrical oven) (Temperature up to 60°C are enough ) this is the « Hell-fire » for the Virus (realized in the prototype with a cigarette lightner inside the car)
The remaining air will be guide through a washer and get in contact with water / alcohol aequeus solution (realized in the prototype with a self-build part with 3-D-printer and a glass for Marmelade)
It`s like a «mechanical vacination »
Each part of the CORONATOR Mask is cleanable, desinfectable and re-usable. It`s personalized. It protects yourself and all other people around you.
To make it «Hipp» or « Trendy » it can also added with earphones to connect with a cellphone which includes a Corona Tracking App. If an infectet person is near to you , you get a warning sound.
A protection glass or whole transparent hull for your eyes can be integrated
After the crisis it can also help people who are suffering on allergical reaction in spring time on pollen.
The principle is shown in the sketches / draft. The design has to be optimized
Locking forward to work in this "EUvsVIRUS" community to bring our Knowledge together and fight down this Virus with our swarm intelligence.
I love to go for social dance and really pissed off to be seperated from my friends and dance partners……
So, let`s go and kill the virus ! I am proud to be a part of this Campaign.
Next challange is to find Partners and companies to realize this product.
Built With
3-d-printer
solidworks | CORONATOR | Advanced Public Respirator MASK // 3 - Step Mouth / Nose Filter System : Filament/Electrostatical seperation - Heat sterilization - Liquid washer / Desinfection * Personalized *Re – Usable*Cleanable | ['Detlef Juesten'] | [] | ['3-d-printer', 'solidworks'] | 1 |
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