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9,978 | https://devpost.com/software/temani-self-quarrantine-buddy-ug4pvd | Inspiration, an always there for you buddy
What it does to chat and accompanying you to stay sane and even help lower your anxiety level through guided mindful breathing call
How we built it with rush and empathy, haha. By zoom meeting with user to get the user journey map and also zoom brainstroming sessions and quick prototyping
Challenges we ran into doing it while still doing daily duties during quarrantine
Accomplishments that we're proud of to build the first prototype in time
What we learned that we can actually do something about this devastating time
What's next for TEMANI self quarrantine buddy
To develop it further
Built With
adobe-illustrator
marvel
Try it out
marvelapp.com | TEMANI self quarrantine buddy | Your self quarrantine buddy | ['prima singgih', 'Nadia Mahatmi'] | [] | ['adobe-illustrator', 'marvel'] | 34 |
9,978 | https://devpost.com/software/my-covidential-diary | Case life cycle
First submission page
Example of the multiple choice questions
Submission for multiple choice questions
End stage
Personalised email sent
Personalised diary entry received by user via their email
My Inspiration
Hello, my name is Jessica Levett.
I have created an application called My Covidential Diary using the PEGA Platform V 8.4.
It's inspired by a woman I have studied and read about for much of my life,
Anne Frank
.
She lived through one of the worlds most traumatic experiences and still wrote and documented her diary.
I wanted to make writing a diary as simple as clicking a button.
So that anyone can document their current experiences.
All entry's are sent personalised to your email and are customised by your answers.
I hope people can find comfort in creating their diary just as others have done before :)
I have entered my application into this
Amazing Hackathon
, in the hope that I can help spread awareness of positive change and using the resources around me avaliable to do so. And to show what girls can do 💪
I wish everyone in the world the best and have a great day!
What it does
It generates a personalised diary entry based on your multiple choice answers to help document your day.
It includes questions inspired by Anne Frank's diary and the types of things she wrote about.
I have also used questions given to me from a few years ago from my councillor which helped me come to terms with how I was feeling at the time.
The language is also not too complicated and provides straight forward answers for those with additional needs.
My younger brother who has severe learning disabilities has trialled the application and submitted his diary entry.
I really tried to make my application suitable and helpful to as many people as possible because writing is an amazing vice for those going through tough times.
How I built it
I built it using PEGA 8.4 in the App and Dev studio.
Challenges I ran into
I wanted to create this application as best as possible in the time frame to ensure functionality.
I'm all about perseverance, pushing through obstacles and finding solutions.
So I'm really happy that I was able to achieve my submitted product.
Accomplishments that I'm proud of
I am proud that it works and that it has already helped some people who have tested it out.
For example I have a teenage sister and offered her to test my app after a stressful day of online exams.
She told me how relieved she felt opening up to herself with the questions and now she has something to show herself in the future about how she has dealt with the current situation.
That really made my day because that was the goal for this application.
What I learned
That I can help people by using my skills with the PEGA system.
What's next for My Covidential Diary
I'm sure once people have grasped the concept they will want to try it, so to make it deployable would be a dream come true. The goal is to help people using PEGA resources and I really do feel that my application does that.
Built With
pega | My Covidential Diary | Document your Covidential Diary with just the click of a button. | ['Jessica Levett'] | [] | ['pega'] | 35 |
9,978 | https://devpost.com/software/bubbguard | Inspiration
Oh dear. Where to begin about this unseen demise due to violence and not because of the Covid19 virus itself? Where we all wanted to rest and meditate during #StayTheFuckHome, my team and I are terribly busier with the unprecedented rise of domestic violence ("KDRT" in Indonesia) and online harassment ("KD" in Indonesia).
We knew it has been around for long but because Covid19 forces the society, from the under-aged to seniors to be a netizen. Some are digital natives, some are immigrants. And so, offline harassment do follow and move online, more than ever.
UN has addressed this issue of how "homes that feel like prison" to survivors of domestic violence and for government to pay attention to
the unseen impacts of Covid19 in mental health.
We decided to create a response idea around April and with this competition, to test this out whether it's actually needed in this world, a guardian of the online galaxy!
What it does
We're a
a) protected online bulletin for "harassers profiles" (just like a WANTED bulletin).
b) highly-regulated online community for netizens to share information and protect each other for advise
c) AI chat-bot to auto-chat harassers - we fight your fight to give the user their peace of mind
How we built it
We built it by using the framework react native, to make UI and becked nodeJS.
We store our database using firebase.
This is how we're going to receive data, analyse, design and implement our app to be smarter:
a) collect user data
b) we will analyze the data and sort it out to make AI logic,
c) after the AI logic we will test connect it to the social media API every user wants security
d) the security we offer, e.g.: scan the communication (mostly text windows) and report warnings (Green / Yellow / Red).
Challenges we ran into
Awareness, market fit, and gender-tailored approaches. What we needed to first understand is even though our survey mentioned 100% female gets the harassment, males do too, and it's
more difficult for them to open up and talk to someone, or even to seek professional help
because of the male ego and toxic masculinity.
Our results showed top priority lies on how to architect our solution based female netizens' pain points.
There's a reluctance during market fit questionnaire, but we managed to steer clear on the demand where under-aged users are more vulnerable, therefore it's the parents' duties to purchase our product, and later to focus on our secondary target market which are female users with smaller spending power aged 20-27YO.
Accomplishments that we're proud of
Firstly, we've gotten more than 500 people to join our polling in Indonesia! That means something is really up. And knowing that we're here to do truly protect our current and next generation for there'll be continuous child traffic, sexual molestation and 'catcalling' that moves online, and it will never, ever end.
It's our first step to validate our idea, during the process of this development, so we're a bit more confident and really wanting to know what GIT judges think.
What we learned
This journey has been nothing but a blessing! Wow. We did learn a lot of things as we compared respondents from two countries (UK and Indonesia) for our survey.
For starters, even though that it's a basic necessity and purchasing a peace of mind, some are still reluctant to purchase a sort of 'antivirus for online harassment' product (without the price point being mentioned). Some even answered _ "don't have the money to spend"_ which to us, it means that their own safety isn't their priority, and they'd place their spending power on other things that is deemed their own priority.
However, we're sure that our product is needed in the near future, with the data provided by our respondents, the average score of 7.6/10 feels very distressed when they're faced with online harassment, mainly sexual, it's our duty to communicate importance of self-vigilance and daily protection because a user will spend more time online than in the offline world in the age to come.
What's next for BubbGuard
We're in the process of designing a specific survey for males in the future, where our results showed top priority lies on the female users. We don't want to leave anyone behind because under-aged users are non-gender specific, we're here to protect the children and tweens, at the very least.
Development-wise, we're going to continue collecting data, and hire linguists to read, deconstruct and feed our AI better. We target to receive 500,000 case reports within 6 months in order for us to create a basic beta AI-Chatbot and start to defend our users.
Built With
react-native
Try it out
drive.google.com | BubbGuard | Your Smart Insurance for Online Harassment - leave it to us to deal with your dick pics, child molester, online stalkers and sexual harassers and unknown users and notify you for prevention. | ['Elizabeth Raisa "Rice"', 'Zul Fandi', 'Ghea Moeis', "Roro Mega Cahyaning 'Azmi Riyandani"] | [] | ['react-native'] | 36 |
9,978 | https://devpost.com/software/flick-off | You call it being alone in our quarantine, we call it enjoying our flick off.
Inspiration
The main thing that inspires us is that we found in this pandemic time, we see every day hundreds of posts on social media that indicate how much pain on being far from our friends and families which actually could make some Suicide thoughts.
We could see now the importance of social media that plays a great rule for these bad ideas of the isolation so why do not we show the positive side of social media? That's what our application shows. It shows how much our life is important.
The great experience from this time, making friends for doing what we love and taking awesome experience in what we wanted and want to do, building a connection between us, building our identities, and knowing ourselves better which would make us control our bad habits and develop the good ones in this isolation. These things would make us forget the isolation and make us connected to others even if someone tested positive for the virus, he could enjoy his isolation, too.
What it does
As we know that everyone isolates themselves from people due to covid19 and this application helps them to spend their lifetime in quarantine with getting the advantage from it.
As they will reduce any mental risk may happen due to the long duration of the isolation so, our application is known by "stay far but not alone".
Through the categories of the application everyone could follow up your Physical health: as the doctors follow up with patients who infected by corona and give updates, medicine and advice to people (not infected/ infected) to protect themselves and in their health and there and follow up the changes body and detect if there is something weird they could contact a doctor from home through the other category to minimize the numbers that go to hospitals unless it needs that. -- Mental Health (online diagnosis): This comprises of following up the user daily mental health and their feeling, make meditation and relaxing courses.
They will find in the same category thousands of rooms that contain every place we used to go to before quarantine such as
Activates/workouts and following up with coach,
-Interactive education platform (1-courses in all fields, 2- soft skills courses with a guide),
Relax category that includes: relaxing music/song, nature calm (Scenes/sound of nature), express yourself by recoding), a music section, artists….. Etc, reading motivation quotes, express your feelings and updates by writing in notes),
-chat with the software,
assess category: include corporate wellbeing in many fields.
–Goals room: talking about your health, career, finance, personal passion, and friends and with a reminder to check this goal,
optional room: help people to make their rooms even if they are friends, family, work, and provided with a high efficient voice and video call. All these categories are connected to a reminder that friends you with everything you add it to interests. The professional's mentors and volunteers will benefit as they will be paid from the advertisings or funds as they stopped their work already
Finally, they could contact with their families despite the isolation which will strength family, friends and human relations and make them more connected to each other that would make them feel happy and forget the isolation for being together and gain skill, experience and all things that they want to gain from your place.
How we built it
We built our application with flutter and dart programing language
As it comes to apply the application and writing the code, then we knew that there a lot of available programming languages, but the most useful one is using flutter as it uses Dart programming language which was introduced by Google in 2011 and Dart syntax is easy to understand for JavaScript or Java developers as it supports most of the object-oriented concepts. it gives many abilities to get high output from the application and provide us with unlimited features that we can get the benefit from it as JavaScript is one of the languages that we studied and it can be downloaded at all kinds of phones e.g. iPhone or android. Also, it has no limit when writing it, not like the MIT app inventor.
Challenges we ran into
While working on the main challenge which is the negative side of the isolation or quarantine that can affect people and put their mental life at risk and in some cases, social distancing may have had the opposite effect of bringing families, groups, and individual's closer together social and to make people not feel alone during their quarantine and reduce the crisis the caused by the isolation. Many ideas hailed to our minds but the problem lied in collecting all these ideas at only one idea that represents the virtual community that allows people to continue their daily activities and without quarantine prevention and also without going outside to keep them safe. We worked on each small idea to make it important detail at the big idea.
we tried hard to make people get the advantage of the quarantine via diverse ways like attending an online course of sticking with daily workouts and there are a lot of people whose work has been crashed because of the pandemic. Therefore, we tried to compile all the essential needs for the majority of people like the need for a professional monitor or the need of getting a reputation or advertising for the monitor himself/herself. The experts in teaching anything like doctors, workouts trainer, teachers, and professors can continue their work via our application. This will create an unforgettable experience for all the users and will leave a huge impact in their life special in the astronauts and the scientist because the isolation is like a daily routine to them and they need to take a breath from their hard life to avoid the risk of depression, self-harm, self-neglecting behavior, and decline in cognitive functioning and it can be solved by our app.
Accomplishments that we're proud of
our Accomplishments that we're proud is to turn all this suffering to a journey of relaxation in our application and make an unforgettable experience for all the users and will leave a huge impact in there to avoid the risk of depression, self-harm, self-neglecting behavior, and decline in cognitive functioning and it can be solved by our app.
As it makes you achieve the advantage of the quarantine via diverse ways like attending an online course of sticking with daily workouts and there are a lot of people whose work has been crashed because of the pandemic. Therefore, we tried to compile all the essential needs for the majority of people like the need for a professional monitor or the need of getting a reputation or advertising for the monitor himself/herself. The experts in teaching anything like doctors, workouts trainer, teachers, and professors can continue their work via our application and provide them to get any skills, experience, soft skills, knowledge, information, relaxing, good health, improve your relations, identify goals …etc.
Do, you imagine owning the good side of the world on your phone? Yes, I imagine and we try hard to turn it to true
What we learned
In trial to impede the propagate of COVID-19, many people around the world have betrothed in protract companionable insulation over the past several months. Connecting families and strengthening family relations through the activities that they could do together in their quarantine is provided by our application. There are some tips we could take from astronauts as they live a long time isolated in space that could help people to overcome their mental health problems through filling their time.
Through our journey with that project, we could tell that it was a kind of filling our boring isolation with valuable projects, and of course, there are many talents and experiences that we took in this journey. Firstly our experience in research has grown so much and we learned that as a general guideline, the more that what you did was something others couldn't have done (i.e., it required your exceptional aptitude, not simply "more hands'), the "better" it is.
Secondly the importance of being connected with others such as our coaches, family, teachers, and friends. communication intends to talk so you are unmistakably comprehended. To tune in, and question to comprehend. Effectively tune in, get on non-verbal signals. Recognize, talk about, at that point work to determine struggle. Families will not only be connected to each other but they will be connected to others as they will do their interests and activities together.
Finally, the importance of social media and computer science in our life because we learned how to code the application and design it and it was an awesome and incredible experience in our isolation. The capacity to share photographs, assessments, occasions, and so forth continuously has changed the manner in which we live and, additionally, the manner in which we work together. Retailers who utilize web-based life as an essential piece of their showcasing methodology typically observe quantifiable results.1 But the way to effective internet based life is to not regard it as an additional limb however to treat it with a similar consideration, regard, and consideration you do the entirety of your advertising endeavors, and The Computer Science Field is one of the quickest developing and most lucrative professional ways on the planet. Be that as it may, there is lessening flexibility of instructors and understudies intrigued by Computer Science. This is to a great extent dependent on how presented understudies are to innovation and assets just as whether the understudies are being urged to investigate the universe of software engineering.
Our mission is to give them opportunities to all young and older people the ability to take care of their health and mental health, learn, and enjoy days of quarantine.
What's next for Flick Off
As usual, we have to know what our plans for the solution are. We are planning on conducting an online survey to see how people would react to such an idea. What people can think about it and what the necessary precautions that we would take. Maybe some people can have second thoughts on the organizing and the structure of the idea. It will be taken into consideration that we will collect data from our neighborhood and the people we have access to which will let us know the actual data from a considerable sample in real life.
Also, it is important to consider searching more about the physiological states and rules we have to follow in structuring the deep details in the application. We will search for what is the best way mentally to monitor this application.
The next step is to search about how the different classes and the diverse ages became affected by the COVID – 19 to make sure we are offering better service. We will know more about how to divide the customers and what their needs, lifestyles, jobs, and interests are.
Flick off will face many updates based on upcoming data about the customers and how to offer the best service for them.
Built With
dart
flutter
software
Try it out
drive.google.com
drive.google.com | Flick Off | Flick Off is multi-function.It is mainly focused on more than one category includes Mental/Physical health,Courses,Activities/Workouts,Relaxation room,Chat with software,Goals and Motivational quotes. | ['Rwaa Alabsawi', 'Mai Mahmoud', 'Manar Tarek', 'Dina Salith', 'Gehad Hosary'] | [] | ['dart', 'flutter', 'software'] | 37 |
9,978 | https://devpost.com/software/helper-helper | top of home page
middle of home page
bottom of home page
Essential worker request form
'Help a helper" page, where volunteers can go to see needs in their area
The form through which volunteers can contact helpers who's requests they want to fulfill, accessed through the "fulfill request" button
Inspiration
Helper helper is a prototype created for the Girls in Tech virtual hackathon in response to the COVID-19 crisis. It's purpose is to alleviate the burden on essential workers by matching them with volunteers/donors who respond to their specific requests. The motivation for creating this direct connection is two-fold:
Many essential workers don't qualify for economic/non-profit support during this time, and are increasingly at risk of burn-out and health related concerns due to the nature of their work.
Many non-essential workers are trying to find ways to volunteer and contribute during the COVID-19 crisis, but most volunteer organizations are not accepting volunteers. Additionally, many people are concerned about where their money goes when they contribute to non-profits and this allows them to contribute directly towards specific needs for essential workers.
What it does
The application works by allowing essential workers to submit requests through the "Make a Request" page. After their essential worker status is confirmed, their request will appear on the "Help a Helper" page where volunteers can respond to the request via a message that will go to the essential worker's email address.
How I built it
Helper Helper was developed as prototype using React as the front-end framework with a "mock" server to display fictional requests. It would be further developed by connecting with a back-end server that stores requests as well as user information so that essential workers would not have to re-authenticate with each request.
Challenges I ran into
One of the difficulties faced with this application is preventing spam as well as making sure that individuals are "who they say they are". If this project is to be developed beyond a prototype and scale up, it will be necessary to have a means of verifying identity as well as using a spam filter such as reCaptcha.
Accomplishments that I'm proud of
I'm really proud of the styling on the forms for both the "Post a Request" and the "Message a Helper" pages. I'd never worked with the Formik library before so it felt like an accomplishment to alter the styling to fit the overall theme of the website.
What I learned
I really learned the importance of being able to integrate a back-end into customized web projects. I've had experience with connecting front-end apps with existing APIs, but this project inspired me to start learning Java so that I can write my own APIs.
What's next for Helper Helper
In order to scale up this project, several components would have to be added:
The user should be able to sort volunteer requests by location or select only remote jobs
Verification processes would need to have some level of automation
A back-end would need to be built out to manage requests and user information
Built With
css3
formik
html5
javascript
react
Try it out
github.com | Helper Helper | Helper Helper empowers volunteers to connect directly with essential workers in their area or remotely to help meet their needs during the COVID-19 crisis. | ['Kira Woods'] | [] | ['css3', 'formik', 'html5', 'javascript', 'react'] | 38 |
9,978 | https://devpost.com/software/crowdassist | SPA
SPA
SPA
CrowdAssist
Introduction
CrowdAsist is crowdfunding app to assist public health workers and suppport local businesses.
Purpose & Motivation
As we ramp up efforts to combat the spread of COVID-19 among valuable populations and provide finanacial assistance to those most in need, We donate to public health and social services agencies to fill workspace gaps.
Another of the consequences of the pandemic is the the economic devastation of the restrictions and quarantine period. Small businesses which rely on local community for a majority of thier sales will get help from volunteers to incentivize customers to buy goods online or in-person as the restrictions are lifted.
How this application works
It's a single page funding application, users can check details and donate or volunteer.
How this application was developed
It was developed using HTML/CSS, JavaScript, jQuery, scss. The payment/donation request feature is not yet implemented.
How to use this application
The application is to assist pulic health workers in front line of the global pandemic and to save local economies through donation to centers and businesses.
Difficulties & Challenges you faced
Bad electricity and low resources, donation payment method.
Go-to-Market Evaluation
Built With
bootstrap
css3
html5
javascript
jquery
node.js
scss
Try it out
github.com
ndkkqueenie.github.io | CrowdAssist | CrowdAsist is crowdfunding app to assist public health workers and suppport local businesses. | ['Queendalin Nduka'] | [] | ['bootstrap', 'css3', 'html5', 'javascript', 'jquery', 'node.js', 'scss'] | 39 |
9,978 | https://devpost.com/software/covid-test-o6yk0r | Inspiration
The number of
Covid19
cases is increasing so fast, because of the process of adding and defining the priority of each patient takes lot of time for the hospitals workers.
So this app will help them to add new the patient easly and the app will define the priority of the new patient.
What it does
Covid-Test
is an app that helps the hospitals workers to :
Show all the patient who has been added and their results didn’t come out yet.
Add new patient (anyone who has symptoms) and define his priority automatically.
Give the result of a patient tests (positive or negative).
show the patients who has
Covid19
.
How I built it
I used Flutter and Dart and Firebase to create this app in Android Studio!
Flutter doc and Firebase docs were a great help for me during the process of making this apa, also stack overFlow.
I used the PRIORITIES FOR TESTING PATIENTS WITH SUSPECTED COVID-19 INFECTION pdf provided by CDC to define the priority of each patient.
Challenges we ran into
I worked solo so i had to do everything by myself from the coding to the design part which i had no experience with so i tried to make it the simplest that i can.Also , I’m completly new to Flutter, Dart and Firebase so i had to learn more during the develping process.
Accomplishments that I'm proud of
I’m proud that i was able to create
Covid-Test
in this limited time.
What I learned
I learned more about flutter, dart and how to make good UI also i earned a lot about the Firebase console, Firebase products such as Cloud Firestore.
What's next for CovidTest
In the future, the app will have more options such as specifying if the user is a doctor or a nurse, the doctor can make notes about a specific patient situation and if he's recoverd or yet, and the nurse will recive a notification when the doctor add a note.
Built With
android-studio
dart
firebase
flutter
Try it out
github.com | Covid-Test | Covid19 tests patient | ['Ilham Reb'] | [] | ['android-studio', 'dart', 'firebase', 'flutter'] | 40 |
9,978 | https://devpost.com/software/covid-testing-locations | COVID-19 Testing Locations Finder.
Website to help people find nearest COVID-19 testing locations in the U.S. Simply select a state and enter your zip code to see testing locations near you.
I believe testing for COVID-19 is one of the most important things we can be doing right now. By testing resources and funding can be allocated as needed and hotspots for the virus can be detected early before an outbreak becomes unmanageable.
I hope my site can be a quick and easy way for someone to get the information and locations of testing locations near them in what may be a stressful time.
Link to website:
Find Testing Locations
This prototype site is for the Girls in Tech 2020 Hackathon.
Link to Hackathon
Features
This website allows people to conveniently access all the information needed to find the best testing site for their needs.
All a person has to do is select their state and enter their zip code.
Tools used
Build using C# and asp.net this application is hosted on Azure and calls 2 APIS
By building on Azure and will be able to expand and scale the website as needed.
Main Tools used
Azure cloud platform
API to get locations information:
COVID-19 API Testing Locations
API to get distance between zip codes:
Zip Code Distance
Challenges + What I learned
I found setting up the APIs to be most challenging as there wasn't a lot of documentation on how they work.
I spend a lot of time trying to find a good way to get the distance from a person to each testing location, unfortunately, I wasn't able to find anything that worked well or that didn't cost money. I settled on an API that gets the distance base on zip code but I would like to find something more accurate than that.
I learned a lot of little things throughout the project, this tech stack is still new to me, so I found myself stuck and needed to figure out how to work a solution. I also gained more knowledge of how to build Azure applications as well as how to work with and call different types of APIs.
Future Improvements
Add more states
Add more information about availability (days of the week and times each location is open)
Find a more accurate way to get distance from locations (sorting by zip code distance isn't a great estimate and current API being used limits calls)
Built With
apis
asp.net
c#
css
postman
Try it out
find-covid-testing-locations.azurewebsites.net | COVID-Testing-Locations | Website to help people find nearest COVID-19 testing locations. | ['Chyanne Haugen'] | [] | ['apis', 'asp.net', 'c#', 'css', 'postman'] | 41 |
9,978 | https://devpost.com/software/overcome | Inspiration
Covid19 problems
What it does
Create checkpoints
How I built it
React
Challenges I ran into
I never had published a project before
Accomplishments that I'm proud of
To work on the same project during a whole week
What I learned
My first react project
What's next for Overcome
Backend
ZIP code for other countries
Built With
flask
react
Try it out
github.com | Overcome | To help small business and donate points to hospitals | ['th3exorcist luci'] | [] | ['flask', 'react'] | 42 |
9,978 | https://devpost.com/software/contactless-covid-test-personalized-diet-suggestions-ai | Contactless COVID-19 Test Web App
App screen
Cough test
Respiratory test
Heart BPM and Respiratory Rate
Patient's medical details
Patient Result
Doctor's tab
Doctor replay to patient
general query chatbot
Inspiration
COVIID-19, the most exasperating topic spoken all across the Globe. We are all aware of this virus and its consequences. People get afraid due to the symptoms of COVID-19 and crowd at the hospitals which is currently very
difficult for the frontline workers to manage and take tests for all
. It is very important to know who actually needs to be tested. Hence people who are at a higher risk are only needed to be targeted.
Also it has been found that the
best medicine
for COVID-19 is
improving our immunity
. So, a
personalized diet suggestions for encountering COVID
would improve each and every one to win this battle against COVID.
Lot of
fake news about COVID
are spreading on social Media where people get confused on what to do. So it would be better if they get answers for their questions on what to do and what not to do.
How this application works
A simple Web App integrated with AI systems is implemented which helps the Doctor to diagnose the patients without visiting them. The Web App contains the following:
Contactless Test
Personalized Diet Suggestions for COVID-19
Chatbot
Contactless Test
A risk score is generated by the AI system which ranges from 1 - 100. It is this score that helps to prioritize the patients. Higher the risk score, higher is the importance given to that patient.
The Contactless test consists of the following:
Dry Cough Severity
The user is made to cough and its sound is recorded and sent to the Database. The Convolutional Neural Networks reads the input frequencies using the spectrogram images and predicts the dry cough rate based on how severe the dry cough is. If its a normal cough or a wet cough, the dry cough rate would be less. This test contributes to the risk sore.
Heart BPM | Respiratory Test
The user is made to take deep breath in and out for 15 - 20 seconds which is recorded by the camera. The Convolutional Neural Networks read the input image sequence and generates the respiratory rate and bpm. Based on these values, the AI system keeps a track to the risk score.
Queries
Well framed queries are questioned where the user need to answer. Eg:
"What is your Current Location?", Do you have any travel history in the past 30 days?, Are you able to smell odorous items?
etc..,
The AI system itself finds how severe COVID is affected in the user's current location and if its high, then accordingly it gets tracked to the risk score. In the similar way all other questions are also tracked by the AI system to the risk score.
Finally the AI System generates a risk score for the patient.
Now Doctors can login the Web App at any time and can diagnose all the patients based on these tests. Finally the Doctor writes the prescription/remarks for the patient.This is sent to the patient's mail.
As a prioritization is made, highly risky patients are diagnosed first. The user can follow the guidelines as prescribed by the Doctor in the Prescription.
AI Personalized Diet Suggestions for COVID-19
The users need to answer the questions which helps to calculate the magnesium, zinc,fat,water,sugar and vitamin content in their body. This is sent to the database. Random Forest Algorithm is used to determine what kind of diet is needed for that person in order to improve the immune system.
Chatbot
Its an RNN based chatbot. People can ask any kind of queries regarding COVID. All the data's and facts about COVID were fetched from official websites like WHO. So people can ask like "How to go to a grocery shop?", "Should I use masks at home?", "Are kids affected equally ?" etc...,
How this application was developed
The COVID Test, Chatbot, Diet Suggestions were created using the tensorflow and keras frameworks. (Python)
The UI was entirely made using HTML, CSS, Javascript.
A MYSQL Database was made locally using phpMyAdmin.
The AI system, UI and MYSQL was integrated using flask.
How to use this application
The packages mentioned in the Github link of the project has to be installed. Once the Database is created as listed in Github, run "python app.py" in the Command Prompt which opens the Web App.
Difficulties & Challenges we faced
Detection of the ROIs(Region Of Interest) in our face to calculate the BPM and Respiratory Rate.
Converting the sound data into spectrogram images to train the CNN.
Accomplishments that we're proud of
We have used AI technology that can simplify the jobs by concentrating more on the highly risky people rather than taking tests at hospitals for everyone. This prioritization focuses on the early identification and protection of vulnerable patients and health care workers.
Apart from that, a diet recommendation and Chatbot is made to effectively make an ALL-IN-ONE helpful website for the people.
What we learned
An in depth analysis was made to understand and evaluate the Nutrient levels in the patient and recommend them a suitable diet.
Working in Face Detection and finding the ROIs.
Go-to-Market Evaluation
The Database has to be pushed into the server. Once the Web App is hosted, it can be assessed by all.
What's next for Contactless Covid Test & Personalized Diet Suggestions - AI
Working to create a pulse oximeter which uses the image of our finger to detect our oxygen saturation levels in our blood. This is very useful for COVID test as it has found that most of the COVID patients have SO2 less than 90%.
Built With
css
flask
html
javascript
keras
python
sql
tensorflow
Try it out
github.com | Contactless Covid Test & Personalized Diet Suggestions - AI | Web App integrated with AI systems to support Contactless COVID19 Test, Patient Prioritization, Personalized Diet Suggestions and COVID Chatbot. | ['Dharineesh Ram T P', 'keerthana ravikumar', 'Karthikeyan Thanigai', 'Kaviya R'] | [] | ['css', 'flask', 'html', 'javascript', 'keras', 'python', 'sql', 'tensorflow'] | 43 |
9,978 | https://devpost.com/software/automatic-alert-hopitals-medical-shops | map
What it does
This project helps front-line workers to totally engage in supplying medications to the nearby hospitals. A database is maintained manually by the by hospital staff and when medications decrease they use the chatbot to share the querry and get relevalent answers. They can also see the map present in another webpage according to the location.
How I built it
The basics of HTML CSS and javascript is used to built this webpage. However many more things need to be completed as I am a complete begineer to this feild like the databse part of this project.
The chabot works on basic of javascript but AI can be added to it.
Challenges I ran into
I faced many challenges and felt like a handicap because I had many ideas but no knowledge to build. So at first I realised that learning is more important than anything else.
Atlast this is my second hackathon.I am exploring things
Built With
api
css3
html5
javascript
Try it out
github.com | Automatic Alert hopitals/medical shops | This project helps medical shops to get automatic alert when medications decrease in hospitals | ['Aditi Sneh'] | [] | ['api', 'css3', 'html5', 'javascript'] | 44 |
9,978 | https://devpost.com/software/summer-health | Caregiver user home screen
Caregiver profile and notification settings
Patient profile in caregiver view
Caregiver sending a message
New message on caregiver view
Meet Summer, the AI chatbot!
Elderly user home screen
Elderly user - health report
Elderly user - connect wearable devices
Inspiration
The
demand for telemedicine is rising
as a result of the COVID-19 pandemic. One of the most vulnerable groups are seniors suffering from chronic illnesses who require frequent health check-ups. Due to lockdown policies and social distancing measures, caregivers may not be able to reach seniors in need. In light of this issue, we devoted ourselves to the mission of
revolutionising elderly healthcare
by building a two-way app platform, Summer Health. It features
remote smart monitoring
for the elderly, health
data analytics and data visualisation
for caregivers to monitor seniors' health easily.
What it does
The app has 2 account types: one for caregivers and one for elderly users.
Caregiver user interface
Once caregivers sign up for their own account, they can invite patients to use the app. The app will provide a PIN they can share with their patient, making it easier for the elderly patient, who does not need to set up their account. Caregivers can
import existing medical records
or manually input pre-existing health conditions of the seniors. All health data is kept securely in our database and will be fed into our machine learning models in order to help in predicting and monitoring the patients' health conditions.
On the caregiver's home page, their patients' data is shown on a
data analytics dashboard
with the most important values and metrics being displayed (such as blood sugar level for diabetic patients). The caregivers will receive alerts in the form of red warning labels when any abnormal values or issues are identified. If there is an emergency, whether determined by the app or by the elderly patient, caregivers will
automatically be notified through a direct phone call
.
Caregivers can also contact their care recipients through the in-app chat, set threshold values for different health parameters and edit/add new patient profiles.
Elderly user interface
For elderly users, their user interface is designed to be simple and easy to follow, with large buttons and clear action indications. Our AI chatbot, nicknamed Summer, conducts daily health check-ups with the elderly by guiding them through the process including taking photos for facial recognition, asking them general and health-related questions. Seniors can respond easily by recording their voice, with
speech-to-text functionality
. Data from their voice, facial images and other responses will be analysed using
machine learning models
to determine if they are experiencing any health issues.
Summer the chatbot also serves as their
in-home caregiver
. Everyone needs real human contact though, so when in doubt, elderly users can easily contact their caregivers through the app's
messaging feature
.
In addition, elderly users can connect their
wearable devices
to the app, in order to import health readings and other relevant measurements to further evaluate the patient's health.
Challenges we ran into
We had long discussions on what platform is the most suitable for elderly, we decided to go for tablet/ phone app which includes a wider screen size and includes all necessary hardware (e.g. camera, sensors, microphone).
Accomplishments that we're proud of
We have completed the prototype concept that is available for initial user test.
What's next for Summer Health
We are looking to train the models for the machine learning analysis and create an app based on our prototype's design.
Built With
figma
Try it out
www.figma.com | Summer Health | Revolutionising elderly healthcare | ['Ava Chan', 'Megan Thong', 'Srujana Munamala', 'Miriam Robledo'] | [] | ['figma'] | 45 |
9,978 | https://devpost.com/software/astatine | Frontline Staff would be able to see booked appointments
Inspiration
As of June 15, 2020, according to the CDC, only less than 10 percent of the population in the United States is tested. If we can help simplifying the process of locating testing centers and giving the frontline staff a overview of how many appointments there are throughout the week, it would help alleviating the burden of the frontline staff.
What it does
On the mobile app, users can locate the nearest testing center.
On the web dashboard, frontline staff can have a great overview on appointment booking.
How we built it
React, firebase, Kotlin
Challenges we ran into
We had some challenges in building a solid team, some team members dropped out in the middle of the hackathon. Hence it slows us down a little in the implementation process
Accomplishments that we're proud of
Building two MVP within a week ! An android app and a web dashboard
What we learned
We learned through the process that finding the right market fit for the product is very important.
We hope to bring this solution to the next level by understanding the unique challenges and circumstances each country face in order to cater the needs and culture of the region.
What's next for Astatine
Explore the scalability and conduct more user research.
Built With
firebase
java
kotlin
react
Try it out
github.com
www.slideshare.net | Astatine | A one-stop solution to locate COVID-19 testing centers and provide an overview for appointment booking for hospital admin staff | ['Brett Hirschberger'] | [] | ['firebase', 'java', 'kotlin', 'react'] | 46 |
9,978 | https://devpost.com/software/covid-assist-k6r7n5 | Home page
World wide Tracker
Line graph
Social distancing
Awareness
Social distancing
Around the world
Education
Immunity checker
Good immune graph
Average Immune system
Poor Immune graph
1.Introduction:
The Covid assist is an web application used to track the worldwide spread of the pandemic.This application also provides a wide range of awareness on social distancing and also provides educational support available during this situation.Using this application the person could also check his immune system(Immunity check).
2.Purpose & Motivation:
As the coronavirus disease continues to evolve, therefore providing an awareness among the people is important.The District is working closely with local, state and national health care entities to closely monitor the situation and provide updates as they become available.In addition to this as students we could help people to monitor or keep in touch with the status of the pandemic,This is the main reason for creating this application
3.How this application works:
This application works through a microframework called the flask,python and the front end is designed using html , bootstrap ,css etc
4.How this application was developed:
This application is completely built using Flask python , and the front end is designed using html , bootstrap ,css etcFlask is a micro web framework written in Python. It is classified as a microframework because it does not require particular tools or libraries. It has no database abstraction layer, form validation, or any other components where pre-existing third-party libraries provide common functions
5.How to use this application:
Web applications are usually coded in browser-supported languages such as Python, JavaScript, and HTML as these languages rely on the browser to render the program executable. These applications are dynamic, requiring server-side processing.
With efficient access of internet usage of this application is easy and provides:
Web applications run on multiple platforms regardless of OS or device as long as the browser is compatible
All users access the same version, eliminating any compatibility issues
They are not installed on the hard drive, thus eliminating space limitations
They reduce software piracy in subscription-based web applications (i.e. SaaS)
They reduce costs for both the business and end user as there is less support and maintenance required by the business and lower requirements for the end user’s computer
6.Difficulties & Challenges you faced:
It was a bit difficult in finding out codes for the tracker and for the prediction of immunity.
Deciding about USER INTERFACE AND USER EXPERIENCE, SCALABILITY, PERFORMANCE, KNOWLEDGE OF FRAMEWORK AND PLATFORMS, SECURITY.
7.Go-to-Market Evaluation (How will this product be made scalable and accessible to the public?)
The frontend is an abstraction that provides a user interface. For example, open a new tab of the browser, type the address of some website, and press Enter. The website should load instantly. A well-designed page template is understandable, and the visual component is impressive, simple and easy to navigate.
Posting the site in social media to gain adversaries, and sharing it to various people will increase the number of users and an easy market evaluation will be achievable.
Built With
bootstrap
covid
covid-api
covid-india
css3
flask
font-awesome
fonts
github
html5
javascript
python
Try it out
github.com | Covid Assist | An initiator to combat the crisis | ['preethi pratheeb', 'Swethaa S'] | [] | ['bootstrap', 'covid', 'covid-api', 'covid-india', 'css3', 'flask', 'font-awesome', 'fonts', 'github', 'html5', 'javascript', 'python'] | 47 |
9,978 | https://devpost.com/software/primaltrack-two-way-app-platform-for-elderly-and-caregiver | Inspiration
Current healthcare systems are not prepared for a pandemic. So the questions are: How can we prepare for the next pandemic? How can we improve the current healthcare system to adapt?
Due to the highly infectious COVID-19 virus, many caregivers are unable to provide care or reach people who need care. The elderly and other care recipients are suffering from chronic diseases that require routine checkups. However this may not be as possible due to COVID-19 crisis and lockdown orders. Furthermore, unmanaged chronic diseases also increase the susceptibility of care recipients from suffering life-threatening complications from COVID-19 infection.
We envision that the future healthcare system should be both preventive and personalized. Our idea is to setup a platform to connect caregivers to elderly and care recipients that required care for chronic conditions, and monitor the health of elderly on a daily basis.
Our solution
Our solution is a two-way app platform for caregivers and seniors who required regular health check up. The system leverages AI technology to analyze data collected from facial recognition, speech recognition, wearable devices and/or IoT on a daily basis, and alert the caregivers if there is any identified risks. The platform also provides a way to facilitate communication between caregivers and care recipients, while aiding with health management to help alleviate caregiver stress.
Main features
Health data collection
Facial recognition
Speech recognition
Chatbot
Phone sensors
Wearable devices/sensors
Elderly focus
Voice control
AI Chatbot to stimulate human interactions
Enlarged text and other accessibility features
Reminder system
visual and sound alerts can be snoozed until the elderly login and complete the health monitoring daily
Data visualization for caregivers
Data analytics dashboard
Detailed health reports of elderly
Alert system for identified issues
Communication and reminders
How We built it
Software
This was an exciting project with many brains and skillset at work.
We preferred open source tools and platforms in different parts of the project.
Frontend Dev using Angular, FireBase Authentication.
Node Libraries Likes charts.js PWAs, BootStrap, Material Design, etc.
Hosting and CICD setups using Netlify and Heroku and GitHub.
Domain and SSL certificate from Namecheap and Let's Encrypt.
SQL DB connected to the app with Restful API.
Invision and Figma - UX/UI ProtoTypes and WireFrames
Slack for Internal Communications & Google Drive for Documents, Images, etc.
Google Colab notebooks to execute heavy GPU workloads and ML Algorithms.
Slidego, Powtoon and Toonly for Video and Pitch Decks.
Machine learning
We collected datasets from varies sources such as Kaggle, JAFFE and IMFDB and trained the machine learning model for a couple of tasks: the identification of emotions from facial expressions, identification of BMI from face images, identification of emotions from speech, and detection of falls from phone sensors. Determination of cardiovascular disease risk is also achieved by reviewing cohort studies and results in medical journals. After training the model, we deployed a demo of the emotion prediction model, BMI prediction model, and cardiovascular disease risk using Heroku service.
Challenges we ran into
It is difficult to find quality labelled data for training machine learning models, which in turn affects the accuracy rate. Given that this is a remote hackathon, we were also unable to test connection with wearables. While there is flexibility to use the app without external sensors, we plan to integrate with multiple wearable devices and platforms in the future.
What's next for miia
We are planning to bring the project to the next stage. Shoot us a message if you're interested!
Built With
angular.js
cicd
firebase
github
invision
ml
namecheap
netlify
pwa
python
restful
Try it out
miia.me
www.figma.com
github.com
github.com
emotionpredict.herokuapp.com
drive.google.com
drive.google.com
drive.google.com | miia | Digital health solution for the elderly and caregivers | ['Vanessa Guillén', 'Deepesh Grover', 'Ava Chan', 'Rohail Khan', 'Chloe Chen', 'Parteek Chhabra', 'Rohan Pal', 'Alice Tang', 'Billy Zeng', 'Mudit Mittal', 'Amit Dandawate', 'Tanjim Azad', 'Andrew Chan', 'Megan Thong', 'Mohammad Yusuf Mulla', 'Ajifama Jobe', 'DANCIL-isecure Cecil', 'Janani Ram'] | [] | ['angular.js', 'cicd', 'firebase', 'github', 'invision', 'ml', 'namecheap', 'netlify', 'pwa', 'python', 'restful'] | 48 |
9,978 | https://devpost.com/software/pharmacy-mgmt-system | Inspiration
I was inspired by improving pharmacy management expensially this covid-19 period. Pharmacies are the backbone of medical health since they provide with required equipments.
What it does
It allows easy management of pharmacies hence reducing sale of expired drugs.
How I built it
I built the system using net-beans IDE for java development using java programming language
Challenges I ran into
Lack of resources and my research was limited since a lot of pharmacies use filling system
Accomplishments that I'm proud of
The system helping the community. And reducing conjention in pharmacies hence people keeping their distance as adviced during this period.
What I learned
I learned a lot about health of the people and learned more about java as a programing language
What's next for pharmacy-mg mt-system
Improving it to help more in future and deploying it so that it can help more pharmacies.
Built With
java
Try it out
github.com | pharmacy-mgmt-system | To improve pharmacy performance expencially this covid-19 period | ['Valentine Gatwiri'] | [] | ['java'] | 49 |
9,978 | https://devpost.com/software/covid-19-help-center-chat-bot | Here it is my chatfuel directory and all blocks i used in my chat-bot
Inspiration
Now a days COVID-19 crisis getting grievous day by day. Here is a initiative to help people by serving COVID-19 related information.Thousands of COVID-19 patients die every day due to lack of ICU. Patients are not able to go out for lockdown and buy necessary medicines. So I wanted to help patients with necessary information.
This public service is absolutely free for our people.People can check out your necessary information very easily.
What it does
This Chat-bot will provide three types of cooperation, regular corona update, emergency service, health service.
The work of 'Corona Update' will give the number of people who are infected in Bangladesh every day, how many people have recovered, how many people have died.
Emergency Service's job is to provide emergency ambulance services, buy medicine online, help provide ICU services
A list of hospitals providing 'Corona' services in the medical care sector, arrangements for contacting doctors, and ways to contact the 'Corona Test Center
How I built it
I have used the 'chat-fuel' platform to create this 'chat-bot'. Every information used here has been collected from the Ministry of Health of Bangladesh
Challenges I ran into
The 'chat fuel' platform for making 'chat-bot' was new to me. So it was a little difficult. The 'chat bot' has to be presented in a simple way to make it user friendly. It has taken some time to use the information of the chat bot after verifying the accuracy of the Ministry of Health.
Accomplishments that I'm proud of
I can see that many people are using my 'Chat-bot', and getting information about 'Corona' which is something to be proud of. I am happy to be able to help people in this predicament
What I learned
For the first time I learned to make a 'chat-bot'. And learn how to present in a user friendly way. And I learned about the health system in Bangladesh during the Corona period
What's next for COVID-19 Help center-(chat bot)
I want to further develop 'chatbot'. And not just corona information, I want to help people by providing all kinds of health care information in the future
Built With
chat-fuel
qucik-reply
Try it out
chatfuel.com | COVID-19 Help center-(chat bot) | Now a days COVID-19 crisis getting grievous day by day. Heath awareness is the most significant issue in our country. Here is a initiative to help people by serving COVID-19 related information. | ['Tabia Tanzin'] | [] | ['chat-fuel', 'qucik-reply'] | 50 |
9,978 | https://devpost.com/software/towards-need | Message Notification
Inspiration
We hear everyday how health care workers are risking their lives to save patients effected with Covid-19,
inspired by the selfless dedication of the front-line healthcare workers who are fighting this battle on behalf of the rest of us.
What it does
Towards Need is a web-based platform that connects healthcare workers who need PPE and any other goods and services with members of the community willing to donate directly to them. The site is very simple for both sides and contains signIn/Register,listing, search,filtering,posting a requirement , Notifications and messaging functionality.
How I built it
Frontend: Angular 9,Angular Material
Backend: Firebase, Google Places API, Google Geo Coding API, Google Maps API
Used FormSpree for messaging functionality.
Challenges I ran into
Getting feedback from healthcare providers and community members in order to design the Product in a manner that is easy to use and deliver the most .
Accomplishments that I'm proud of
I was able to do a short survey and understand the requirements and build a prototype that can make a huge impact .
What I learned
Health care workers are facing challenges every day with the facilities provided to them , In research i also found that donations are not directly getting to them its very complicated .Its needed to support the front line workers at large scale from community members.
What's next for Towards Need
Some future ideas we have are as follows:
1.Scaling: As app gets ready for the production as number of hits gets increase to site that can be handled by caching db queries and putting a load balancer using ELB on AWS.
2.Features:As web app moves to more enterprise level architecture ,features like collecting health care worker medical center location and filtering data to show on map limited to a nearby area using Google Distance matrix API and sending notifications whenever there is donor have posted in nearby area and vice-versa and having a social sharing feature can even more help the health care workers .
Built With
angular9
angularmaterial
bootstrap
firebase
google-geocoding
google-maps
google-places
Try it out
github.com | Towards Need | A Platform to Connect Front-line Health Care Workers With Community Members to help Health Care Workers to donate them critically Needed PPE during Covid-19 Crisis | ['vijaylakshmi karwa'] | [] | ['angular9', 'angularmaterial', 'bootstrap', 'firebase', 'google-geocoding', 'google-maps', 'google-places'] | 51 |
9,978 | https://devpost.com/software/socialdistancer | Social Distancer
This app keeps people 6 feet away
This simple but useful App uses your iPhone’s camera to alert you when someone is within your six-foot safety zone.
Click on the App and your front camera opens as you point it at anyone nearby. If someone is within 6 feet, the box around the person turns red. If the person is more than 6 feet away (approximately 2 meters), the the box around the person turns green.
How to use
Hold phone horizontally while directed at people. If the box around a person is green, they are beyond 6 feet from you. If the box around a person is red, they are within 6 feet of you.
If there is no box when the camera is pointed at a person, than the camera does not see the person clear enough.
Works best when the target person is standing.
How Does it Work?
Social Distancer was created in Xcode and Android studio using Swift and Java. They both use the YOLO Object detection model to track people. When the camera sees a person, the app estimates the distance of the person based off of the size of the person in pixels.
Releases
Apple version can be demoed here:
https://ariwasch.applivery.io/social-distancer
Android version can be demoed here:
https://play.google.com/store/apps/details?id=org.microincorporated.socialdistancer
NOTE
Social Distancer was taken down from the app store after Apple introduced new policies to prevent the spread of false information of Covid-19. That means no social distancing or Covid-19 related apps are allowed to be published by individuals. If anyone who is reading this is part of a recognized institution (hospital, government agency, university) and would be willing to publish it, the developers of both the Apple and Android version would be willing to do so.
Additionally, we are willing to donate a majority of the ad revenue to Covid-19 relief efforts once both apps are published.
Contact us
For more information, email
[email protected]
or
[email protected]
Prerequisites
You need an Android device and Android development environment with minimum API 21.
Android Studio 3.2 or later.
Built With
java
Try it out
github.com
play.google.com
microsyncinc.github.io
ariwasch.applivery.io
github.com | Social Distancer | This simple but useful App uses your phone’s camera to alert you when someone is within your six-foot safety zone. | ['Lincoln Doney', 'Ari Wasch'] | ['The Wolfram Award', 'First Place - Covid Track'] | ['java'] | 52 |
9,978 | https://devpost.com/software/keep-your-distance-1s0lbz | Home Screen
Map showing nearby stores and public buildings
Social Distancing Violation Alert
Heat map telling you how crowded a store is
Details like number of people in a store, capacity and last sanitized time for a store
Inspiration
In the last few months, everyone's life has been taken over by one main thing, COVID-19. We've all spent nearly three months in lockdown and now that things are slowly opening up, the urge to go out, be free and meet people has increased significantly for many of us. However, we realize that it is still necessary to take precautions, keep our distance, and limit our contact with other people. Recognizing the ease with which one may get carried away, we have built a mobile app that helps you stay safe and keep your distance!
What it does
Our android app solves two main problems. Firstly, it helps maintain social distance between individuals who use the app. It can measure the distance between two individuals and provides an alert whenever you are too close. Thus, it helps reduce the chances of contracting COVID-19. Secondly, it identifies nearby stores and public buildings and gives you information such as the number of people in the store, the maximum people who can be in the store safely as well as when the building or store was last sanitized. This allows people to make informed decisions on whether going to a building is safe or too risky and hence can reduce the possibility of the spread of COVID-19.
How we built it
Our app was built on Android Studio. We wrote the code in Java and integrated Google's maps and places APIs to provide the location and building information capability to the app.
Challenges we ran into
There were several challenges we ran into through this journey. The first major hurdle we faced was that no one on the team knew how to build mobile apps and so we had to learn how to use Android Studio from scratch. This definitely slowed down our process and made every step much harder than it would have been if we were familiar with the environment. In addition, one of our biggest challenges was trying to work with the database. We faced significant challenges trying to prevent duplicates from being added to the database as well as trying to query information from it.
Accomplishments that we're proud of
Overall, we are very proud of the app we have built, especially considering we knew nothing about the platform we built it on when we started. Specifically, we believe that the detection of whether the social distancing rules are being violated is something we are proud of as we had to consider several different methods before finally getting one that truly works and we believe that it would be something very useful in the current world.
What we learned
Apart from learning a new platform, a new language, and how to work with some APIs, one of the biggest learnings from this project was how to appropriately use and learn from the vast resources on the internet. Since we were working with Android Studio for the first time, we looked for several different tutorials and documentation online, and initially, there was a lot of time wasted because we were not able to find the information we wanted. However, as time progressed, we learned from our mistakes and became better at optimizing our searches.
What's next for Keep Your Distance!!
Currently, the app only provides the number of people in a store and that helps one decide whether it is safe to enter or not. In the future, we plan to implement this for each aisle of the store and generate a map that shows where people are around you so that you can make more informed decisions on where to go
Built With
android-studio
firebase
google-maps
google-places
java
xml
Try it out
github.com | Keep Your Distance!! | An app that helps maintain social distance and identifies the areas around you that are safe and hygienic for you to enter | ['Sruti Srinidhi', 'saroja srinidhi'] | [] | ['android-studio', 'firebase', 'google-maps', 'google-places', 'java', 'xml'] | 53 |
9,978 | https://devpost.com/software/auto-mask | Inspiration
When mask-wearing became required due to COVID-19, I empathized with the doctors and nurses who have always had to wear the itchy and hard-to-breath face covering. Realizing that face coverings will always be uncomfortable no matter what material or design, I thought to make masks easy to take on and off so catching my breath in a grocery store would be effortless.
What it does
Auto Mask features an eye shield to protect from infected saliva, touchless control to minimize bacteria transfer from hands, and even a sneeze detector! An electrode on the abdomen activates the mask just in time to catch a cough or sneeze.
How I built it
I designed the 3D printed headpiece and combined the Arduino microcontroller with an ultrasonic sensor, muscle sensor, and a pair of servo motors.
Built With
3dprinting
arduino
c++
cad
Try it out
www.thingiverse.com | Auto Mask | Normal masks are uncomfortable to wear all day. Auto Mask features touchless mask on/off control and abdominal muscle sensing sneeze detection to catch coughs in time. | ['Taliyah Huang', 'Calista Huang'] | ['Hardware winner'] | ['3dprinting', 'arduino', 'c++', 'cad'] | 54 |
9,978 | https://devpost.com/software/happy-days-will-begin-soon | My Logo
A Ray of Hope
Arogya Setu App
Stay Home! Stay Safe
Wash Wash and Wash!
Follow Guidelines
News Fee
Lets Fight!
Covid-19
Motivation to all the Warriors
coronavirus
Follow Guidelines
Vaccines
Covid-19
Follow guidelines
Stop Corona
Motivation to all the Warriors
Stop Covid 19
Support Hospital Workers
Hope and Sunshine
Hope and Sunshine
Stay Strong
Covid-19
Covid-19
Weak Masks
Motivation to all the Warriors
Motivation to all the Warriors
Where there is Will,There is a Way
Coronavirus
Motivation to all the Warriors
Motivation to all the Warriors
Life is not about Challenges. It's all about how you overcome these challenges in Life. I was scrolling through my LinkedIn feeds when I came to know about DevPost Hackathons and realized why did I never participate in the same. Its good to work on your projects but it is excellent to complete the challenges or tasks given my some Organization.
The Name of my Project is as so, because, since the World has encountered this pathetic pandemic, Happy Days are almost gone. So, what I feel is to encourage one and all so that they could stay strong and fight this pandemic and soon, we will be singing the "Happy Days have Begun".
This Project is a website on Coronavirus with a tagline of "Let's Fight & Stay Strong". It includes all the information related to this pandemic. It involves-
1) The Home Section
2) News Feeds
3) Updates from all over the World
4) Updates from all over India
5) Visualization through Graph
6) Motivation to all the Covid-19 Warriors
7) Status Check
The Project has been developed using technologies such as JavaScript, HTML, CSS, Bootstrap, MySQL, PHP and jQuery as well.
HTML, CSS, Bootstrap, JavaScript and jQuery has been used for Front End Development while PHP and MySQL is used for Backend, for maintaining the database, for every user that makes the entry to check his status.
Challenges must be something that do not let you sleep. You must overcome all of them. The challenge that I faced was on Graph visualization but managed to overcome that as well and was extremely happy to have that.
I am proud to face challenges in my life. Moreover, Looking at these Corona Warrior patients is something that gives us motivation on how to fight death even if, it reaches the threshold.
Last but not the Least, The only motive behind this Project is to aware the people all around the world to Stay Safe and Healthy. Do not Lose Hope as Happy Days will Begin Soon!
The Link to my Project is:
https://drive.google.com/drive/folders/1N-D3l-DsKifqs0ZivE66e9MQQ_TsJRRz?usp=sharing
Built With
bootstrap
css3
font-awesome
google-font
html5
javascript
php
phpmyadmin
visual-studio
xampp
Try it out
drive.google.com | Happy Days will Begin Soon! | Let's Fight and Stay Strong! | ['Kanika Bagri'] | [] | ['bootstrap', 'css3', 'font-awesome', 'google-font', 'html5', 'javascript', 'php', 'phpmyadmin', 'visual-studio', 'xampp'] | 55 |
9,978 | https://devpost.com/software/social-media-on-iphone | Inspiration
Game online winwin
Built With
html5 | Social media on iPhone | Social media game on iPhone | ['Tam Nguyen'] | [] | ['html5'] | 56 |
9,978 | https://devpost.com/software/bigfridge | BigFridge App Design
Business Model Canvas
Inspiration in Covid-19 Crisis
What is the problem about food during Covid-19 Pandemic?
There may be shortages in food supply and ambiguity in food demand due to lockdowns.
If the isolation period prolongs over months there can be shortages of some food. Some vegetables, fruits and grains cannot be planted for the next year because of social distancing is necessary for farmers. Some ingredients cannot be transported from local producers to other countries because the borders are closed.
Food stocks should be planned carefully in this disaster. Otherwise food will be a serious problem along with virus disease health issues.
In the coming months, local authorities, food producers, big companies and governments will require data. In normal times they use their own data and projection tools in order to plan the food demand properly and distribute evenly. But this is a crisis that the world had not been experienced before. Everything can fall into chaos. Supply chain might be disrupted. Demand routines might change abruptly. Chaos in food supply might cause serious destruction. Therefore accurate predictions are essential keys to handle this disaster.
What it does?
If we count what we have in every individual fridge, then we will be able to know the big data of all available food stock.
BigFridge is an app where individuals can contribute to the macro planning of food supply by providing information of what they have in their own household stocks and what they will need in the coming months.
When all food stock is gathered in the BigFridge’s pool, Big Data is provided to food producers, big grocery chains and local governments.
There are more than 1.2 billion households worldwide. The number of total population under the age 25 is more than 3 billion. We target 1% of these households to use this app, which is 12 million users. During this quarantine times, we expect the young members of the families will adopt this new app and contribute big food data while winning.
What's the future target of BigFridge - Implementation of AI
This study should be accepted as the first step and groundwork of a long-term project which will provide better projections of food demand. With BigFridge application, people around the world will be able to upload the existing food stock in their houses.
Sharing this information may build big data and when numerous fridges are analyzed, basis for accurate planning is obtained. For the progressing stages of the project, it will be enhanced with Artificial Intelligince algorithms resulting in more reliable predictions. AI will also be facilliated in order to provide customization for better user experience.
The value of the solution after the crisis
BigFridge is not developed just for providing a solution during this virus crisis. For times when life turns back its normal routine, BigFridge comprises exclusive solutions:
i) Prepaid orders provide win-win for consumers as well as food producers and big grocery stores. Users will receive significant discounts when pay beforehand and producers will feel quite safe because they will be able to plan their production according to what they have already sold.
ii) Control of excess food prevents waste. When using BigFridge app one organizes her/his fridge and checks what it is present there for 5 to 10 minutes. This is a necessary time interval that everyone should spend every week for controlling the expire status of the items in food stocks. If some of them are going to expire soon then you can push the donate button and BigFridge will inform the closest Food Bank to your home.
The necessities to continue the project
No piece of edible stuff should be wasted while there are people suffering from hunger.
Personal Level: If you have excess food and wish to donate, BigFridge app informs the local food bank nearby your location.
Society Level: If supply chain is planned according to accurate demand projections there will be less food to be wasted.
What we have learned?
While studying on this project we have learned to realize that personal privacy is important. It should not be violated or abused even we are in the middle of the hard circumstances of a global disaster.
Users may sign up as anonymous with nicknames in order to protect their privacy. However they should let the data they have uploaded to be shared with partner companies and related local government.
User profile of BigFridge requires 7 simple questions:
Age,
Gender,
Country and City,
Health Condition,
Education,
Income Level,
Number of people in the household.
What are the next steps?
What we have submitted as the mobile tool for this challenge is only the demo version of the coming product. We are working on developing the real app and it is going to finish soon. We have completed the first week of the project schedule below:
Week 1.
Brain storming, lean startup canvas, product design, app in demo version, web site
Week 2.
Graphic designs, coding, MVP, developing, IOS and Android app
Week 3.
Launching the app,promotions, digital marketing, user feed backs, initial sponsors
Week 4.
Agreements with data analytics business partner. Agreements with food producers, big grocery stores and state officials
Week 5.
Running the app and gathering big data. Implementing basic AI algorithms
Business Model Canvas
KEY PARTNERS
Key Partners in Food Production and Supply: (and/or)
i)Big Grocery Chains
ii)Online Grocery Companies
iii)Food Producers
Motivated by optimization in operations and stock control. Improvement in profit margins due to reduction in waste with prepaid orders.
Key Partners in Planning of Food Supply: (and/or)
i)Local Government Authorotiries
ii) Agriculture Departments and Bureaus
iii) Ministry of Food & Agriculture
Motivated by better coordination due to reduction of risk in food supply chain.
Key Partner in Data Analytics:
i) A reliable and trustworthy data analytics company in order to share data.
Motivated by the acquisition of particular data resources gathered by the app from the activities and personal information provided by BigFridge users.
KEY ACTIVITIES
i) Building and promoting an online medium (eg. ios/android mobile apps) for the users in order them to provide the data of their household food stocks.
ii) Making agreements with Big Grocery Chains and Online Grocery Markets about the gifts and discounts that they are going to offer to BigFridge Users.
iii) Organizing of the gathered raw data according to the partner Data Analytics Company’s requirements.
KEY RESOURCES
i) Creative designs and ideas are important in order to build this brand new mobile app. Our young and creative team members are the key resource.
ii) Strategic partneships and coloborations among food business circles is at the heart of this model. Our mentors and advisers are industry experts having +60 years experience totally.
VALUE PROPOSITIONS
VP for Users:
i) Being a part of the solution for the possible problems in Food Supply Chain.
ii) Receiving discounts, giftcards and paychecks for grocery shopping.
iii) Access to healthy meal recipes that can be prepared with the existing goods in the fridge.
VP for Food Poducers and Grocery Markets:
i) Prepaid orders provide win-win for consumers as well as food producers and big grocery stores. Producers will be able to plan their production better.
ii) If supply chain is planned according to accurate demand projections there will be less food to be wasted.
Characteristics:
Newness, Convenience, Accessibility, Design, Customization, Cost Reduction, Risk Reduction
CUSTOMER RELATIONSHIPS
BigFridge is positioned as a novel domestic mobile brand which provides some benefits and have fun when using it.
Therefore it is important to keep the online product of BigFridge always updated, attractive and functional by continuous flow of fresh content on easy cooking, healthy recipes, kitchen tips, food hygiene, etc.
Giftcards, paychecks, discounts and delightful surprises will be waiting for loyal users and BigFridge will soon become a love mark.
CHANNELS
The channel of the main business activity for user interface are Mobile Apps (ios/android). Promoting the mobile apps to reach as many young ypeople as possible will be held by digital and conventional marketting tools. Getting the support of local authorities and governments for promotion campaigns as well as cooperating with local communities and food banks are important in order to spread the usege of the apps. BigFridge is planned to be a part of the daily kitchen and grocery shopping routines of individual users.
CUSTOMER SEGMENTS
Young generation are the target customers while every person with a mobile phone who is willing to download an app can use BigFridge. It is so easy to use but there is a limitation in terms of place: It can only be used at home, in the kitchen. The user should look in the fridge and write down what is there, check the lists on the app, take photos of the food. When the weekly task is complete, the user receives a QR code and views the gifts. Although these activities are all simple and fun, people over 50 of age are generally not prone to use such apps.
There are more than 1.2 billion households worldwide. The number of total population under the age 25 is more than 3 billion. We target 1% of these households to use this app, which is 12 million users. During this quarantine times, we expect the young members of the families will adopt this new app and contribute big food data while winning.
COST STRUCTURE
BigFridge is value driven rather than costs. The requiriments for fixed costs are almost negligible and all the workers are paid in certain percentages of the income. Therefore they have to create revenue in order to be paid well.
Variable costs are due to digital marketting and promoting activities. All the operational activities are held within a cost sensitive perspective. No offices, no luxirius utilities. Costs like hosting and cloud storage are afforded by foundations supporting startups.
REVENUE STREAMS
BigtFridge app is free to use. No payment or fee is expected from the user. Similarly nothing is charged to partner Grocery Chains while they are expected to offer discounts, giftcards and paychecks frequently to loyal users while sponsorship supports are all welcome from partner companies.
When data of food stocks of the users are gathered, big data is provided to food producers, big grocery chains and local governments within the partnership of a data analytics company.
The customers of the partner data analytics company who are willing to pay are going to be the main source of income. Tehrefore the price or value of the collected data as a resource is going to be dynamic and depends on the negotiations according to current market circumstances.
Team
ARTUN AKDOGAN (21)
Sophomore in Electrical and Electronics Eng. Bogazici University /
QuID for Developers Certificate – ETH Zürich /
Applied AI Certificate – inzva (Sanctuary of the Turkish Hacker Community) /
Cyber Security Certificate – BUSIBER /
Excelled in Python and Linux /
github.com/artun-akdogan
ILAYDA ISERI (17)
Koc High School Junior /
Google Science Fair 2019 Regional Finalist with ‘The Woof Project’ /
MIT Research Science Institute Summer Program 2020, Candidate in the national short list /
Awards and honors in national math contests /
Studying to be a mathematician, composer, cartoonist and filmmaker.
BARKIN E. OKSUZ (15)
First year in Robert College, RC24 /
IDTech Camps in Game Design and Development, Stanford Campus, 2018 /
He builds web sites and apps, wants to be a gamer
Built With
appsheet
jawa
python
wix
Try it out
www.appsheet.com
oksbar24.wixsite.com | BigFridge - Big Data of Food | We build a bridge over fridges. BigFridge is an app where individuals contribute to the macro planning of food supply during the pandemic by providing data of what is already in their household stocks | ['Artun Akdogan', 'İlayda İşeri', 'Melsen Tunca', 'Barkın E. Öksüz'] | [] | ['appsheet', 'jawa', 'python', 'wix'] | 57 |
9,978 | https://devpost.com/software/safe-zone-your-safety-is-our-priority | Test center
Test center testing details
Restaurant
Restaurant timing details
Store
Store timing details
Church
Church timing details
Inspiration
In light of the covid-19 pandemic, the idea of being in public itself is its own risk. This is due to how highly contagious the Covid-19 disease is. Being in close proximity to other people automatically puts you at risk for contracting the virus, since there is no way of knowing who has it or not. It becomes a particularly more dangerous situation when crowding occurs. In a city like New York, where crowds are sometimes inevitable, the risk is more real compared to other places.
Solution
Our app provides users with the information they need to plan their trips according to busy and quiet hours for certain establishments (Test Centers, Restaurants, Stores, Churches ). By providing users with a list of the busy/quiet hours typical for specific locations, it will help them to better prepare and plan their visits. For example, they have the information at hand to select any of the quiet times to visit an establishment. Likewise, they will know beforehand if they are visiting an establishment during busy hours and will be able to better prepare (e.g. ensuring that they do not forget masks and hand sanitizers before leaving their homes). This app will help users to plan their trips or outings with more confidence.
Theme
Nontraditional methods to deliver care in a COVID-19 landscape
What it does
Safe-Zone is currently a concept app we have designed with mock-up data that shows the busy and quiet hours for certain restaurants, covid-19 test centers, stores and churches in the city of New York which was very hard-hit by the covid-19 pandemic.
How we built it
We approached this project by first brainstorming the idea. Once the idea was finalized, we divided the UI, API and potential database work amongst our team members. One team member, Aastha, was working in IST zone. The other team member, Kai-Ann, was working in EDT zone. Priya helped in analyzing which tool to use for collaboration among Jira and github. We collaborated with each other on a regular basis to discuss the progress using Slack and Google meet-ups. We used the Agile methodology with the GitHub Projects planning tool for keeping track of our tasks and progress. One person built the UI using Flutter. The other person explored the APIs and built the JSON files required to showcase the data in the UI. We were also able to configure and initialize the Firebase Firestore database (Real-time database) in Flutter. This ensures that our app is also back-end ready. We are proud of successfully collaborating with each other on this project despite being in different time-zones (EDT and IST). In addition, we are happy that we learned how to position Widgets in Flutter because it allowed us to develop a better UI.
Challenges we ran into
Working in different time zones (IST vs. EDT).
Taking time out of hectic office/work schedules while also working overnight to complete the project.
API Challenges : Difficulty sourcing an API that measures crowd data in Real Time so that we can show crowd statistics for any given location at any time. Google maps popular times is not available in their API unfortunately. Another solution we found called BestTime API was subscription-based and so we we decided against using it at the time. Building the JSON data was tedious because it involved a qualitative comparison of popular times for each place. Even though we used mock-up data, the data points themselves are accurate.
Learning and exploring new technology like Flutter and figuring out the widgets for our App design. Understanding Firebase integration (issues with compiling DEX files) and Google Map API integration. Using JSON data in Flutter.
Accomplishments that we're proud of
This is the first mobile app we have built. We also used Flutter for the first time which itself is the biggest achievement. Now we can build mobile apps using Flutter and Firebase. We have successfully built an app to help people and is a noteworthy contribution to society during such tough Covid times.
What we learned
We learnt UI design, back-end modelling and developed a MVP in record time. We chose Flutter as it is the latest technology which enables one to build the mobile app with fastest turn-around time. We were amazed at how creating a good design for a mobile App with good UX is so much easier than before using the Flutter framework. We are very proud of our achievement and thank Girls In Tech for organizing this Hackathon. We also thank DevPost for providing us with such an amazing platform including the slack tool for collaboration.
What's next for Safe Zone
Implement BestTime API to make this app production-ready in near future. Currently, we are using JSON files to populate the data and have Firebase as a back-end service. Once the BestTime API is implemented, we can expand and store collections in the database. We can also implement SignUp and Login methods (using Firebase OAuth) so that we can store unique data pertaining to our users. This will assist with future data analytics and insights into our app usage.
Built With
dart
firebase
flutter
github
google-maps
json
Try it out
github.com | Safe Zone | Zap your worries away and plan your trip with confidence! | ['Indirapriyadarshini .', 'Aastha Khatri'] | [] | ['dart', 'firebase', 'flutter', 'github', 'google-maps', 'json'] | 58 |
9,978 | https://devpost.com/software/open-consulting | 100 days recovery index
US and other countries deviating from 100 days index as on 12/06/2020
What inspired us.
Countries are slowly opening up economies after a long lockdown, but are not very sure about the risks involved due to the dynamic nature of people movement. We have used google mobility dataset along with "Our World in Data COVID-19 Testing dataset" to generate a risk and recovery index of any particular country.
What it does
Source Datasets used as below:
Our World in Data COVID-19 Testing dataset
https://ourworldindata.org/coronavirus-testing
Google Covid19 Community Mobility Reports
https://www.google.com/covid19/mobility/
Methodology:
It Aggregates source data at a daily country level and consolidates as master data
Calculate risk index based on the rate of infection and the total number of infections
Train machine learning model to translate the relationship between risk drivers (mobility and/or restriction) and risk index
Prediction Scenario:
To prevent the second spike in the recovery phase, one would be able to predict the risk index given the assumed risk drivers therefore to adjust government policies and countrywide communications
Risk Index Formula:
rate of infection: the increase/decrease rate of current total cases against total cases from 14 days ago (normal virus incubation period)
number of infection: current total cases per million
The formula refers to the UK government risk index guidance:
https://www.spectator.co.uk/article/how-number-10-should-illustrate-its-covid-alert-formula
Prediction Model Build:
It makes use of a classification model to capture the relationship between risk drivers (mobility and/or restriction) and risk index to future prediction that aids recovery phase planning
How I built it
Risk & Recovery Index generator App is powered by python notebooks running on Azure Databricks using datasets from Our World in Data COVID-19 Testing dataset and Google Covid19 Community Mobility Reports.
We used Azure Databricks to run our notebooks attached to a Spark cluster.
Pushed notebook analysis outputs to an Azure WebApp services python site.
On the web app, a user can input destination location to get Risk Index.
User can use another field to get destination flight information.
Challenges I ran into
Webservices do not work as intended in a python flask environment.
Runs fine locally.
Accomplishments that I'm proud of
We not only managed to get a brilliant analysis done based on datasets available but made it interactive with a web app running on Azure web services.
Risk index calculator is our USP. We created a formula based on R-value calculator.
What I learned
How to configure Azure Databricks and how the spark clusters power the notebooks for machine learning.
Notebook integration with a web app using react and flask.
Python coding.
What's next for OpenConsulting Team.
We plan to put Risk and Recovery Index to production by creating a Chat App for Travel, Human resources and retail sector powered by Azure Databricks.
Built With
ai
azure
azurewebservices
coco
databricks
datetime
flask
functools
github
itertools
machine-learning
math
numpy
pandas
python
react
Try it out
github.com
covid.azurewebsites.net
hackforgood-video.openconsultinguk.com
hackforgood-web.openconsultinguk.com | Risk & Recovery Index | COVID19 Risk & Recovery Index App for air travel,HR and retail industry. | ['Edmund D’souza', 'Minu Beena Sisupal', 'Raghuveer Yarlagadda', 'M Kumbnani', 'Ewan Zhang'] | [] | ['ai', 'azure', 'azurewebservices', 'coco', 'databricks', 'datetime', 'flask', 'functools', 'github', 'itertools', 'machine-learning', 'math', 'numpy', 'pandas', 'python', 'react'] | 59 |
9,978 | https://devpost.com/software/covid-19-health-center-qogj8t | Doctor
Inspiration
I took inspiration to do this project from the growing crisis and how any help related to the current scenario can yield something better.
What it does
This is a GUI Application with which the user can check for symptoms with the help of a rule based chatbot, which will further give recommendations on evaluating their health. The user can also read all the latest worldwide news related to COVID-19. This digital health center also help the user to keep track of the statistics that is the total cases, total recoveries, total death, total active and critical cases of any country and allows the visually impaired to listen while the machine speaks the text. Furthermore the user can read or listen the precautions given by WHO to keep one safe.
How I built it
I built it using tkinter to give users an easy interaction. A text to speech library- pyttsx3 has been used to also help the visually impaired to some extend. There is a rule based chatbot that evaluates the health by asking certain questions. The data for evaluation has been adapted from DOH Guidelines. To keep track of the statistics I have used the "Coronavirus map" API. And the other data has been obtained from the WHO website.
Challenges I ran into
I ran into certain challenges while making the chatbot since pyttsx3 and tkinter were not syncing together so I decided to use multithreading to some extend. Other than this the designing and functioning needed a lot of thinking and efforts.
Accomplishments that I'm proud of
I'm really proud of the fact that I did something on the current crisis that might be beneficial for people and especially the fact that I did consider the visually impaired while building this. I am also proud of the fact that I used OOP completely to build this project.
What I learned
I have learnt various different libraries and I think I have grown a hands on experience in using most of them like Tkinter, BeautifulSoup and pyttsx3. Other than this I have grown a fair knowledge of information related to COVID-19.
What's next for COVID-19-Health-Center
I really plan on using machine learning and training the chatbot to answer smartly. There are still some thing that can be added to the GUI.
Built With
beautiful-soup
python
pyttsx3
tkinter
Try it out
github.com | COVID-19-Health-Center | This is a GUI application needed to keep track of almost everything related to coronavirus. This is made also to help the visually impaired, so that they can keep track with just one click. | ['maryamnadeem20 Nadeem'] | [] | ['beautiful-soup', 'python', 'pyttsx3', 'tkinter'] | 60 |
9,978 | https://devpost.com/software/safety-travel-app | Safe travel
app for iOS and Android that was born to help to the revival of tourism.
A trip is definitely one of the most beautiful and constructive experiences to do in life. For us who love to travel every opportunity is good to leave our habits and set off to new places, new cultures and new people.
From our experience we have understood that it is essential to travel safely in order to live this life experience.
That's why Safe travel app will follow you in your every move and help you at any time
Our goal is to create a worldwide network of concierge, a physical person, not a virtual bot, that based on your location will be the nearest operator so you don't have time zone problems or away if you have your own need!
Built With
blockchain
c++
eos
firebase
java
objective-c
python
solidity
swift
Try it out
bitbucket.org | Safe travel | Safe travel | ['Massimiliano Pizzola', 'Daniela Tabascio'] | [] | ['blockchain', 'c++', 'eos', 'firebase', 'java', 'objective-c', 'python', 'solidity', 'swift'] | 61 |
9,978 | 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
Try it out
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'] | 62 |
9,978 | https://devpost.com/software/covid-oversight | Details
SS1
SS2
SS3
Inspiration
Let's consider the story of Chris. He is still under lockdown and he is worried about his
health. Currently he is not aware of the risky areas surrounding him. So he cannot leave his home
to visit the local grocery store (which he prefers to buy from over online stores) without panicking.
Also he fears he might take a route through a region infected with the virus which can affect him as
well. And even if he reaches the store safely, he might be faced with a crowd which doesn’t
maintain social distancing; and even if they do so, they all come at the same time leading to long
queues. Even after all this, there is still a chance that he might be affected but asymptomatic and
he might further infect others as he might be unaware of whether he had been in contact with
anyone before.
What it does
COVID-Oversight tries to mitigate the above problems with a one-stop solution for
visualizing local risky areas, finding safe stores and safer routes for visiting them, creating
systematic queues for reducing delays and a case reporting mechanism for leveraging
crowd-sourced data to map the crisis and protect one and all
How I built it
Here maps, Twilio API, IBM Cloudant, IBM Cloud Foundry, Postman
Accomplishments that I'm proud of
Completed the hack in under 24 hours
Created an end-to-end communication, reporting, and verification system
What I learned
Apllication of Twilio and Postman
Cloud hosting
What's next for COVID-Oversight
● Integrate chatbot inside the web app
● Use IBM Watson API for further diagnosis on chatbot
● Use IBM Watson Studio to design a forecasting algorithm for better queue management and
COVID spread
● Use Here Maps geofencing API and Twilio Notify API to alert users when they enter risky
areas
Built With
flask
here-geocoder
here-map-image
ibm
postgresql
postman
python
twilio
Try it out
github.com | COVID-Oversight (Team OopsIDidItAgain) | COVID-Oversight tries to mitigate the above problems with a one-stop solution for battling Covid-19 | ['Saumo Pal'] | [] | ['flask', 'here-geocoder', 'here-map-image', 'ibm', 'postgresql', 'postman', 'python', 'twilio'] | 63 |
9,978 | https://devpost.com/software/mylog14 | Find us on twitter #MyLog14 #EnjoyHome #TogetherWeLog
Log Your Life, Keep Your Data Share & Help With Your Consent.
Post COVID-19 lockdown, there are some problems we face
What MyLog14 provides.
GIF
Provides easy way to record self symptoms, and all data is saved locally to protect privacy.
The incentive feature flow
Built by community, open and transparent!
MyLog14 got lots of users feedback!
Add Japanese and French support to the App
Problem and Inspiration
According to the Harvard scientists
[1]
, the world may need to live with the virus until 2022. During the pandemic, some governments choose to strictly monitor citizens' symptoms, daily activity, and travel history in order to slow down the spread. However, such measures raise serious privacy and surveillance concerns.
The post-pandemic period is going to be a period of at least 12 or even 18 months long. Therefore, all tools and services have to put privacy and users' right first. The pandemic is slowing down at the moment, some countries such as Germany are preparing to re-opened or are thinking to reopen. This allow us to think early: "how can we build a tool to strike the balance of protecting people from virus infection but at the same time reduce the damage to our democracy".
We believe the key is the connection of different stakeholders in the post-pandemic life with a service that respects users' privacy. Only if we fight altogether, it is possible to maintain normal life under the continuous thread of the virus. For countries and cities thinking about reopening, there are three key things need to be considered:
1. Citizens need to self-report and record daily symptoms to make sure we and our loved ones are healthy and safe.
2. Governments and research institutes need crowd data to analyze changing symptoms and to monitor high-risk areas.
3. Shops and restaurants are financially suffering from low volume customers
That's why we have been developing MyLog14.
[1]These Harvard scientists think we'll have to socially distance until 2022
The Solution
What can MyLog14 do?
MyLog14 empowers individuals with their health data to improve public health and support the local economy. This App is built in the MyData community and was highlighted by MyData Global[2][3]. The privacy policy follows MyData Principles[4].
[2]
https://mydata.org/2020/03/26/mydata-vs-covid-19/
[3]
https://weekly-digest.ownyourdata.eu/en/weekly/2020-04-03
[4]
https://mydata.org/declaration/
It provides the following solutions:
1. An accessible and affordable way to record self symptoms, all data is saved locally and controlled by users to protect privacy.
2. Users can contribute by sharing data to exchange for coupons. Contributed data can be used by research institutes for analytical purposes. Shared data is anonymized, name or information which can identify individuals will be excluded.
3. Shops and restaurants can advertise their products by providing coupons.
MyLog14 provides a mobile app for users to efficiently log and manage COVID-19 related symptoms without sacrificing privacy. The features of MyLog14 includes:
√ Symptoms logging/Snap-Capture
√ Keep raw data (location/timestamp/device information) with every log/capture
√ Reminders
√ Local data storage
√ Export of users’ own personal data
√ The incentive for motivating participation
How does MyLog14 differ from other tracking apps?
Tracking apps do not commonly collect your symptoms, but you can manage them through MyLog14.
Tracking apps are good, but in a post-lockdown society with a low number of infected cases, the advantage of tracking is limited. What matters more is the health status of each of us.
With MyLog14, people can easily log and track their symptoms and health status without compromising privacy. The recorded data can be used for
★ Self-management to protect you and the loved ones are healthy and safe.
★ Helping doctors to diagnose better by sharing the recorded data temporarily with the medical staff you trust.
★ Contributing to research institutes by sharing anonymous data for analytical purposes.
★ Collecting bubble-tea points to exchange for coupons and help small businesses.
The goal for MyLog14 is to empower individuals with their health data to improve public health and support the local economy. At the same time, it helps strike a better balance between civil rights, data privacy, and epidemic prevention.
What we have done during the weekend
☆ Host kickoff and
3
project sync-up meetings.
☆ Acquire
2
new members joining the project development, one with expertise in business consultancy and one with expertise in AI and Computer Vision research.
☆ Enhance features of the current MVP.
☆ Finalize the technical design of the coupon-sharing mechanism.
☆ Discuss with
10+
mentors for the long-term working models and identify the stakeholders.
☆ Add Japanese and French support to the App.
☆ Collect
50+
survey results for MyLog14 in the hackathon. For the question "Will you use MyLog14?", only
less than 4% responded no
.
☆ Update English terms and conditions to
ensure GDPR compliancy
.
☆ Survey the current privacy concerns and user reactions of tracking apps.
☆ Collect
10+
feature requests for the next phase of development.
☆ And, an online Yoga with the team together!
The solution’s impact to the crisis
Helping individuals to record daily activities and own their data
We’ll soon get into the post-pandemic period. Before the vaccine has been invented, everyone has a risk to expose under the virus threat. Neither lockdown or using government authority to track people is the permanent way to prevent the breakout. The app can help healthy people to record their daily health status and activities. If they get infected or under high risk of infection, the data they logged will be useful to organizations that need to analyze their location history.
The necessities in order to continue the project
86% of users believe services provided by MyLog14 can contribute to epidemic prevention!
During the last month, we have
★ From idea to a usable MVP, it only takes less than one month.
★ The size of the community grows
600%
since we kickoff MyLog14 project.
★ With the diverse community, we are able to collect opinions and feedback from people living in
3
continents around the world.
★ All doctors we interviewed love the idea and are looking forward to introducing it to their patients.
Swiss doctors we interviewed expressed great interest in the concept.
The next milestones will be
◎ MyLog14 finished the app's incentive feature in #EUvsVirus hackathon
◎ 2020/4 Introduce MyLog14 to the chief commander of epidemic prevention of Taipei city
◎ 2020/5 Release Android beta version to Google Play
◎ 2020/5 Release iOS beta version in TestFlight for the broader community test
◎ 2020/6 Implement a data-sharing mechanism to allow users to contribute the data to research institutes. The funding from research institutes will go to small businesses that are willing to provide coupons.
◎ MyLog14 will be a non-profit community app. It will be completely open-source for the community to operate and maintain in the future. After the Covid19 epidemic, we highly encourage the community to build more applications on MyLog14's framework.
The value of your solution(s) after the crisis
Helping small businesses affected by the crisis
We also build a positive enhancement mechanism in the app to motivate the users to log their data. After using the App for 14 days to record data, users can get a cup of virtual bubble tea as an incentive. MyLog14 collaborates with small businesses that are affected by COVID-19 to provide coupons. Users can exchange the virtual bubble tea into a cup of real bubble tea or coupons. It not only helps individuals to log and keep their log without sacrificing their privacy but also can help to restore the economy destroyed by COVID19.
Crowdsourcing data donation
Users can donate data anonymously with the lower location accuracy, upload to academic or research institutes, which can be used for epidemic analysis and symptom research.
Since MyLog14 leverages the power of civic engagement and respects users' privacy, there is no tracking or surveillance. We believe it can help restore the wounded democracy during the pandemic and protect it afterwards.
How We built it
The App and services are built by the MyData community, the local hub of MyData Global based in Helsinki. We have great diversity in expertise, members including NTU professors who have strong connections with medical professions, and software startups who have very good technologies in AI and blockchain. There are also great user experience researchers in the team to help test how MyLog14 can help users. The team is international, some of us are from Japan, Hong Kong, Belgium and other countries, and some of us are from Taiwan. The high diversity allows us to use local data storage, encryption, and ledger technology to build the app and make it compliant with local culture.
During the past month, we have released one prototype and five alpha versions on github. With a strong emphasis on data protection, MyLog14 is able to attract professionals with a variety of backgrounds, including technological and methodological innovation as well as privacy and security.
As for #EUvsVirus hackathon, we completed the incentive feature of MyLog14, and the Beta release is on the way. We are going to turn the idea into a useful service company our life in the post-pandemic period!
Challenges We ran into
Many people from MyData, civic tech community g0v, #CodeVsCovid19 and #EUvsVirus hackathon work together to make this project happen. We have different expertise but share the same passion. The biggest challenge for us is to build cross-disciplinary communication, for example, it is not always easy to communicate the technology behind the application to non-technical team members, including legal experts and UI/UX designers. Nevertheless, since we share the same passion and the willingness to learn from each other, we have adjusted our communication strategies to successfully overcome the challenges and create the prototype together as a family.
What we learned
Empowering the global community with highly experienced professionals with our culture and our principles can assist the wider community and make a better impact on the benefits of this App.
While exchanging ideas with European participants at the #CodeVsCovid19 and #EUvsVirus, we realized that some citizens tend to put data privacy before pandemic control, while other citizens tend to be the opposite - thinking it is okay to slightly compromise privacy to help the country to contain the pandemic.
We believe that MyLog14 will help to solve this dilemma as a great tool to strike a balance between pandemic control and privacy protection.
Built With
android
english
french
ionic
ios
iota
ipfs
japanese
javascript
love
mandrin
passion
python
typescript
Try it out
github.com
hackmd.io | MyLog14 | Together, We Log. | ['sddivid DaYuan', 'Sherry Chung', 'Tai-Ying Lee', 'Paul Wang', 'Bofu Chen', 'BlackSquirrelz Weisskopf', 'Chi-Chuan Wang', 'LIFEI KUNG', 'Dixon Siu', 'Sofia Yan', 'Tammy Yang', '道宜 張', 'shc261392 Chien', 'Chloe Chen', 'LEEL VINOD', 'Quentin Brasseur', 'Yu Ju Yang'] | [] | ['android', 'english', 'french', 'ionic', 'ios', 'iota', 'ipfs', 'japanese', 'javascript', 'love', 'mandrin', 'passion', 'python', 'typescript'] | 64 |
9,978 | https://devpost.com/software/in-virtual-hospital-we-trust-trust-my-vh | hand grasping medical equipment via oculus
Instructor medical persona explains the system and procedures
Performed medical equipment
Case Selection
Operating Room
Inspiration
COVID-19 affected Health Workers at extreme. According to Medicalxpress, %21 of the total covid-19 cases belongs to heath-workers alone! Particularly, in china this percentage is %4, while in Wuhan it is 41.5. Moreover this scale is 30.5 % in Uk, 30.5 % in Spain.Regarding 16th of April, recorded covid-19 cases among health workers are stated as more than 9.600. Since, virtual and augmented reality learning environments is my profession for 7 years for medical applications in particular, We knew that we have to do something to save not only patients lives but also to protect medical personnel as well. Zeynep designed and developed a virtual operating room including the preoperative preparation learning scenario during and after my PhD. When Ms.Tacgin was a post-doctoral fellow at Australia she noticed that they have been preferring 360 videos for the VR experience rather than completely structure virtual spaces. Producing 360 videos have offered to reach more individuals through the audience can experience it using cheaper devices. Creating a 360 video not only easier and takes less time than structuring a whole virtual environment but also they are as sufficient as an immersive VR to achieve the desired learning outcomes.
What it does
During the COVID-19 crisis, I wanted to contribute to humanity somehow. After considering my professional experience, we decided to run the project: *
Trust-My-VH ( Trust My Virtual Hospital ) *
.
As known, several countries all around the world need more medical staff; therefore, they started to graduate their students earlier than expected to overcome their healthcare requirement. These students must start to work in the field with a lack of orientation and practice. Besides the newly graduated ones, even the current employees do not enough informed with respect to the particular applications and procedures of the pandemic.
Trust-My-VH is a 360 interactive hospital that is designed to teach a hospital orientation and the pandemic procedures to the medical staff. The users of Trust-My-VH can practice the learning scenario of the pandemic in a safe zone. Trust-My-VH can reduce to have an infection at the work with having enough knowledge and experience. The represented hospital orientation scenario makes Trust-My-VH a general training tool for all medical employees. Especially, newly graduated staff can find an opportunity to learn in a secure environment.
How it is built
The previous version of this project developed using the Unity Game engine. This version was compatible with Oculus Quest VR headset. The virtual operating room was completely structured to teach preoperative procedures. (link)
In this project, the learning scenarios regarding pandemic applications and a hospital orientation was recorded using a 360 camera with the guidance of experienced medical staff. While this specialist was illustrating procedures, all the details were explained for designing Trust-My-VH.
The recorded 360 materials were stitched to provide 360 vision and the markers were added to present the theoretical information about the scenes and stages. The video stitch program of Insta and Unity Game Engine were used to add interactivity to Trust-My-VH.
Trust-My-VH were built for Android (.apk) and Oculus Quest. Thus, the users experienced Trust-My-VH either their cheap mobile phone integrated head-mounted display or a standalone HMD. We also uploaded Trust-My-VH to Youtube360 channel to reach more user.
Challenges ran into
Having the permissions from the hospital and a specialist to support was the bigger challenge for this project. Especially during the COVID-19 pandemic, video recording at the hospital had high-risk.
Accomplishments that we are proud of
I am glad to add value to the medical field with this 360 learning material. Depending on the previous research, it is possible to say that using VR to teach and learn reduce learning time and the learners can keep their attention on the subject longer than the traditional techniques.
Trust-My-VH serves to everyone even they do not have HMDs. The users become able to experience hospital orientation and pandemic procedures via Youtube360 preference. They can use this free platform to increase their knowledge and awareness.
What we learned
We are planning to apply the different version of Trust-My-VH to compare the distinguishing effectiveness of the platforms. After gathering and analyzing the data, we will be able to compare the perceived effectiveness between using a mobile phone integrated HMD and 360 web-based videos.
What's next for In Virtual Hospital We Trust (Trust-My-VH)
The scenario of Trust-My-VH can be enhanced or new scenarios can be added using similar technique and devices. We are planning to develop a 360 learning set to support both in-service training and not only limited to on-job training of the medical staff, but especially other active officers during pandemic such as policemen, traffic polices and military to train the procedures. It is also aimed to be presented to civils so that they can simply learn the procedures to obey pandemic rules such as social distance, mask usage, hand restrictions, glove usage, procedures regarding washing hands and disinfection prior to enter home and sterilize from outside conditions. It is aimed to set a machine learning to test whether they can learn the procedure with minimum of 85%. In case of success the civil will gain the access to go outside since the civil obeys pandemic rules at an expected level. Further on pandemic, in the aim to propose TRUST-MY-VH as an accessible solution, we will set this as an accessible and free material so that it can be implemented to poor geographic regions, improved by other professionals and open a space for enthusiastic young generation who wishes to be involved with the technology as a learning material.
Built With
360-camera
insta
oculus
unity
vr-box | In Virtual Hospital We Trust (Trust-My-VH) | Trust-My-VH is a 360 interactive hospital that is designed to teach a hospital orientation and the pandemic procedures to the medical staff. | ['NAZENIN GURE', 'Zeynep Tacgin'] | [] | ['360-camera', 'insta', 'oculus', 'unity', 'vr-box'] | 65 |
9,978 | https://devpost.com/software/covid-experience | Inspiration
COVID-19
is a disease caused by SARS-CoV-2, a novel strain of coronavirus that has affected the lives of millions of people. This virus is like nothing the world has seen before and is a historic event that we are all experiencing. Many people are experiencing drastic shifts within their daily lives causing uncertainty, anxiety, and fear. We began thinking
“how can we create a community that brings us together during a time of isolation?”
What it does
Voice Over Virus
is a
social media-based campaign
dedicated to bringing each individual experience together to start a conversation about the social, personal, and emotional impact of COVID-19. We encourage patients, caregivers, and anyone whose life has been affected by the virus to
share their journey and words of strength
by tagging
#VoiceOverVirus
through posts, photographs, and videos via social media in order to help and empower others who may be going through something similar. We believe that collecting
shared experiences
will provide a sense of community, and a space to
destigmatize aspects such as isolation, mental health, and sickness.
Our campaign is supported by
VoiceOverVirus.org
which serves as the
anchor for the campaign
and will be used to drive engagement through various means such as showcasing existing stories, statistics, resources, and eventually, polls that will not only engage our users but additionally inform how we can evolve and provide for this community in the future.
The website is a
Progressive Web App (PWA)
, such that on iOS and Android smartphones it can be "added to home screen" and when invoked as such is almost indistinguishable from native mobile applications.
How we built it
We began by ideating the user journey by creating user flows and sketches. From there we utilized Figma to create high fidelity screens while keeping our users at the forefront of the experience. We developed it as a PWA using Svelte UI framework and deployed it on the Firebase serverless platform. It makes use of Firebase hosting, realtime database, and cloud functions. There are
several integrations
with social media sites (Twitter, Instagram, etc), mapping API's (mapbox), and COVID-19 data APIs. Also, on the backend, it uses NodeJS for certain batch tasks.
Challenges we ran into
With a short timeline and a big goal, it was inevitable that we would face bumps in the road along our journey. Through resilience and active communication, we were able to overcome the following challenges:
Lack of access to desired API’s
Several API’s are not ready to be consumed by third party sites such as ours (lack of “CORS” headers)
Insufficient time for implementing several real-time and interactive features
Restrictive API's that allow limited freedom for utilization outside of their platform
Getting in contact with influencers to help us spread our message
Accomplishments that we're proud of
A live working website created in less than
48 hours
.
Live
working integrations
to Twitter and real-time Covid-19 data.
Initial engagement in the campaign. One of the initial Instagram posts on the campaign received
1621 likes and 42 comments
.
See the post here.
Establishing ourselves and creating content amongst several social media platforms
What we learned
We learned about the
importance of community interconnectedness
and how to encourage closeness during a time of isolation by inspiring individuals to share their experiences through text posts, photos, and videos.
We also learned the
process of creating a platform
that allows our community to engage with carefully curated user flow dynamics as well as color themes such as blue and turquoise which represent integrity and communication.
As we come from
diverse backgrounds
, members of our team learned how to improve our collaboration and communication skills as we brainstormed, designed, coded, and implemented our project.
We have taken tremendous strides since day one of our project and we have
learned to love the process as much as the outcome.
What's next for #VoiceOverVirus
We plan to continue the social campaign in order to grow the community and reach our goal of
100 posts per day over the next 30 days
. We will create seed posts to encourage people to share their story. We also plan to personally outreach to people who have shared their stories to join the community and include our hashtag. We will continue reaching out to influencers and celebrities to amplify the movement.
Various
enhancements are planned for the website
including integration with other social media sites, micro-surveys, and polls that will lead to further engagement and data collection, including positive statistics.
Built With
figma
firebase
instagram
javascript
mapbox
node.js
pwa
svelte
twitter
zeplin
Try it out
voiceovervirus.org | Voice Over Virus | Voice Over Virus blunts the impact of the current Covid-19 crisis by cultivating compassion, resilience, connections, and advice that will help humanity emerge stronger. | ['Vidhya Sagar Reddy', 'Jitesh Doshi', 'You Song H', 'Anup Mahansaria', 'Albert C', 'Maya Shenoy', 'Lyric Metroplos'] | ['Spotlight Project'] | ['figma', 'firebase', 'instagram', 'javascript', 'mapbox', 'node.js', 'pwa', 'svelte', 'twitter', 'zeplin'] | 66 |
9,978 | 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'] | 67 |
9,978 | https://devpost.com/software/remote-elderly-home-care-via-privacy-preserving-surveillance-28xtmh | Privacy Preserving Person Face Detection at Home
Home Page
Person Detection Indoors
Person Detection Outdoors
Plug and Play AI Device Discovery
Inspiration
COVID19 isolated at home many of us, including our elderly parents and grandparents. Not being able to check on them regularly elevates the risks that they are exposed to such as falls, gas leaks, flooding, fire and others.
What it does
Ambianic.ai is an end-to-end Open Source Ambient Intelligence project that removes the stigma associated with surveillance systems by implementing privacy preserving algorithms in three critical layers:
Peer-to-Peer Remote access
Local device AI inference and training
Local data storage
Ambianic.ai observes a target environment and alerts users for events of interest. Data us only available to homeowners and their family. User data is never sent to any third party cloud servers.
Here is a blog post that goes into the reasons why we started this project:
https://blog.ambianic.ai/2020/02/05/pnp.html
And here is a technical deep dive article published in WebRTCHacks. It clarifies that it is absolutely possible to build a privacy preserving surveillance system, despite popular cloud vendors making us believe that all user data belongs safely on their cloud servers:
https://webrtchacks.com/private-home-surveillance-with-the-webrtc-datachannel/
How I built it
Ambianic.ai has 3 main components:
Ambianic.ai Edge: a Python application designed to run on an IoT Edge device such as a Raspberry Pi or a NUC. It attaches to video cameras and other sensors to gather input. It then runs inference pipelines using AI models that detect events of interest such as objects, people and other triggers.
Ambianic.ai UI: A Progressive Web App written in Javascript using Vue.js and other front end frameworks to deliver an intuitive timeline of events to the end user.
Ambianic.ai PnP: A plug-and-play framework that allows Ambianic UI and Ambianic Edge to discover each other seamlessly and communicate over secure peer-to-peer protocol using WebRTC APIs.
Challenges I ran into
Challenges include selecting high performance, high accuracy and low latency AI models to detect events of interest on resource constraint edge devices.
Another challenge is taking into account user local data to fine tune AI models. Pre-trained models can perform reasonably well, but they can be improved with privacy preserving federated learning on unique new local data.
Accomplishments that I'm proud of
Ambianic.ai has been in public Beta for several weeks helping a number of users in their daily lives. Some users report success in keeping an eye on their elderly family members:
https://twitter.com/mchapman671/status/1230931722650423299
What I learned
Although the project sets ambitious goals, there seem to be sufficient enabling Open Source frameworks and community momentum to drive the ongoing success.
What's next for Remote Elderly Home Care via Privacy Preserving Surveillance
We need to work on these major areas:
Recruit volunteers in the home care community to test the system and provide feedback
Select more models to address open use cases such as fall detection, gas leaks and others
Work on implementing Federated Learning infrastructure to fine tune initial pre-trained models.
Built With
javascript
pwa
python
raspberry-pi
tensorflow
webrtc
Try it out
docs.ambianic.ai | Remote Elderly Home Care via Privacy Preserving Surveillance | COVID19 isolated at home many of us, including our elderly family members. Left unattended they are prone to risks such as falls, gas leaks, flooding, fire and others. | ['Ivelin Ivanov', 'Björn Kristensson Alfsson', 'Yana Vasileva'] | [] | ['javascript', 'pwa', 'python', 'raspberry-pi', 'tensorflow', 'webrtc'] | 68 |
9,978 | https://devpost.com/software/covidcentral-u21txv | Landing Page
Landing Page
Landing Page
Landing Page - Contact Us Section
Signup Page
Login Page
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'] | 69 |
9,978 | 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'] | 70 |
9,978 | 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'] | 71 |
9,978 | https://devpost.com/software/biozene-interactive-bioinformatics | Why Biozene?
Problem Statement
Solution
Supports all kind of devices
Biozene will help in vaccine discovery
Benefits: Helps in decoding the DNA sequences of virus
Desktop View
Mobile View
Tablet View
Several Features
Data Visualization
View DNA features
Generate plot automatically
Generate Dot Plot between sequences
Mutation rate modelling
Amino acid frequency
Translation
Decode thousands of sequences within minutes
Decode thousands of sequences within minutes
DNA alignments and their scores
Amino acid frequency
Inspiration
Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is the causative agent for the Coronavirus Disease 2019 (COVID-19). Since its first detection in December 2019 the disease has engulfed almost the entire world by spreading over more than 100 countries that resulted in the above 352,294 deaths as of 25th May 2020. This highly infectious virus spread via respiratory droplets and aerosols when an uninfected person comes in contact with an infected one. Without any drug or vaccine at sight, the world is slowly succumbing to the disease. Therefore, researchers around the world have started collaborating and sharing their research data so that with concerted efforts a cure for the disease can be developed quickly. In this challenging scenario,
Bioinformatics came out as one of the essential tools to analyze viral data as it provides vital information about the genetic makeup of the virus and also assists directly in the development of drugs or vaccines against the deadly disease.
The COVID-19 pandemic is far from over, and there is worldwide research on the development of effective diagnostic methods as well as treatments and preventable vaccines.
We wanted to automate the overall process so we came up with a solution in free time.
We took this as a challenge more than an opportunity and developed a bioinformatics application “Biozene” for researchers/scientists/anyone who is working on the DNA sequences of the virus.
What it does
Biozene is a bioinformatics application for computational biology and to perform basic to advanced tasks in a short amount of time. This application is developed considering COVID-19 in mind to help researchers/scientists or anyone who is working to fight with the pandemic.
It is a data analysis application for integrated and interactive analytics on genomics to compute and compare millions of sequences of COVID-19 DNA sequences.
Biozene can help scientists decode the genome of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that causes COVID-19 disease.
This approach could help in drug identification and vaccine development.
Features of Biozene:
1. Represent and analyze DNA sequences
2. View DNA Features
3. Protein Synthesis Analysis (Translation, Transcription, Complement, Amino Acids generation, etc)
4. Generate Genome Diagrams
5. Mutation Rate Modeling
Benefits:
1. Helps Researchers/Scientists
2. Saves number of hours
3. Free to use and supports all kind of devices
How we built it
Biozene is a SaaS application which supports all kinds of devices (responsive). The application runs on the cloud and performs tasks in real-time. We have used end to end pipeline structure to build the solution. Starting from data mining to deployment, we have used several tools, frameworks, libraries, and languages. The core language behind Biozene is “Python” and supported by the Tornado engine as a server. Below are the techniques used to develop the app:
Data Analysis and Visualization: Pandas, Numpy, Matplotlib, Seaborn, etc.
Core Language: Python.
Supporting language: Markdown, JavaScript, Bootstrap, etc.
Main Library: Biopython, and Scikit-learn.
Cloud Technology and Server: AWS, Tornado, and, Streamlit.
Additionals Tools: Git, Anaconda, Colab, Instamojo, Putty, etc.
NCBI and the University of Edinburgh are the two platforms where we collected a lot of information about the bioinformatics tools and algorithms. Biozene currently supports the “FASTA” and “GenBank” files that are available on NCBI.
Challenges we ran into
The biggest challenge of this year is the “Novel Coronavirus” itself. Biozene is deployed on free dynos on a cloud service provider and the challenge we are facing is of funds at the moment. We are not able to scale up the infrastructures on the cloud. For preparing this production level application, we used free services.
In the coming days, we would like to enhance the features like integration of Databases, authentication, malware, better UX, etc and for those integrations, we will need to upgrade the cloud services.
Apart from that, we are really excited to bring Biozene in production to help our researchers/scientists.
Accomplishments that we're proud of
We have developed this application in a very short span of time. After developing the solution, we reached out to a
few reputed research institutes and labs in India
who are working on vaccine development. They really find our solution impactful and at the moment we are exploring the opportunity to build a partnership with them so they can use Biozene and other custom analytics-based solutions. We are proud of our team who have contributed to the development of the project.
What we learned
We took this pandemic as a challenge more than an opportunity. Biozene is one of our special projects and so far and we are really happy with the outcomes and response from the community. At the moment, India is incomplete lockdown and our young and dynamic team is working from home (remote). We learned the art of work in these lockdown situations. Apart from it, on the technical and development side, we learned awesome-streamlit which is going to revolutionize the AI/ML domain in the next few months. The production level deployment also helped us learn new concepts like adding domains, add-ons, custom pipelines, etc. Learning is a continuous process and we will keep on learning going forward.
What's next for Biozene: Interactive Bioinformatics
We are adding more features in a few upcoming days to provide a robust and feasible tool to the bioinformatics community who is working to battle the deadly virus.
Coming Soon:
- Run Blast
- Machine Learning Modeling (Cluster and Regression Analysis)
- Phylogenetics and sequence motifs
Biozene is free to use so anyone can use it by their convenience. We are also developing a customized paid solution. Apart from the development, we are optimistic about the collaboration with the research labs here in India to accelerate their COVID-19-related R&D activities with Biozene and related custom solutions. We are committed and dedicated to work with anyone who is working to fight with COVID-19 to support their COVID-19 related research and discovery efforts using AI, ML, and Bioinformatics technologies.
Built With
amazon-web-services
anaconda
biopython
bootstrap
git
google-colab
javascript
markdown
matplotlib
numpy
pandas
putty
python
scikit-learn
seaborn
streamlit
tornado
Try it out
biozene.online
drive.google.com | Biozene: Interactive Bioinformatics Application for COVID-19 | Biozene is bioinformatic application for interactive analytics on genomics to compute and compare DNA sequences to speed up the vaccine discovery by reading the genetic structure of the viruses. | [] | [] | ['amazon-web-services', 'anaconda', 'biopython', 'bootstrap', 'git', 'google-colab', 'javascript', 'markdown', 'matplotlib', 'numpy', 'pandas', 'putty', 'python', 'scikit-learn', 'seaborn', 'streamlit', 'tornado'] | 72 |
9,979 | https://devpost.com/software/decentralized-uber | The PeerPool Logo
Order Page
History Page
Map Page
Become A Driver
Inspiration
PeerPool was inspired by corporate giants such as Uber and Lyft, and how they are centralizing all common transactions between the common driver persona and passenger. Uber and Lyft prevent users and drives from connecting and they collect 25% of the total amount of money the passenger pays to the driver. We wanted to remove the middleman (Uber and Lyft) and develop a new application that would have all the features of Uber (and way more) and decentralize the whole process of common ride sharing platforms. PeerPool solves the problem by removing the middleman and storing user’s data such that it’s decentralized and no one can access it other than themselves. PeerPool, A Decentralized Solution to Carpooling Services, solves the problems that many corporate giants fail to address. We decentralize this service with trustles smart contracts and eliminating the middleman, and the fees that come along with them.
What it does
PeerPool allows Users to operate a ride sharing program similar to the likes of Uber or Lyft, but quite simply, in the most efficient way possible. PeerPool is a Dapp, or decentralized application, that utilizes trustless smart contracts in order to act as the intermediary for Ride Sharing. Think of it as an automated peer managed version of a middleman. Because of this, we can provide costs for Rides that have virtually a $0 middleman fee. This is revolutionary in the sense that we can sort out disputes and move legal liability away from the Gig Workers, into trustless contracts.
How we built it
We built this decentralized application with IPFS, the Ethereum Ecosystem, ReactJS, Express, Material UI, and our brains. We used the IPFS Protocol, to store our user data such that it’s decentralized and it will prevent any external sources from accessing the user’s private information. IPFS works such that when you upload a file it will generate a hash linked to that file which we can access on any IPFS Gateway. We also utilized the Ethereum Ecosystem to securely store the smart contracts that we wrote to monitor each user. The Ethereum Ecosystem was necessary for our application to fully flower as it was needed in our proof of thought for our project. We utilized ReactJS to develop our frontend for this application, by creating multiple pages for the user and also develop multiple components that will connect to our Express Backend. We used the Google Maps API to display the routes between one point on the latitude and longitude and we developed this by using a Higher Order Component that will wrap over the initial Map component that will display the route between any two given points. For our application we needed to use the Web Geolocation API that would determine the current user’s location on the decentralized web application. We used the data from the Geolocation API and the address that the user would input (their desired location) to properly route these locations. We also used the Material UI Library to style our components and properly make our application UI and UX friendly. Our backend barebone consists of express with multiple routers for every single endpoint that would call everyone a single IPFS function, and Smart Contract function.
Challenges we ran into
One of the most challenging things that we had to do was bug fix the incredibly complicated Smart Contract backend. There was so much undocumented features that we had to pratically invent from scratch, in terms of Solidity concepts. We also had to deal with the very very very bad error handling. Node and Solidity EVM errors were extremely vague and thus difficult to diagnose. Also, the infrastructure itself was a huge pain to keep track of and build. There were so many components and processes going on that we had to really focus on to make sure it all worked together. I highly recommend looking at the Git Repo and checking the contracts (Main.sol) as well as the routes folder to just see how comedical the amount of features and processes we had.
Accomplishments that we're proud of
We are really proud of developing a fully functional Decentralized Application by only being introduced to the Ethereum Ecosystem and the IPFS Protocol shortly. Our desire for the entire application was to style it off come on ride-sharing platforms but implement it with the ever-growing popularity of blockchain. This was a lot of work for a team of 4 to finish in less than 24 hours. By developing the entire application, to arguing at midnight with our team. We had overcome many challenges that were never seen once we came up with this idea. The whole proof of thought for PeerPool was that it could be decentralized and protect the user’s data and prevent the big corporate giants from hoarding this data. With only 4 members on our team, we had delegated our team to have two people on the frontend, and two people on the backend. Our group and I are very proud of our final solution and we would’ve never seen this application to fully function.
What we learned
During this 24 hour hackathon, our team went through many challenges and overcame most of them. Let's start off with our main smart contract that was written in Solidity. Solidity’s syntax and language was built in such a way we cannot loop through the keys in a hashmap. Because our application stores all of the users on a hash map, it was NECESSARY for us to loop through all possible drivers and send them to the passenger. We need to code our own function to do this, and it allows us to access any key value pair in the hashmap. Next we implement the InterPlanetary File System Protocol, or IPFS, which utilizes the Peer-2-Peer network methodology of decentralized file sharing. We used this to update the drivers that updated their cars, and locate the latitude and longitude of our users and store it in a decentralized manner. None of us had that much experience with IPFS, but through grit and hard work we overcame this challenge with a fully functional decentralized system. Lastly, the most important concept that we learned was to call Smart Contract functions from the front-end. We had enough experience with calling Smart Contract functions in the backend, but since we needed the current user’s balance to transfer the ether, we needed to call it through the injected Web3 in the frontend. This task was very difficult, as it took away 3 hours of time and all 4 members on our team were working on this. All in all, we learned a lot through this hackathon regarding smart contracts and the IPFS decentralized protocol.
What's next for Decentralized-Uber
The application that we built with blockchain technology performs some functionality, but since we couldn’t launch and deploy it to the main network (which would cost some of our own money), it would be the next main thing for PeerPool. We would’ve also loved to add a history feature for our users, so they can review their previous transactions and possible refund them.
Built With
css3
etherium
ipfs
javascript
metamask
node.js
react
react-vis
solidity
truffle
Try it out
github.com | PeerPool - A Decentralized Solution to Carpooling Services | A decentralized Ride Sharing Application with virtually no middleman fees, and trustless smart contracts to manage liability for the workers as well as the riders, all done autonomously. | ['Aditya Keerthi', 'Daniel Yu', 'Evan Wang'] | ['First Place Prize'] | ['css3', 'etherium', 'ipfs', 'javascript', 'metamask', 'node.js', 'react', 'react-vis', 'solidity', 'truffle'] | 0 |
9,979 | https://devpost.com/software/masseyhacks-2020 | Logo.
Home screen. The user sent a recording to the backend, which returned an analysis as output.
Logs of past recordings. Green highlights improvement and consistency, while red highlights areas that need improvement.
Inspiration
According to the 2016 census for Canada, about 22.9% of all Canadians have a non-official language as their mother's tongue, and about 1.9% of all Canadians cannot hold a proper conversation in either English or French. It is crucial that these people, along with other non-native English speakers around the world, can obtain the same working and education opportunities as everyone else. Furthermore, the detrimental effects of the COVID-19 pandemic have given us much less opportunities to communicate with others and many people are still struggling to land jobs or internships, further emphasizing the need for maintaining superb communication skills. The best method to improve and maintain these skills is undeniably practice, PRACTICE,
PRACTICE
, an aspect that our project greatly helps with.
What it does
CogniTalk can analyze recordings and audio files of verbal responses to common interview questions and store these past recordings in a log to keep track of progress. After logging in with their Google/email account, the user will choose a random interview question to respond to and they can either record themselves on the web app or upload an audio file of their own recording to the question. The audio data gets passed to our Flask backend server, where a voice-analysis library analyzes it and returns an output to the Svelte frontend. This data also gets stored in a Firestore database in order for the user to keep a log of their past recordings. This log of recordings gets displayed in a table that highlights areas of success and improvement.
How we built it
Our frontend is built with SvelteJS and our backend is built with Flask. We used an existing audio-analysis library that runs in the backend to help us analyze audio data. Finally, Firebase authentication was used for logging-in and signing-up users and Firebase Firestore was used as a database to store the performances of the past recordings.
Challenges we ran into
As only a team of 2, we faced a major struggle of accomplishing all our desired tasks in time. One of us (Eric) worked on the entire frontend aspect and the other (Borna) worked on the entire backend aspect of the project, meaning that both of us had a significant portion of the project to contribute to. One example of a major challenge with our code was trying to get our backend to analyze audio with only a URL to give as input (case where the user records with the web app). We spent countless hours trying to figure out how to use that URL to store the audio data in a .wav file. Another major issue we faced was trying to return the output to the frontend and getting it stored in Firestore. We struggled to link our frontend and backend using our minimal knowledge of web requests and work with the Firestore API to store data in a complex format. However, we managed to pull through with each of our bugs and end with a successful project.
Accomplishments that we're proud of
As mentioned before, we are proud to have overcome nearly all of our bugs and end the hackathon with an almost fully-functional web app for others to currently use. We have also learned a couple of new technologies, including working with audio files, and greatly improved on existing skills, such as using web requests, during our hacking period.
What we learned
Apart from the new technical skills we gained while hacking, both of us learned about the advantages and disadvantages of being a duo rather than a full team of 4. Most notably, we have learned that although being in a duo requires more work and coding contributed from both teammates, duo teammates have much more control over their hacking decisions and can each gain much more satisfaction with the project and more hacking experience.
What's next for CogniTalk
One of our future goals for CogniTalk is to develop a much more rigorous algorithm to a recording's overall performance and output this deeper analysis to the user's recording logs. Furthermore, we have also thought about creating our own speech-analysis model with machine learning for better accuracy on the crucial speech information.
Built With
css
firebase-auth
firebase-firestore
html
javascript
my-voice-analysis
python
svelte
Try it out
github.com
cognitalk.tech | CogniTalk | Practice and improve your communication skills or prepare sufficiently for interviews with CogniTalk. | ['Eric Xiao', 'Borna Sadeghi'] | ['Second Place Prize'] | ['css', 'firebase-auth', 'firebase-firestore', 'html', 'javascript', 'my-voice-analysis', 'python', 'svelte'] | 1 |
9,979 | https://devpost.com/software/tbd-21iqa9 | Domain:
mentalsafe.space
therapy.space
Try it here
Inspiration
Mental health is becoming an increasing problem in the world, especially for students in school. Poor mental health, untreated, can lead to a whole host of terrible consequences including self-harm, depression, suicide, and more. That's why we've created MentalSafeSpace.
What it does
MentalSafeSpace uses state-of-the art machine learning technology to detect mental health flags in text messages early on so those who need help can receive the support they need, when they need it. MentalSafeSpace does this in a beautiful, easy-to-use, room-based chatting system that connects anyone, worldwide over the internet.
How we built it
We built this app with a few different technologies. Firstly, HTML, CSS + Bootstrap, and JS for the front-end chat interface. Next, we used Node.js, express, socket.io, and MongoDB for the back-end. Finally, the star of the show, we used a machine learning model, trained on the Google Cloud Platform to perform sentiment and risk analysis on text messages.
Accomplishments that we're proud of
We built a fully functioning app in less than 24 hours that we believe is a starting point for a useful solution that will help people and potentially save lives. We also learned many new technologies and how to intertwine them together as a team.
Challenges and what we learned
We decided to challenge ourselves for this week's hackathon. Our goal was to learn and use technologies that we've never used before. Our front-end developer, Samer, used Javascript for the first time to create this application. Our back-end developer, Matthews, learned Express, Socket.io, and MongoDB in the process of creating MentalSafeSpace. Our machine learning expert, Rohan, used GCP for the first time to train the model.
What's next for MentalSafeSpace
We want to improve this platform and make it a real product that schools and organizations can use to help students and other people.
Built With
bootstrap
express.js
google-cloud
moment.js
mongodb
node.js
socket.io
Try it out
github.com
mental-safe-space--rshetty.repl.co | MentalSafeSpace | MentalSafeSpace helps schools and organizations to find and treat at-risk individuals | ['Matthews Ma', 'Rohan Shetty', 'Samer Rustum', 'Harry Kim'] | ['Third Place'] | ['bootstrap', 'express.js', 'google-cloud', 'moment.js', 'mongodb', 'node.js', 'socket.io'] | 2 |
9,979 | https://devpost.com/software/omnisyncr | Inspiration
Due to the current COVID-19 situation, everyone is stuck at home. Fortunately, we can still browse the internet and have fun playing with friends. Our group had started watching anime and movies together over discord streams, but the experience was rarely smooth. Video quality is compromised and the stream is often paused for each person, then we must restart and have someone else load the video if the streamer leaves. We wanted to make a chrome extension that will fix that, allowing everyone to watch the video together while each displaying the best quality possible.
What it does
Our chrome extension allows people to create and join rooms, following the stream of the party leader. Leadership can be passed and friends can be added, but the core of the project is that everyone's video will be in sync with the leader. When they pause/play/skip/buffer, everyone follows that timestamp. People can also go out of sync to rewatch moments on their own and then resync when they want to.
How we built it
The hack is a chrome extension written in javascript. The frontend was created using HTML and Vue.js, along with MongoDB as a persistent database. NodeJS was used in the backend and is hosted on a digital ocean server, to allow people to join rooms. Firebase (Cloud Firestore) is used for realtime communication between the chrome extensions, and interactions between the extension and the chrome tab were handled in javascript.
Challenges we ran into
There were challenges in communication between the different parts of the hack, getting the extension to have full control over the video, lack of sleep, and getting the project to run the same on everyone's laptop. It was also extremely hard to test this application, as it takes multiple people for a proper test, and debugging requires tracing print statements from laptop to laptop.
Accomplishments that we're proud of
This project had multiple firsts for us as it was the first time we created a chrome extension, first time using node.js and first time using digital ocean. We are very happy with the outcome and will probably be using this extension.
What we learned
Even the simplest ideas can be very challenging to implement. The extension was unexpectedly one of the most difficult projects we've worked on. We weren't able to sleep but we did learn a lot more about chrome extensions.
What's next for OmniSyncr
Honestly, we're looking forward to trying this out in our discord.
-- The original demo was rushed because we found a bug with redirecting very close to the deadline. It was all in one take so please contact us for any clarifications, it's here
https://www.youtube.com/watch?v=tnrQmosaqgg&feature=youtu.be
. We retook it after fixing nithin's internet.
Built With
chrome
digitalocean
firebase
javascript
mongodb
node.js
vue.js
Try it out
github.com | OmniSyncr | Synchronized video extension built to bring people together | ['Nithin Muthukumar', 'Noor Nasri', 'Daniel Liu'] | ['Best Entertainment Hack'] | ['chrome', 'digitalocean', 'firebase', 'javascript', 'mongodb', 'node.js', 'vue.js'] | 3 |
9,979 | https://devpost.com/software/f-filter | Inspiration
Nowadays, the most popular form of communication is through social media. And the most popular social media apps all revolve around photo sharing and image thumbnails (Instagram, Facebook, Twitter, etc.). Not everyone has a license and certification to Photoshop, and not everyone can afford to spend money, time, or effort to fine-tune their images.
This is how F-Filter was born. The F stands for forever free, friendly, flexible... and fantastic.
What it does
F-Filter aims to have the flexibility of apps like Photoshop with convenience, simplicity, and inclusiveness. You can apply image adjustments by navigating through a list of filters, or just simply speak to F-Filter to get what you want.
How I built it
The majority of F-Filter (so far) lies in the front-end, based on React. The Canvas API allows for the manipulation of each pixel's RGB values. I did research on algorithms to provide filter options such grayscale, tint, and temperature.
The speech functionality
only works with Google Chrome
due to the Web Speech API only working on Google Chrome. I inputted a grammar file to make the browser put more priority on relevant commands (e.g. "brighten", "warmer", "red", "turquoise").
The back-end is relatively simple; node.js running express for the endpoints and mongoose to manage data in my MongoDB Atlas database. So far, the server allows users to store filters as codes and later retrieve filters from their codes.
Challenges I ran into
only Chrome supports the Web Speech API, I had to come to terms with that
Heroku was a big hassle to get working due to the set-up of my GitHub repository
Accomplishments that I'm proud of
Setting up the voice commands to work pretty fast!
Adapted to working in a new environment: TypeScript, Neovim
What I learned
TypeScript is super fun but sometimes a hassle to sort out (but it's worth it)
I should prepare more on my codebase structure so that deploying my app to Heroku, for example, becomes easier for future projects
What's next for F-Filter
So much more:
way more image adjustments! e.g. colour inversion, sharpen/blur, etc.
optimization for larger image files
a mobile app, given that most people take and share photos from their phones
an image classification endpoint that allows users the option to get an auto-filter based on the contents of their image
a social network where users can save and share filters with ease.
a better UI
Built With
canvas
express.js
mongodb
mongoose
node.js
react
rest
typescript
webspeech
Try it out
github.com
f-filter.now.sh | F-Filter | Perfect photo filters within seconds. | ['Peter Lin'] | ['Best Lifestyle Hack'] | ['canvas', 'express.js', 'mongodb', 'mongoose', 'node.js', 'react', 'rest', 'typescript', 'webspeech'] | 4 |
9,979 | https://devpost.com/software/preview-ld3wku | preview
Built With
javascript
Try it out
github.com | preview | quick no-click website previews | ['Brad Boratto', 'Fawn Barisic'] | ['Best Beginner Hack'] | ['javascript'] | 5 |
9,979 | https://devpost.com/software/covidmaps | Inspiration
The last few months have been quite a shock to the world as COVID-19 has spread around the world at an unprecedented rate. With growing fears about a potentially even more disastrous "second-wave" hitting the globe, our team decided that we should try and find a novel way to help people flatten the curve.
What it does
One of the best ways to fight the spread of COVID is through social distancing. But social distancing can be a challenge. Lots of people go on walks and runs everyday, and end up getting closer than the recommended six feet of distance from other people. Toronto has resorted to increasing the width of their sidewalks, but it's an expensive solution and doesn't completely eliminate the problem. Our webapp aims to solve this problem by providing the public with real-time pedestrian traffic information, so that people can time their walks and choose routes in ways that minimize the amount of close contact.
How we built it
Our app works by having drones scan public roads and paths to detect the amount of people present at a given time. The detection is done through a PyTorch CNN model trained to detect humans from an aerial point of view. The data from the CNN is piped to a backend server which maintains running averages of the amount of people at every location reported by the drone. This data is then sent to our frontend app which lets us generate heatmaps of pedestrian traffic. Furthermore, we also utilized the Here API and Google Maps API to enable users to get directions that minimize the number of people they could run into.
Challenges we ran into
Linking together the video streams from the drones with our ML model, with our backend database, and with our frontend webapp took a lot of planning and teamwork.
Accomplishments that we're proud of
We're really proud that we managed to link all four of these technologies together in such a short duration.
What's next for CovidMaps
At the moment, we've only used a single drone for testing. Obtaining more drones would be a next step for CovidMaps.
Built With
aiohttp
android-studio
dji
gnupg
google-elevation-api
java
material-ui
python
pytorch
react
socket.io
vincenty
Try it out
covmapsbackend--cristianbicheru.repl.co
github.com | CovidMaps | Real-time pedestrian traffic mapping using drones. | ['Kevin Gao', 'Trevor Du', 'Aryan Afrouzi', 'Cristian Bicheru'] | ['Best COVID-19 Hack'] | ['aiohttp', 'android-studio', 'dji', 'gnupg', 'google-elevation-api', 'java', 'material-ui', 'python', 'pytorch', 'react', 'socket.io', 'vincenty'] | 6 |
9,979 | https://devpost.com/software/nanime | Inspiration
Being a weeb and constantly forgetting names of animes
The
relevant xkcd fnder
What it does
NANIme?! lets the user input a brief description of an anime and generates a list of names of potential animes matching that description.
How I built it
Term frequency–inverse document frequency (TF-IDF) calculations over a database of synopses of animes provided by
https://www.animenewsnetwork.com/
.
Challenges I ran into
It was a bit difficult to retrieve data from anime sites.
Accomplishments that I'm proud of
Managed to actually get this project working. I've already used it once to find an anime that I forgot the name of (it was Kokoro Connect).
What I learned
What's next for NANIme?!
I plan to get it on a webserver, increase the size of the anime database, and add checking of synonyms/related words to increase the accuracy of predictions.
Built With
python
Try it out
github.com
nanime.herokuapp.com | NANIme?! | Finds the names of animes that you may have forgotten based off of their descriptions | ['Ruyi Li'] | ["Judge's Choice"] | ['python'] | 7 |
9,979 | https://devpost.com/software/bootleg-telekinesis | Detection and Translation of hand
Inspiration
I wanted to be able to do things in 3D and VR without having to use a controller
What it does
Using just your hand (and a webcam) you can take full control of a game with just your hand. In the example I used, I controlled an arm in a 3D VR game. You can move it up, down, left, right, as well as front and back, and finally grab items.
This kind of technology can eventually be used in the medical field (for example with surgeries) as well as assisting people with various disabilities and impairments (helping them learn).
How I built it
I built it using OpenCV to isolate the hand and obtain raw data - from there I used python to figure out where the hand was (coordinates), how far it is, and what symbol it is showing (grabbing).
Challenges I ran into
Connecting Python and Unity was rather difficult to do with the given permissions for file and data parsing
Accomplishments that I'm proud of
This is my first time using OpenCV and controlling my computer without any physical input.
What I learned
I learned how to use part of the OpenCV library
What's next for Bootleg Telekinesis
I hope to add more functionality with multiple hands
DOMAIN FOR DOMAIN AWARD
http://crewdragonisin.space
(lol)
Built With
opencv
python
unity
Try it out
github.com | Bootleg Telekinesis | Control 3D and VR games using just your hand (no controller) | ['Andrey Starenky'] | ['Best Domain Registered with Domain.com'] | ['opencv', 'python', 'unity'] | 8 |
9,979 | https://devpost.com/software/twitter-hashtag-heat-map | The MongoDB cluster used to power the heatmap
The uses of #Happy around the world
Inspiration
Around the world today, there are many movements that have united the population in an otherwise stressful period of time. A very popular way of expressing this unity is by using hashtags on twitter. Large groups of people use a certain hashtag to show their support for a particular movement. We wanted to get data on where these movements are taking place by gathering location data on the tweets.
What it does
You can input any hashtag into the program and it'll upload all relevant tweet locations to a MongoDB database. You can then use the frontend graphics program to view the data in a nicely displayed map
How I built it
This Project was built with a combination of the Twitter API and MongoDB. The language of choice was Python since it has two readily available libraries, TweePy and PyMongo. A cluster was set up through MongoDBs AWS servers and was configured to accept collections of tweet information. The tweet-fetching program will leverage the Twitter API to fetch all relevant tweets and upload them to the MongoDB cluster. Finally, the graphics frontend will fetch the tweet data stored in the MongoDB cluster and display it to the user in a nicely laid out map.
Challenges I ran into
Getting the Twitter API to find the tweets that we want
Parsing the tweet info into a format that MongoDB will accept
Accomplishments that I'm proud of
First time leveraging a database in a project
First time using the Twitter API
What I learned
How data is retrieved and stored in APIs
How databases help store data
What's next for Twitter Hashtag Heat Map
The next step for the Hashtag Heat Map is server deployment. We were not able to get a domain and hosting in time for this Hackathon but the project was built with that in mind. The program that searches for the tweets themselves can be hosted server-side and be coded to handle multiple users at once. The graphics frontend can be turned into a website that leverages Google Maps (for more accurate location information) and present the user with a nice and easily accessible interface.
Built With
mongodb
pygame
python
twitter
Try it out
github.com | Twitter Hashtag Heat Map | Find out where popular hashtags are being used around the world! | ['Miraj Ismail', 'Armaan Randhawa', 'Dimitrios Christopoulos', 'Tanzim Hossain'] | ['Best use of MongoDB Atlas'] | ['mongodb', 'pygame', 'python', 'twitter'] | 9 |
9,979 | https://devpost.com/software/friendly-fire | A two-player game of two minigames designed for casual, relaxed play to build connections between people stuck at home during the coronavirus pandemic
Built With
pygame
python
Try it out
github.com | Friendly Fighters | A game of minigames to battle those you're with during the coronavirus, in a positive manner | ['Bansari Patel', 'Akib Shamsuddin'] | [] | ['pygame', 'python'] | 10 |
9,979 | https://devpost.com/software/left-on-seen | Wanna play a game?
Inspiration
Games like "Emily is Away", "Vee is Calling", and "Doki Doki Literature Club" definitely inspired us to make our own. With lots of user interaction, beautiful graphics and a storyline that pulls you into the game, you can clearly see how heavily "Left on Seen" is influenced by the aforementioned games. Though we did draw ideas from other "dating simulators" we tried to throw in our own twists to make the game as original and unique it can be.
The Game:
"Left on Seen" follows a lonely girl who browses through dating apps while taking the subway in the early hours of the morning and tries desperately not to fall in love and even more desperately not to get left on seen.
The Process:
The creation of this project was pretty spontaneous. It started out of boredom but quickly became something serious that we wanted to work on.
Challenges:
Many times when people see games where your interactions with others affect the story, they don't factor in how messy a story like that can be. We had the same mindset until we tried to make this game. Stories are hard enough to build already, so adding even more complication into that mess was a struggle. Another big challenge was the time crunch, although that can go without saying in any hackathon.
Accomplishments that we're proud of:
While a time limit is always going to cause problems, most hackathon games don't really have to worry about assets. If you're using Unity, you can just download some from the store, and most sane pygame users download sprites from the internet. Although it caused a bit of trouble, we couldn't be prouder of the pixel art in this game that we made from scratch.
What we learned:
Get on top of things quickly. If you can't manage yourselves, it makes it a whole deal harder to get anything done.
What's next for "Left on Seen":
With more time, patience, and a lot more caffeine we'd work towards adding colour to the graphics, more complex storylines with different endings, and more boys to swipe right on :). ( + actually finish it )
Built With
pygame
python
Try it out
github.com | l e f t o n s e e n | We all know one of the worst feelings in the world: being left on seen. Follow a girl as she travels through the subway in the early hours of the morning and try to avoid being left on seen. | ['Shengbuo Fang', 'Angela Wang', 'Eston Li'] | [] | ['pygame', 'python'] | 11 |
9,979 | https://devpost.com/software/aroundme-n6wzr4 | Inspiration
Going for a walk is one of the best ways to get some fresh way and reconnect with the world around you, but with a social pandemic going around we thought why not give each user unique routes protecting them and allowing them to see more of their neighborhood.
What it does
Around Me creates personalized routes for you to explore your community all while making sure that no two users get pointed on the same path or destination. With Around Me you can achieve your target walking distance, visit places in your community, and distance yourself from others all at once.
How I built it
we built this app using the Twilio API for our SMS powered front end and flask as our backend that connects the text messages information to the google directions, maps, and places API to return clean directions to and from your destination. In addition, by implementing MongoDB we were able to store routes that were currently being used and re-route others accordingly.
Challenges I ran into
- Setting up the flask backend
- Receiving the messages from the Twilio API
- Working as a team over calls and collaborating on the same file at once
Accomplishments that I'm proud of
- Making a working app
- Learning how to all use one language
- Learning how to collaborate over git
What's next for AroundMe
adding a picture that helps to show
Built With
flask
google
google-directions
mongodb
python
Try it out
github.com | AroundMe | With social distancing keeping everyone inside we made a program that gives each person a unique walking route so that they can explore their neighborhood while distancing from others. | ['Ankit Gupta', 'Arianne Ghislaine Rull', 'Jana Jandal Alrifai'] | [] | ['flask', 'google', 'google-directions', 'mongodb', 'python'] | 12 |
9,979 | https://devpost.com/software/cubie | Main menu scene
Enemy cube explodes when destroyed
Enemy cubes following you
Score/GameOver scenes
Inspiration
Inspired by Dani. A youtuber.
How to play
A first person game where you shoot cubes with your pistol. Your main goal is to achieve the highest score you can get by destroying the enemy cubes without losing to them.
How I built it
Built with C# and Unity
Accomplishments that I'm proud of
I'm proud that I somehow managed to make the game look nice (just by messing around with the post processing layer and volume). This game is also bug-free.
Challenges I ran into
Unity has crashed a lot of time on me, mainly due to lack of ram. There were a lot of bugs related to the gun, animation, enemy ai etc.
What I learned
I'm slowly getting used to Unity and C#. I've been using Unity for about 2 weeks now and I've gained many experiences making games on Unity.
What's next for Cubie
The game can be improved in many ways, such as adding different levels, improving the weapon animation, adding different types of enemies based on their level. I might plan on adding music to entertain the player.
Built With
c#
unity
Try it out
github.com | Cubie | First person shooter | ['Michael Yang'] | [] | ['c#', 'unity'] | 13 |
9,979 | https://devpost.com/software/the-abyss-a-text-based-game | my brain
its a text-based game
with python and hard work
tiredness
creating something
brute-forcing the code is very time consuming and looks messy
nothing
Built With
python
Try it out
repl.it | The Abyss - a Text Based Game | Have you ever wanted to shop in the void's greatest (only) supermarket? Well now you can! | ['Ashley Bi', 'Niksha v', 'Jeslyn Lu'] | [] | ['python'] | 14 |
9,979 | https://devpost.com/software/hear-me-out-wj5bte | Our HTML UI
HearMeOut Model
Hear Me Out
A web app that allows one to listen to a slideshow in the voice that one intends.
HearMeOut is a project dedicated to making a better, and more beneficial online education system. Through HearMeOut, the teacher/instructor's voice can be cloned, allowing the computer to present a slideshow in a similar manner to the teacher/instructor. In the wake of the novel Coronavirus, many countries have begun to use online learning tools to support children. The goal of HearMeOut is to benefit children who are auditory learners, and may depend on the teacher/instructor's voice.
Additionally, HearMeOut can also be used for children with special needs, who may not be comfortable speaking or presenting presentations. This allows such children to get the support they need and the education they require, through the help of AI and the web app.
What Inspired Us
Since the start of the social distancing measure, schools have been closed and the education system has been moved online. We noticed many of our teacher were preparing lessons on slideshows, which were quite different from the usual lesson format that is used in classrooms. We realized that there was an auditory component missing from the lessons, so we decided that needed to be fixed, which inspired us to create HearMeOut. This allows students like us to feel like our teacher is presenting to us, similar to a classroom, without having the teacher record the entire lesson.
What We Learned
We learned many new skills during this project, which included creating python web apps with Flask, using REST APIs to get useful information (specifically from a Google Slides presentation), CSS skills, and forms in HTML (with JS integration).
How We Built It
We started out by splitting up the work into front-end and back-end. The front-end work was with the HTML, which included CSS styling and some JS with the forms. The back-end work included using the Voice-Cloning Colab notebook, which uses Tensorflow to learn the spoken sample, to create the Text-to-Speech and using the Google Slides API to get the text from all slides of a presentation as a string, so that it could be inputted into the Voice-Cloning TTS.
Challenges We Faced
One of the biggest challenges we faced was getting the text from a presentation as a string. At first, we tried using Google Scripts with the HTML to get the text, but this did not work as hoped. The second attempt for this was more successful, as Google Slides API was used, to get the information from the json produced by the GET call by narrowing down attributes until the correct one was reached.
Another big challenge we faced was connecting the various parts of our project, which were the HTML UI, the findtext python file, and the Voice-Cloning Colab Notebook. Unfortunately, connecting the back-end pieces to the HTML proved quite difficult and we were unable to do this in time.
Built With
colab
css
html
javascript
json
python
slidesapi
tensorflow
tts
voice-cloning
Try it out
github.com | HearMeOut | An AI-based, education solution for auditory learners to help those affected by COVID-19 and the subsequent online learning system. | ['Arnav Gupta', 'Harshul Gupta'] | [] | ['colab', 'css', 'html', 'javascript', 'json', 'python', 'slidesapi', 'tensorflow', 'tts', 'voice-cloning'] | 15 |
9,979 | https://devpost.com/software/arlabs | Creating the 2-D Collision Simulation in Unity
Collision Simulation Demo in Unity
1-D Kinematics Friction Simulation Demo in AR
Inspiration
Due to COVID-19, many students are receiving inadequate science education. A proper scientific learning curriculum always includes experiments and labs, to teach students how to test hypotheses for important concepts, collect data, and develop analytical inquiry. Because online learning lacks these experiments, students are unable to develop these essential skills.
What it does
ARlabs uses augmented reality to simulate experiences while allowing user interactivity, emulating actual scientific experiments. By placing a target image, the simulation will lock onto a plane and generate the experiment. The user can interact with the lab experiment.
How it was built
ARlabs was built using the latest Unity physics engine and Vuforia Augmented Reality engine. Experiments were carefully designed to match essential concepts in middle and high school physics. After creating a realistic physics model, the simulations were placed on a target surface for augmented reality, and deployed onto Android for testing.
Challenges
Since Unity was developed for game creation, functionalities for developing an app were less intuitive. Creating a user interface was especially difficult, since the simulations were developed in three dimensions and the user interface had to be overlayed.
Accomplishments and Future Work
ARlabs succesfully created scientific experiments that students can use anywhere through augmented reality on their phones. ARlabs plans to increase the amount of experiments and design a better user interface. Moreover, graphical elements would allow users to edit properties of lab experiments without Unity. After finishing classical mechanics, ARlabs plans to introduce labs in electromagnetism, chemical reactions, and optics through augmented reality. ARlabs seeks to democratize scientific education through augmented reality, allowing students to learn anywhere and anytime. We hope that this will become a useful tool for educators and learners everywhere.
Built With
android
arcore
arkit
c#
gradle
unity
vuforia
Try it out
drive.google.com | ARlabs | Scientific labs in AR for students. Learn Anywhere, Anytime. | ['Andrew Z L', 'Linus Chen', 'Kevin Wan'] | [] | ['android', 'arcore', 'arkit', 'c#', 'gradle', 'unity', 'vuforia'] | 16 |
9,979 | https://devpost.com/software/out-of-this-world | Flight to Orbit Stages: Other SpaceX Missions
Flight to Orbit Stages: NASA's Process
Flight to Orbit Stages: SpaceX and NASA's Falcon 9’s launch of Crew Dragon’s second demonstration (Demo-2) mission
Flight to orbit process: Launch stage detected by the algorithm
Algorithm detecting that a Flip Maneuver has happened
Algorithm detecting a Dragon spacecraft, and that Dragon separation has happened
Algorithm detects that the Dragon spacecraft is proceeding to the International Space Station (ISS)
Algorithm detects that the Dragon spacecraft opens the Astronaut Capsule to attach to the International Space Station (ISS)
Close up of previous image (“DRAGON OPENS ASTRONAUT CAPSULE TO ATTACH TO ISS”) to provide more training data to the algorithm
Algorithm detecting that a Payload Separation has happened
Algorithm detecting that a Stage Separation has happened
Inspiration
This project was inspired in light of a recent international event, which was the highly-anticipated SpaceX and NASA combined mission
This project served as a stepping stone for furthering my interest in technology and aerospace, in order to thoroughly understand these two inter-related fields, along with continuing humankinds' endeavours in the fields of technology and aerospace.
What it does
This system/algorithm identifies the stages of space flight, specifically the flight to orbit stages, that the spacecraft undergoes.
How I built it
Tensorflow libraries
Google Colab notebooks
Python
Challenges I ran into
GPU's setup
Finding training and testing data
Achieving a high accuracy rate in the algorithm
Accomplishments that I'm proud of
Having a high accuracy rate (90%) for the machine-learning algorithm, with the given training and testing data
What I learned
Understanding the technical aspects of Tensor flow libraries and Google Colab notebooks
This was done through following tutorials, along with asking help from mentors, in order to develop this interactive platform
What's next for Out of this World!
Providing more training data such as image datasets of additional companies and agencies in the field of space exploration, other than SpaceX and NASA
Reducing the limitations in the algorithm (e.g. identifying spacecraft from a wide range/variety of companies and agencies)
Collaborating with educational platforms (e.g. Khan Academy, Udemy, and Skillshare) to teach others about and introduce them to the field of space exploration, specifically the phases needed in the flight to orbit process
Built With
python
pytorch
tensorflow | Out of this World! | This project is based off of a series of machine learning algorithms, that are able to identify the flight to orbit stages, which a form of spacecraft is undergoing. | ['Hargun Bhalla'] | [] | ['python', 'pytorch', 'tensorflow'] | 17 |
9,979 | https://devpost.com/software/trustworthy | FictionFilter
We use NLP and Machine Learning technology to detect the veracity of articles, fact-check claims made inside them (cross-referencing sites from across the internet), and help people determine whether their news source is trustworthy.
How it Works
Our approach is multi-pronged.
First, we use an LSTM to classify the trustworthiness based on the structure and words used. This technology is state-of-the-art when it comes to text classification, allowing us to predict the trustworthiness of even individual sentences without relying on potentially biased and incomplete lists of "which news sites are credible," especially since many news sites contain a mixture of truthful and unreliable content.
In addition, we use an NLP-driven approach to isolate the most important claims in the article in a unique way via extractive summarization, allowing us to find the most important statements in the article and search fact-checkers for them. This means if the article makes a claim that shows up on Snopes, Politifact, or a host of other verified fact-checking websites, we'll be able to get the truth value.
Robust
Because we use powerful and robust techniques to extract the text from the site given to us and verify it server-side in addition to using one of Google's search APIs, we have multiple measuring sticks with which to determine the trustworthiness of an article. This helps protect us from source bias or discrimination against any one particular writing style by using multiple methods together.
Relevant
The Internet makes it easier and easier for people to share the truth. Unfortunately, it has a similar effect on lies. Fake news spreads rapidly, as does satire disguised as truth. This can broaden the widening gulf in our political climate by reinforcing echo chambers to not even care about reality. In addition, dangerously misinformed citizens make worse decisions. By arming people, especially the less media-literate, with the tools they need to ensure the media they consume is accurate, we can create a more informed populace, better able to combat hoaxes about topics like COVID-19 and other current events.
Technology we Used
We used TensorFlow and Keras to create our LSTM neural network, as well as the powerful nltk library for preprocessing. We also used an extractive text summarization technique to give readers digestible chunks of information about the articles they're reading.
Try it Out!
https://fictionfilter.andrechek.com/
Code
https://github.com/antigluon/trustworthy
Built With
ai
css
flask
html
javascript
jupyter-notebook
keras
machine-learning
natural-language-processing
nltk
python
tensorflow
Try it out
github.com
fictionfilter.andrechek.com | FictionFilter | We detect the trustworthiness of articles by using machine learning and cross-referencing fact checkers with NLP techniques. | ['Eric Andrechek', 'Jainil Shah', 'Rabab A'] | [] | ['ai', 'css', 'flask', 'html', 'javascript', 'jupyter-notebook', 'keras', 'machine-learning', 'natural-language-processing', 'nltk', 'python', 'tensorflow'] | 18 |
9,979 | https://devpost.com/software/stopthevirus-1cjqen | Opening website
Reasons to help
Donation form
Inspiration
Seeing as how in just a short while, the Covid-19 has impacted each and everyone's lives. I know there are a lot of donation websites out there, but a lot of them are not visually appealing, give correct information, and have a user-friendly user interface. I wanted to create something that gives hope that we all can fight this through together.
What it does
This site has links to educate the public. The links take you to the World Health Organization's Covid-19 website as they are trying to educate that we should always follow their website for the most up to date and most accurate information. The website also has a donation form page for people to help further by not only social distancing, but also by providing Covid-19 relief funds.
How I built it
I used html, css, and bootstrap to create the site.
Challenges I ran into
Adding a donation form to the website was a bit tricky. Currently, I'm not sure about the security aspect of the form, so I would like to next spend time working on making the form more secure. Another challenge I ran into was creating a visually appealing site in a short amount of time. If I had more time, I would have conducted user studies to see what most people find appealing and user friendly.
Accomplishments that I'm proud of
I am proud that I was able to educate my audience, provide relief to the sick and our health care workers, and create a user-friendly UI for users. I also like how my website is more inspirational and not daunting as many donation websites can be.
What I learned
I learned that we all have our part in helping #STOPTHEVIRUS. Most of us are sitting at home practicing social distancing, so it feels like we are not doing much, but we are. I wanted to do something from my home that can help people, which was to create a donation and information giving website.
What's next for #STOPTHEVIRUS
I would like to make the website more secure, scalable, and maybe create a mobile app to further the #STOPTHEVIRUS campaign.
Built With
bootstrap
css
html
javascript
Try it out
stopthevirus.tech | #STOPTHEVIRUS | To create an application that is visually appealing, user friendly, and help educate so users are inclined to donate to the Covid-19 pandemic. | ['Tarj Mecwan'] | [] | ['bootstrap', 'css', 'html', 'javascript'] | 19 |
9,979 | https://devpost.com/software/masseyhacks-vi | Probably not gonna finish, but there's a lot of code that is there.
Built With
c
glfw
Try it out
github.com | MasseyHacks VI | tower defense | ['Kevin Zhang'] | [] | ['c', 'glfw'] | 20 |
9,979 | https://devpost.com/software/shepard-run | Inspiration
We are familiar with fairytales and similar stories, so we decided to create a game based around a shepherd trying to regain his flock of sheep. This idea was chosen because it is a rather calming and peaceful premise, yet it is still entertaining.
What it does
The game lets the player take control of a shepherd who, at night, is attempting to return his flock to his farm. The player needs to walk up to the sheep to collect them and then walk back to his farm to deposit them. All the while, wolves will be spawning near him, wolves that he'll have to scare off, and these wolves will try to attack him and scatter his collected sheep again. The player only has a limited amount of time to collect as many sheep as possible.
How we built it
We used java with swing and object-oriented programming. We worked as a team and divided up the work, each person working on a different class. Sometimes we collaborated on one specific issue if it was especially difficult or unexpected. We used open-source sprites.
Challenges we ran into
Most of our team was unfamiliar with using coding using different classes in different files, so new had to come together and pool our knowledge. We also weren't aware of some of the features of java and swing that we needed, so we had to look online for advice and documentation. Working with Github and having all the members of our team isolated due to quarantine also made the collaboration more difficult and made progress slower because it was harder to all work at the same time. As always, time was a challenge and we wish we could have worked on this more.
Accomplishments that we're proud of
We are proud of the physics and collisions, using a bit-mask, that we implemented into the game. The organization and object-oriented nature of the game is also something we are proud of, along with the size and scale fo the map. Overall, we are proud of the game itself and how complete we were able to make it.
What we learned
We learned that it is more difficult, but certainly not impossible, to work well as a team, even isolated from one another. Most of us learned how to compile and use multiple java files at once, and we all learned a lot more about the features and flexibility of java and swing, also how useful object-oriented programming is when trying to add new features. Our coding habits and organization have also improved since we have also learned to plan out the game properly before coding it.
What's next for Shepard Run
We are looking to polish this game further and realize our original intentions with it more fully. With more time, a better wolf/enemy AI will be made, extra sound effects added, and visuals updated to make things more consistent and visually appealing.
Built With
java
swing
Try it out
github.com | Shepard Run | You are a shepherd who has woken to find that all of your sheep have run away. You must now go out and recover your sheep but be careful, they say wolves roam around this farm. | ['Arsalaan Ali', 'Yang Li', 'Matthew Mao', 'Andy Liu'] | [] | ['java', 'swing'] | 21 |
9,979 | https://devpost.com/software/app_data_cloud_saver | About
Tired of losing save files for you games? Or maybe you just want to upload your notes everytime you finish working with certain app?
Using this app you can your executable and file you wish to save to the dropbox cloud, and everytime you close it, it just uploads straight to your dropbox drive.
Disclaimer:
This project was made for hackaton, late at night, therefore code is pretty bad.
Maybe one day I will make it better.
Also, in this state it's very unsafe to use, planning to make it safer (i'm unwraping everywhere lol)
Built With
dropbox
gtk
rust
Try it out
github.com | Important data saver | Upload your app's import data (like game saves etc) to dropbox, automatically after closing it | ['Korneliusz Wojnicz'] | [] | ['dropbox', 'gtk', 'rust'] | 22 |
9,979 | https://devpost.com/software/extreme-fishing | We were inspired by the games Stardew Valley and Club Penguin. The appeal of the indie aesthetic of Stardew Valley drew us in, we knew we wanted a pixellated game that anyone could play to wind down from a long day at school. Club Penguin's fishing mechanics were initially what we wanted to recreate to a certain extent but when we decided to add the concept of an immortal, aggressive, enemy, our gameplay evolved in a different direction.
Extreme Fishing is a top-down fisher game that places you as a lone fisherman named Benji Tom. You are continuously running around a pond with your rod, catching passerby fish while also avoiding the many different attacks employed by the Kraken in the very centre of the pond. Magic power-ups may appear in the pond allowing you to fish faster, bring you luck with a bigger catch or freeze the Kraken, giving you a short period of rest and relief to fish in peace, if you get lucky you can even learn to block shots with your own rod. Each fish you catch gives you points that contribute to your score, or even your high score.
Extreme Fishing is a group effort created on Repl.it using Python and Pygame. Separate functions were created on our own in Idle then compiled in a Repl.it.
Some challenges we ran into were co-ordination, sprites and de-bugging. Mainly because we all code differently and have different knowledge in terms of Python, we struggled in piecing our code together coherently so that we understood what the others had written. We also faced challenges finding sprites and art for a top-down style game as well as debugging when one of our programmers was sleeping.
We're proud that we took the time to participate in MasseyHacks because we are still technically beginner programmers with only knowledge of Python. We created a game in 24 hours that could typically become an FSE for our course which we are very proud of.
We learned a lot about time management as well as seeing others projects and ideas from more advanced programmers. For our very first hackathon there was a lot of firsts for people who aren't very avid programmers, we learned about how other languages are used and what they are mainly used for.
Next for extreme fishing would definitely be Undertale or Stardew valley dialogue boxes and a short intro scene. We also planned on implementing popups when catching fish, and varying fish shadows depending on the value of the fish, as well as longer reel in times depending on how large the fish shadow is. There is lots to be improved as there is always space for improvement and we plan on doing the best we can do with our time.
Built With
pygame
python
Try it out
github.com | Extreme Fishing | Extreme Fishing is a top-down, high score based fishing games. Fish for points to win a high score and avoid the Kraken trying to steal your fish | ['emily hu', 'Charlie Berg', 'Olivia Yan', 'Andrew Malloy'] | [] | ['pygame', 'python'] | 23 |
9,979 | https://devpost.com/software/vea-sjm2pq | Inspiration
In a dark time, we realized that people are indulging in negative news more than ever. While it is important to know what is occurring, the constant influx of negativity is bound to reflect onto a person's mental health, influencing their daily life. The media seeks these negative stories as that is what most catches our attention, but we are diverging from the norm. We built vea in order to show some of the lesser known & more positive articles to add a smile to someone's day and have a little effect that (hopefully) lasts a long time.
What it does
Vea pulls New York Times articles using the NYT API to look for the latest news. Upon finding an article, it then performs sentiment analysis to decide whether the article is positive or not. If it is, it uploads it onto a Firebase database where the iOS application can then grab the article and display it for the user.
How I built it
The searching and sentient analysis was done via Python. The database was Firebase. The iOS app was written in Xcode with UIKit for the frontend. On the backend, SwiftSoup was used to scrape article content and Firebase was used to pull data from the database.
Challenges I ran into
Vea was especially challenging for us due to the application of concepts that we were not exposed to before MasseyHacks. We had never come in close contact to NLP (sentiment analysis) and implementing it into a python script was truly a challenge. Moreover, we were able to overcome this challenge by making use of our resources: online tools, experience, and the team itself. MasseyHacks allowed us to come out of our comfort zone and learn new technologies, beyond which was imagined in our initial stages.
Accomplishments that I'm proud of
We are proud of how the app turned out overall and the functionality of it. Looking back, we were able to incorporate different technologies seamlessly and the way that they were interacting together was great. A functional backend along with artificial intelligence technology to make decisions in the background play together to enhance the user experience! We also are proud of the design of the app as it flows nicely and users can access all of the features quickly.
Built With
artificialintelligence
firebase
keynote
new-york-times
nytapi
python
ruby
sentimentanalysis
sketch
swift
swiftsoup
uikit
xcode
Try it out
github.com | vea | Highlighting the good in humanity one news article at a time. | ['Ritvik B', 'Vidit Agrawal', 'Siddhant Kumar'] | [] | ['artificialintelligence', 'firebase', 'keynote', 'new-york-times', 'nytapi', 'python', 'ruby', 'sentimentanalysis', 'sketch', 'swift', 'swiftsoup', 'uikit', 'xcode'] | 24 |
9,979 | https://devpost.com/software/not-flappy-bird | Inspiration
Inspired by Flappy Bird, a mobile game developed by dotGears.
What it does
It is a simple game where the player must jump in the air to avoid approaching obstacles. As the game progresses, obstacles approach faster but further apart to increase the difficulty while still being possible.
How I built it
This game was built with Python and pygame.
Challenges I ran into
There were, of course, many bugs in my code which I had to fix. This is also my first time coding a game with object-oriented programming, so it took some time to get used to it.
Accomplishments that I'm proud of
Even though the game is very simple, I'm still proud that it runs smoothly and is (as far as I know) bug-free.
What I learned
I learned to continue persevering even when your team leaves you xD. I also became more comfortable making games with the pygame module.
What's next for NOT Flappy Bird
This game can use improvements such as a settings feature where the user can adjust the difficulty. The obstacles and background could also use some aesthetics. Background music would add more appeal. Once perfected, it can be developed into an app or web app for many more to enjoy.
Built With
pygame
python
Try it out
github.com | NOT Flappy Bird | A simple but addictive game that might resemble flappy bird. | ['Rayton Chen'] | [] | ['pygame', 'python'] | 25 |
9,979 | https://devpost.com/software/cloak-k5jtxi | Create new form
Website landing page
Filling out a form
Viewing form responses
View the project
LIVE
and see the instructions in the
video
as well as our
Github
.
Purpose
Cloak is an applications platform that removes any personal biases from the hiring process, by hiding an applicant's personal information fields, as outlined by the form creator, until after they have been accepted. Fields the form creator could choose to "make secret" could be name, gender, race, etc, and will be visibly differentiated. We also provide the form creator with various other tools to help in their decision making process, such as an NLP-powered summarizer, and a JSON API for an employer to run their own processing on.
Inspiration
Now you may be wondering what inspired us to make Cloak. So let's break it down. At first, one of our team members watched a video explaining the inherent biases that people have and how it affects everything in their daily lives, from employment to shopping. This reminded of the blind auditions that music companies use with great effect. And this is where we realized... if the music industry can adopt this practice, why can't anyone else.
So with that, and the massively increasing unemployment caused by COVID-19, Cloak came into existance and now it's fully functional on our website cloak.theavid.dev so let's dive in.
Development
The core functionality of Cloak resides in the Django open source Python web framework. It allows us to create flexible models, stored in a PostgreSQL database, without writing a single line of SQL. Through Django's admin pages, Cloak hides all personally identifiable information to remove potential bias from applications. Cloak is hosted on a dedicated server running an Nginx reverse proxy. Our fabulous domain name is provided by Namecheap with DigitalOcean acting as a nameserver and host. All traffic is secured through LetsEncrypt SSL certificates ensuring that your private data is safe.
Challenges
Of the three of our members, each one of us was using a different OS and browser, between us covering Chrome, Firefox, Safari on Windows, Arch Linux, and MacOS. This led to some differences in the front-end, and meant we had to make sure all of our commits worked on all three browsers.
However, this also meant that the final product was as polished as possible, working on a large number of systems.
Accomplishments
The biggest accomplishment that we are proud of is the model system that integrated perfectly with the PostgreSQL database and stored all of the data. It worked seamlessly right off the bat because we took a proper amount of time thinking about the best implementation. Getting the site completely functional and into productions was also very rewarding since it means that everyone can try it out and see what it does.
Learning
Some of us were new to Django, and got the chance to familiarize with it through this project. We also got to experiment with things such as TextRank's summarization and secure random number generators. We took an inside look at how other providers make their forms and came up with a solution that expanded the possibilities.
Future
We would continue to expand on the functionality for form creators, allowing a file upload option (where we would remove instances of name, gender, race, and other private information), expand our export options to include .txt, .pdf, .md, etc., and allow for custom email acceptance/rejection messages.
Another possibility is making the secret answers completely secure using end to end encryption so they never leave the user's browser. This will also require some changes to the backend infrastructure because of how the data is currently stored, but it's a goal we'd love to accomplish.
Built With
css
digitalocean
django
html
javascript
jquery
nginx
postgresql
python
textrank
Try it out
cloak.theavid.dev
github.com | Cloak | An application platform that removes bias from the equation | ['Justin Lu', 'Celeste L'] | [] | ['css', 'digitalocean', 'django', 'html', 'javascript', 'jquery', 'nginx', 'postgresql', 'python', 'textrank'] | 26 |
9,979 | https://devpost.com/software/timelec | Timelec logo
Inspiration
Teachers and students are having a hard time adjusting to an unfamiliar learning environment during the quarantine, unable to use the current applications like
zoom
to its fullest. After discussing what was wrong with the lectures, we decided that they were
boring
,
unorganized
, and
hard to follow
.
In order to help the students through COVID-19, we needed to make it so lectures are easier to pick apart and make the important information easier to access.
What it does
Timelec takes a video that you provide and automatically transcribes the audio using
Google Cloud Speech API
so that you won't need to spend hours finding a particular topic the teacher talks about. Once you find what you are looking for through the text, you can click on it to jump through that part of the video. We also added a search function where students can type in keywords in the video and allow them to find a topic even faster without having to look through the transcript every time.
How I (we) built it
We used Django for the backend, PostgreSQL (Heroku) as the database, HTML, Javascript, CSS and bootstrap boilerplate for frontend. We used Heroku to deploy our app.
How to use
Upload your video and wait for the file to process.
Navigate to results to see the transcript. On larger files you can use CTRL+F to search for key words.
Enter the associated timestamp in the search bar below the results
Hit GO and the video will jump to the specified time.
CONSTRAINTS
Please use Firefox, the site doesn't have full functionality with Chrome.
Feel free to use your own video, but there are constraints to video length and size. Video have to be less than a minute, and smaller than 10 MB.
-here is a sample video you can use to test
lecture.mp4
Challenges I (we) ran into
I accidentally posted my Google API key on Github which resulted in some guy mining cryptocurrency with my Compute Engine.
Deploying to Heroku (was new for us).
Accomplishments that I'm proud of
Being able to navigate to specific times in the video.
Transcribing the video with Google Cloud Speech-to-Text.
Converting .mp4 to .wav to .flac to mono channel .flac.
What I learned
File conversion with ffmpeg and python.
A great master named Xiang learned Heroku.
How to use Bootstrap along with HTML.
The meaning of stress.
What's next for Timelec
A cleaner UI/UX is a good start.
Support for browsers other than Firefox.
Support for video longer than a minute and greater than 10 MB.
Additional functionality, adding timestamps on the video, displaying video.
Built With
bootstrap
django
firefox
google-cloud
heroku
pydub
python
Try it out
drive.google.com
timelec.herokuapp.com | Timelec | An application that makes lectures easier to navigate. | ['Raymond Weng', 'Zeta Sovery', 'Jordan Wang'] | [] | ['bootstrap', 'django', 'firefox', 'google-cloud', 'heroku', 'pydub', 'python'] | 27 |
9,979 | https://devpost.com/software/pandemic-party | Inspiration
People currently can't have in person parties and many people have party-based jobs which means that those professionals were unable to work at the same rate, until now.
What it does
Pandemic Party allows you to throw a party no matter where you are. Professionals are able to host workshops for you and your friends and you pay them for being at your awesome virtual party. Artists could lead painting parties, chefs could lead cooking sessions, musicians could play live, djs could spin records;the possibilities are endless!
How we built it
Amazon Web Services and Javascript
Challenges we ran into
There were issues on both the client and server side.
Accomplishments that we're proud of
Getting to the finish line and submitting our project.
What we learned
Time management is one of the most important parts of competing in a hackathon.
What's next for Pandemic Party
Throwing a party using our app!
Built With
amazon-web-services
javascript
Try it out
pandemicparty.tech
github.com | Pandemic Party | Have fun during a pandemic, no matter where you are. | ['Clarissa Ramos', 'Benjamin Swerdlow', 'Isabelle Wagenvoord'] | [] | ['amazon-web-services', 'javascript'] | 28 |
9,979 | https://devpost.com/software/just-draw-d6phy9 | Tracing elephant clipart
Writing over motivational quotes
Inspiration
The inspiration came when I was messing around with pygame. I realized that I had a childlike enjoyment for simply moving a circle across the screen with my mouse. This made me think of creating a drawing program with few features and no UI- just pure drawing.
What it does
Lets you draw by holding the mouse button and moving the cursor. The only other tools are an eraser, equipped by right-clicking, and a colour picker, equipped by middle-clicking. The user can also load in images with transparency if they want to trace over an image they like.
How I built it
I used pygame's mouse and graphical functionality as well as basic programming skills. Some math was required for smoother drawing, but most of the program runs on beginner code.
Challenges I ran into
I tried to add a zoom function and the ability to move the canvas, but I had to scrap it because I couldn't get it working.
Recommendations
Try tracing over a cartoon elephant. They're super cute!
Built With
pygame
python
Try it out
github.com | Just Draw | Stressed about something? Unwind with a childishly simple drawing program. | ['Salman Rashid'] | [] | ['pygame', 'python'] | 29 |
9,979 | https://devpost.com/software/quaranttime | Inspiration
Inspired by the Sims 4 and the fun that comes with creating your own story
What it does
How I built it
With python and pycharm
Challenges I ran into
Accomplishments that I'm proud of
What I learned
Work in team, be realistic
What's next for QuarantTime
Video Link :
https://share.vidyard.com/watch/B92QmWZqxFQ2yuegeBXsoV
?
Built With
pygame
python
Try it out
github.com | QuarantTime | A simulator of a week in the life of a stay at home worker. How will your choices impact others? | ['Tahjeira Cameron'] | [] | ['pygame', 'python'] | 30 |
9,979 | https://devpost.com/software/covid-data-0q3esr | Inspiration
We were inspired by the websites that were popping up with coronavirus data. We found that many were complicated and had huge tables.
What it does
It has two parts: a website and a discord bot. The website has:
A link to invite the bot
Quick coronavirus stats:
Recovered
Deaths
Confirmed
A tool to find your local health agencies, including:
Your national health agency
Your regional health agency
This is determined by your IP address.
The bot has much more detailed stats, including total recovered, total deaths, total new cases, total new deaths, total active cases, and total serious cases. You can access this data by running c!data (country).
How we built it
We looked at what we knew, and thought of something that we could make with it. 2 of us know python, so we made the backend in Flask and the
Challenges we ran into
We registered a Domain.com domain (covidstats.tech) but due to DNS records not updating we were unable to.
Linode wouldn't allow us to use Flask, so we switched over the Microsoft Azure, as one of the team members had prior experience working with Microsoft Azure.
IP addresses weren't being detected by Flask, as they were being rerouted through a proxy when being hosted by Microsoft Azure. Finding a solution took a while.
Accomplishments that we're proud of
It took a while to make a system that checks your IP address and finds the country you're in.
What we learned
Gordon: Getting user info through HTTP requests with proxies and Linux server administration
Gus: Flask
Kaylee: HTML/CSS
David:
GET
requests in python, JSON dictionaries
What's next for Covid Data
Some things that we could add next include creating more features for the bot to use the full extent of the API and more features on the website.
Built With
discord
discordpy
flask
html
python
Try it out
masseyhackscovid19.azurewebsites.net
github.com | Covid Data | A quick way to get stats on the novel coronavirus. | ['Gordon Lin', 'David Chen'] | [] | ['discord', 'discordpy', 'flask', 'html', 'python'] | 31 |
9,979 | https://devpost.com/software/the-grossery | Game "cover"
Our Notion Group Organizer pt 1
Our Notion Group Organizer pt 2
Our Notion Group Organizer pt 3
Our Notion Group Organizer pt 4
Our Notion Group Organizer pt 5
Our Notion Group Organizer pt 6
Our Notion Group Organizer pt 7
Our Notion Group Organizer pt 8
Our Notion Group Organizer pt 9
Script for the "Grossery" commercial video
GIF
Protagonist
GIF
Enemy Basic
GIF
Enemy Medium
GIF
Enemy Advanced
GIF
Mecha Karen Boss
Toilet Paper Pickup
Mask Pickup
Vaccine Pickup
Sanitizer Pickup
Inspiration
The current pandemic has everyone stressed. We decided to build a game to make light of the situation and structured our game to be about social distancing in a grocery store and defeat the final boss: a toilet paper hoarding Karen! We love stealth games and classic pixel art style games and decided to create a game that combined all of the above. As for the name, we did a play on words with the word "grocery" and "gross" (because when you're sick you feel gross!) to make the name of our game, the grossery!
What it does
The Grossery is a top-down 2D stealth game where enemies who don't follow social distancing rules will chase you. Pick up the items on your list and evade the enemies as you move about the grocery store! Don't let the boss, Mecha Karen, catch you on your way out!
How we built it
Almost everything in this game was made by our team. Most of the sound effects, all of the music, all of the art (that includes the map, assets, sprites, animations, everything!) and all of the coding was made by us. Almost every single thing you see and hear in our game was custom made within 24 hours!! We used Unity to build the map and to write the code, and various paint tools such as Piskel and Clip Studio Paint to make the art.
Challenges we ran into
We had a difficult time trying to get the sprite animations to play at the right times. We also had a difficult time trying to stay awake the whole time! But we did it!
Accomplishments that we're proud of
-Making all of the art, music and animations from scratch
-Learning to code sprite animations
-Working together as a team
What we learned
We learned a lot about Unity and how to make stealth games. We also learned that we have great team chemistry!
What's next for The Grossery
Only time will tell... some more levels, perhaps?
Built With
clip-studio-paint
piskel
unity
Try it out
github.com | The Grossery | A stealth game that demonstrates just how important social distancing is | ['Jordan Wideman', 'Alyssa Dupuis', 'Amanda Dupuis', 'Josiah Henson'] | [] | ['clip-studio-paint', 'piskel', 'unity'] | 32 |
9,979 | https://devpost.com/software/heart-disease-diagnostic-application | Inspiration
I recently read online that in the United States, someone has a heart attack approximately every 40 seconds. The disproportionately large number of people suffering from heart-related diseases shocked me, and I was inspired to work on a project that could potentially help a person at risk of having a heart attack or some other heart-related disease. At the same time, I was motivated to apply my knowledge of machine learning to a practical, real-world problem and to integrate it with a easily-accessible web application.
What it does
The user inputs 13 variables (age, gender, cholesterol level, etc) into the UI, and a machine learning model that I trained and developed predicts whether or not the patient is at risk of contracting heart disease. The web application also provides additional information about how to reduce risk of heart disease. The data that the user inputs is confidential - it is not stored anywhere to be reused.
How I built it
I built the application using Python, HTML, CSS, and Javascript. I found heart disease data online that was collected by the Long Beach and Cleveland Clinic Foundation. I then used the pandas and numpy library in Python to preprocess the data. I used this clean data to train and test 6 different machine learning algorithms found in python's scikit-learn library: Logistic Regression, Linear Discriminant Analysis, K-Nearest Neighbors Classifier, Decision Tree Classifier, Support Vector Machine (SVM), and Gaussian Naive Bayes Classifier. Upon evaluation, the Gaussian Naive Bayes algorithm achieved the highest diagnostic performance at approximately 90% accuracy. I then used the Flask web-framework library in python to host the trained machine learning model. I developed the website using HTML, CSS, and Javascript.
Challenges I ran into
The heart disease dataset that I found online had several missing entries/missing values. I had difficulty preprocessing the data. To preprocess it, I replaced each missing value in a column with the mean of the other values of that column. Another difficulty I ran into was sending form data from the user to a format that the machine learning model can predict on.preprocessing the data.
Accomplishments that I'm proud of
I am proud that I figured out how to properly process the missing data so that I would be able to train my models. I am proud of developing a simple machine learning algorithm that is capable of diagnosing risk for heart disease with nearly 90% accuracy. This model can hopefully help to reliably diagnose whether or not a patient is at risk and can potentially save someone’s life.
What I learned
I learned how to integrate Flask with machine learning.
What's next for Heart Disease Diagnostic Application
Next, I plan on using deep neural networks to improve diagnostic accuracy. I can use PyTorch or Keras to implement these neural networks. In addition, I think that using a react framework would result in a more simplistic and user-friendly interface, so I will also implement that in the future.
Built With
css
flask
html5
javascript
numpy
pandas
python
scikit-learn
Try it out
github.com
hearthelper.pythonanywhere.com | HeartHelper | Machine learning-based heart disease diagnostic application | ['Bill Sun'] | [] | ['css', 'flask', 'html5', 'javascript', 'numpy', 'pandas', 'python', 'scikit-learn'] | 33 |
9,979 | https://devpost.com/software/board-t4adnl | Inspiration
From my neighbour
What it does
It creates streamline of posts made by admins and board members
How I built it
To ensure creoss palform, I have used react native
Challenges I ran into
Altering permissions of memebers in Board
Accomplishments that I'm proud of
That I have implemented node.js which I have learned recently
What I learned
Effective use SQL Databases (Postgres)
What's next for board
Use facebook, Instragram, Twitter API to enable streamline from anywhere.
Get bakcend code from
https://github.com/harshal2030/board-server
Built With
java
javascript
objective-c
react-native
ruby
starlark
Try it out
github.com | board | Create and read streamline of posts in boards on an react native app | ['Harshal sanghvi'] | [] | ['java', 'javascript', 'objective-c', 'react-native', 'ruby', 'starlark'] | 34 |
9,979 | https://devpost.com/software/meowscician | Fully working tuner
Title screen
Inspiration
We were inspired by our passion for music and computer science to create a program which could give interactive feedback on music playing like other apps such as (and 100% not copied from) Yousician
What it does
MEOWscician records your computers audio and produces a note matching the frequency. It offers two modes: tuning mode, and rhythm mode. In tuning mode, the program does what you'd expect - listening to the notes being played, and determining whether to tune up or down if its flat or sharp. In rhythm mode, you can choose a song from a list of iconic pieces such as "C Major Scale", "Twinkle Twinkle", or "Mary had a Little Clam", and more! Then the program will test to see whether you are playing the piece correctly or not.
How we built it
We built MEOWscician using python 3.7, as well as other libraries like PyGame and PyAudio.
Challenges we ran into
We had great difficulty getting started due to problems with installing PyAudio.
Accomplishments that we're proud of
We're proud of making a program that is helpful for music learners.
What we learned
We learned that with every program comes a myriad of hurdles to get over. We learned more about the physics of audio and real time audio processing.
What's next for MEOWscician
If we had the time to continue our project, we would aim to include more functionalities such as:
chord recognition (using the Fourier transform), being able to record your music and play it in rhythm mode, and many more!
Built With
pyaudio
pygame
python
Try it out
github.com | MEOWscician | Have you ever wanted to tune your tuba? Or have you ever considered playing Piano Tiles but with an actual piano!? MEOWscician can accomplish all of that and nothing more. | ['Jaden Hong', 'Mudkip LOLZ'] | [] | ['pyaudio', 'pygame', 'python'] | 35 |
9,979 | https://devpost.com/software/many-birds-one-stone | Inspiration
The saying "two bird with one stone" just isn't hyper efficient enough for me.
What it does
Entertain you and provide the cathartic experience of throwing (digital) rocks at digital birds
How I built it
I made the sprite in piskel and coded the game in PyCharm using Pygame.
Challenges I ran into
Creating the sprite and making the game work the way I want it to in Pygame.
Accomplishments that I'm proud of
Fixing the problem of being unable to have an opening screen that I had.
What I learned
To start my project earlier.
What's next for Many Birds, One Stone
I'm considering using the idea to make an actual game for the App store or Google Play.
Built With
piskel
pygame
python
Try it out
github.com | Many Birds, One Stone | An easy to play and fun game based on the saying "two birds with one stone", except you can be even better at throwing rocks. | ['Mc Ocelot'] | [] | ['piskel', 'pygame', 'python'] | 36 |
9,979 | 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'] | 37 |
9,979 | https://devpost.com/software/video-summary | logo
Inspiration
No one likes watching an hour-long documentary,
What it does
it pulls the captions from a youtube video, and runs the text through a summarizing algorithm. With the summarized text, the program is able to edit the original videos using the caption file and compile a seamless shortened video
How I built it
Pure python and some libraries.
Challenges I ran into
originally wanted to use youtube's API to download the captions, but I couldn't get it to work. Switched to a python library. I wanted to implement some other stuff but never got to it.Got a bit boring
Accomplishments that I'm proud of
made something
What I learned
SRT caption file/format, editing videos with python
What's next for Video summary
also, edit video based off visual characteristics instead of only text. Improve summarizing algorithm
Note
Not sure what I changed since the youtube demo(I don't remember changing anything), but it's really slow now. for better performance and easier use, run nonwebapp.py
¯_(ツ)_/¯
Built With
python
Try it out
github.com | Video summary | Quick Way to digest videos | ['William Chen'] | [] | ['python'] | 38 |
9,979 | https://devpost.com/software/polibias | Inspiration
With the spread of the COVID-19 epidemic, more and more individuals are dependent on the news source for their connection to the outside world. With that in mind, many of us can get a false perception of what is happening and who to trust. To resolve this, our team of Keshav Ganapathy, myself, Iain Lee, Yuhwan Lee, and Mohamed Benalla developed PoliBias, an application that allows one to detect political bias in text and online articles.
What it does
We use a recurrent neural network to detect political bias in text and web sites. The neural network has a trained model and gets passed a string that goes through the model. From here, the model returns back a political bias value that the user then sees.
How I built it
With the languages HTML, CSS, and Python, flask library. Additionally, we used the ATOM and the Spyder IDE. We used HTML and CSS for the front end to make it visually pleasing, and flask for the back end infrastructure.
Challenges I ran into
Integration between the front end and the back end was the main one with flask as this was a topic my entire group was new to and making the neural network. Additionally, we were not able to get the logos to show up as a part of the page.
Accomplishments that I'm proud of
Getting the project to work! Though not fully integrated we have a relatively functional project. Also, we worked together and really capitalized on our individual skills.
What I learned
Neural Net Design, collaboration, and Integration via flask. Also, we learned different parts of web design such as scalability which is why we focused on things like mobile-friendliness. Lastly, we learned interlanguage communication which is something that none of us were exposed to before.
What's next for PoliBias
We hope to complete the integration between the front and back end and host the flask app so one can use it in real-time. Additionally, we did not get the logos to work, so that is something we will work on in the future.
Built With
css
flask
html
javascript
python
Try it out
github.com | PoliBias | A machine learning algorithm for political bias detection in media. | ['Keshav Ganapathy', 'Yuhwan Lee', 'Iain Lee'] | [] | ['css', 'flask', 'html', 'javascript', 'python'] | 39 |
9,979 | https://devpost.com/software/quarantimes-d546tg | menu screen
chat room
about us
facts about covid-19
top movies
blog
Inspiration
Being bored while staying at home, we created an app to get rid of our boredom!
What it does
This application provides many accessible features such as the recent Covid - 19 News, Movies, Chat, and blogs about things you could do including cooking, exercising, reading books and much more!
How we built it
We used
https://github.com/umluizlima/flask-pwa
as a template for creating a progressive web application on flask. Our app was made using python, python flask module, html, css and javascript.
Challenges we ran into
Creating the application as a PWA app was a difficult task. Also, integrating API’s and a chat room to flask was challenging at first since we have not dealt with flask PWA and socket.io before.
Accomplishments that we're proud of
Creating a centralized Progressive Web App, the future of web applications, that can serve content that help us during the boring times that we are stuck in right now.6 It spreads awareness of COVID-19 and helps us be productive and find ways to utilize our time. Our web application can also be run both on computer and on mobile.
What we learned
We learnt about the amazing capabilities of web applications. We began to truly understand the method to create proper and pristine applications. And to be honest, we learned the importance of hard work and learning as an overall accomplishment.
What's next for Quarantimes
We wish to deploy this app so that it can be hosted on a web server. That way, it would be accessible to anyone on the internet with ease. During this time, our website is very useful for the community and makes a positive impact.
Built With
css
flask
html
imdb
javascript
news-api
pwa
python
requests
socket.io | Quarantimes | Quarantimes is an app dedicated to solving the issues of boredom and anxiety during this time. We spread awareness of COVID-19, and help the community utilize their time effectively. | ['Dhanish Natarajan', 'Charan Battula', 'Niranjan Mathirajan'] | [] | ['css', 'flask', 'html', 'imdb', 'javascript', 'news-api', 'pwa', 'python', 'requests', 'socket.io'] | 40 |
9,979 | https://devpost.com/software/covid-19-questionaire | intro screen to game
one of the multiple choice questions
Inspiration
Because of the pandemic happening we decided that we wanted to do something that would help inform people in a fun way, we created a 10 question gameshow application that shows facts, difficult and light questions that would help ease the tension caused through out the pandemic.
What it does
This game can answer the given questions, show the right answer and play nice relaxing music
How I built it
We built it using pygame and python
Challenges I ran into
We ran into a few issues, the colours didn't match when we originally picked the backgrounds, the multiple choice questions had issues coordinating with the mouse, other keys collision issues, and formatting
What I learned
I learnt how to better use pygame, using functions, and further developed my skills in python
What's next for Covid-19 Questionaire
If we do continue this game, we plan on making it more advanced; more developed application feel to it, smoother transitions, and maybe add voices that would direct the player.
Built With
pygame'
python
Try it out
github.com | Covid-19 Questionaire | A pygame game show about Covid-19 | ['Benjamin Tran', 'The Legendary Snorman', 'Jerry Wu'] | [] | ["pygame'", 'python'] | 41 |
9,979 | https://devpost.com/software/covid-19-hack-how-long-will-your-toiletpaper-last-you | Inspiration
The panic buying really caught my attention and it inspired me to make a hack that tells you how much toilet paper you would really need and how long it would last for.
What it does
It is a series of questions (7) that once answered, will calculate the number of days left until you run out of toilet paper.
How I built it
I used Python.
Challenges I ran into
It was time-consuming. It took many trails to run the code the way it was intended, and I had to make a few changes each time until I finally got it right.
Accomplishments that I'm proud of
I am really proud of the fact that I have created my first project ever! While using a language I had no experience with.
What I learned
I learnt my first coding language, Python! I have also learnt about the amount of time and effort it really takes to complete a small project and I will never take the lessons I have learned today for granted.
What's next for Covid-19 Hack: How Long Will Your Toilet Paper Last You?
I hope that in the future, this hack grows to be more advanced, accurate, and overall a better hack. I had limited knowledge about coding, so I hope that as my skills evolve, this hack does too.
Built With
python | Covid-19 Hack: How Long Will Your Toilet Paper Last You? | Is your TP running out? Here we can tell you exactly how long your stock will last you. | ['Aayyan Farrukh'] | [] | ['python'] | 42 |
9,979 | https://devpost.com/software/covid-19-hack-happiness-meter | Inspiration
The students who work online during this pandemic share a similar emotion. Their lack of motivation and sadness really urged me to make something we could all relate to and find common ground, despite being in different places.
What it does
Using four specific questions (which sum up what we do during most of our time in isolation), it calculates how happy the individual who's taking the test is.
How I built it
I used python and it's pygame module.
Challenges I ran into
It was just time consuming. It was mostly the visuals which took the longest to make; not the logic behind the testing feature.
Accomplishments that I'm proud of
I have never coded so many lines in one sitting before, and I'm really proud that I didn't give up despite really wanting to. I hardly ran in to the common syntax errors, and whenever I did, it never took more than a minute to solve the issue. I also didn't use any online aid like I usually do with CS projects.
What I learned
Always assume that there's a couple more hours of work left despite knowing that your program is complete. There are always some hidden bugs or minor logic errors, so I'll be sure to be careful of that from now on.
What's next for Covid-19 Hack: Happiness Meter
I hope that with enough time and effort, this can become a proper way of testing an individual's happiness. Especially during a time when everyone's mental health isn't doing the best. I want this to also have different modes and better visuals (depending on the individual's preference). And of course, a lot more than just 4 questions.
Built With
python | Covid-19 Hack: Happiness Meter | Has isolation gotten you down? Well, we can help find out exactly how your happiness has been affected. | ['Saleena Farrukh'] | [] | ['python'] | 43 |
9,979 | https://devpost.com/software/the-ultimate-covid-19-webguide | Inspiration
The whole reason MasseyHacks VI is online in the first place -- COVID-19.
What it does
It's only site you'll need when it comes to COVID-19.
How I built it
HTML5 and CSS3, from scratch.
Challenges I ran into
Image positioning.
Accomplishments that I'm proud of
Creating a functioning website.
What I learned
A lot of new commands in CSS.
What's next for The Ultimate COVID-19 WebGuide
To have more time to work on it (and give it a facelift).
Built With
css3
html5
Try it out
www.dropbox.com | The Ultimate COVID-19 WebGuide | The only site you'll need when it comes to COVID-19. | ['Athavan Balakumar'] | [] | ['css3', 'html5'] | 44 |
9,979 | https://devpost.com/software/hacksim | Inspiration
We wanted to build a full-story text RPG, so we learned about the structure behind Flutter and Dart logic. We implemented humorous concepts into it for a fun experience!
How we built it
We used Flutter (Dart) to build our project.
Challenges we ran into
We spent the majority of the Hackathon's duration coming up and learning the structures and concepts involved, and are grateful for the great MasseyHacks community! Our dives into Flutter were great, but our main structure was not implemented into our app. Regardless, it was a great experience!
Accomplishments that we're proud of
We're really excited with what we've learned so far and are proud of our progress made.
Other
Domain.com registered domain: FALCON9IN.SPACE
Built With
dart
flutter
Try it out
github.com
FALCON9IN.SPACE | Dungeon Crawl: Fighter | Fight and explore your way through the dungeon in an epic text-based RPG | ['Jason Telanoff', 'Henry Marks', 'Jessica Golden'] | [] | ['dart', 'flutter'] | 45 |
9,979 | https://devpost.com/software/covid-19-test-to-test-your-understanding-of-the-pandemic | Inspiration
I wanted to teach and inform others about these unprecedented times
Built With
python
Try it out
github.com | Covid-19 Test, to test your understanding of the pandemic | I made a questionnaire relating to the current pandemic to inform and teach others of the risks and tips to be safe. | ['alex tran'] | [] | ['python'] | 46 |
9,979 | https://devpost.com/software/farmer-frenzy | cool
Try it out
github.com | Farmer Frenzy | GAME | ['Vicky Chen'] | [] | [] | 47 |
9,979 | https://devpost.com/software/nezahack |
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quantity
product
sale
login
Inspiration
Our teacher Luis Martinez decided to ask us if we wanted to participate after a talk about the seriousness of the event and to know that it is the first participation of the school in a non-national contest, it was reason enough to participate.
What it does
inventory control of an online store to which you can add products and supplies of all kinds while keeping track of sales.
How we built it
How we build it
After a chat, which was very quick, we decided to use applications and knowledge taught in the different subjects of the university and it was decided that it would be in Java and MySQL
Challenges we ran into
encounter
the first fuel time, since we only have a couple of hours to organize ourselves and the second fuel we should focus on and who will be the members.
Accomplishments that we're proud of
are proud of
to be able to carry out the project with little time and knowledge of the contest and also to be able to deliver the project with our effort, since our guide was the same members.
What we learned
We learned how complicated it is to develop a project in record time and the difficulties of working like this even when everyone is in their own home.
What's next for NezaHack
Will it grow or evolve into something, in what? We do not know What we do know is the project will continue while the members of this team can keep in touch, since although we learned, it also united us as a team.
Built With
java
mysql
Try it out
github.com | NezaHack | Learn and develop a project with knowledge in record time | ['JOSE-EDUARDO MONTALVO-RODRIGUEZ', 'RICARDO FABRICIO RAMIREZ NIETO', 'Marco Antonio Gomez Valencia', 'Carlos Antonio Zistecatl-Jamaica', 'Maria-Guadalupe Hernandez-Hernandez', 'Jonathan Emmanuel Escobedo-Romero', 'Jumy Solano', 'AXEL MICHEL AYALA-CEDILLO'] | [] | ['java', 'mysql'] | 48 |
9,979 | https://devpost.com/software/takeaction | Inspiration
What it does
How we built it
Challenges we ran into
Accomplishments that we're proud of
What we learned
What's next for ignore
ignoree
Built With
python | ignore | ignore | ['Ivan Mudarth', 'Andy Chen', 'Siddu Palaparthi'] | [] | ['python'] | 49 |
9,979 | https://devpost.com/software/masseyhackslucasoping | Inspiration
I wanted to take my Python skills further and learn how to use pygame. I decided to create a game that was kind of like a cross between pong and tag.
What it does
It's a game built for lively entertainment.
How I built it
I built my game using Python with pygame.
Challenges I ran into
I ran into many challenges during my game, including learning how to do all the different things that I needed to as part of this game. Getting things on the screen, making things move, everything was new and required research and time to get it all working.
Accomplishments that I'm proud of
Having no prior experience with pygame prior to this event, getting anything on the screen was a huge hurdle for me to overcome at first, but after that, things began to go a lot more smoothly. I also didn't know how to use files.
What I learned
I learned to use pygame to code a simple game. I learned to implement files to track high scores.
What's next for MasseyHacksLucasOPing
I have many enhancements planned - and next I think I should learn to create an app so I can distribute my simple games to my friends.
Built With
pygame
python | Ping | In this game, stay away from the red circle to survive as long as you can to get the new high score! | ['Lucas Omstead'] | [] | ['pygame', 'python'] | 50 |
9,979 | https://devpost.com/software/pharmaceutica | Main Game Screen
Develop a Vaccine
Oh no! Your vaccine failed.
Research Minigame
Your second attempt resulted in success!
Inspiration
Growing up, I have always loved playing tycoon games, from Game Dev Studio to Rollercoaster Tycoon 3 to Cities: Skylines. The current world circumstances are a perfect time for a Pharmaceutical Company Tycoon Game, something which is new to the tycoon game scene.
What it does
Allows the user to take ownership of a company granted $1 million in funding from the government to create a vaccine for COVID-19. Choose what type of vaccine you will develop, what ingredients you will include, and even research new types!
How I built it
I built Pharmaceutica in Unity Game Engine with the C# Programming Language.
Challenges I ran into
Art is not my strongest skill, and so doing the pixel-art/hybrid art for the game was the biggest challenge for me.
Accomplishments that I'm proud of
Actually completing the first version of the game from start to finish.
What I learned
It is far easier to develop a game when you have a solid foundation for ideas and features you would like to implement.
What's next for Pharmaceutica
The hiring of scientists and other personnel, the upgrading of labs, and more research options and minigames.
Built With
c#
unity
Try it out
github.com | Pharmaceutica | A tycoon game where you run a pharmaceutical company racing to develop a vaccine for COVID-19 | ['Reezan Visram'] | [] | ['c#', 'unity'] | 51 |
9,979 | https://devpost.com/software/aroundme-84mslw | Inspiration
cedasjkl
What it does
How I built it
Challenges I ran into
Accomplishments that I'm proud of
What I learned
What's next for AroundMe
Built With
css3
figma
html5
Try it out
github.com | Disregard this submission | Allowing people to | ['Arianne Ghislaine Rull', 'Jana Jandal Alrifai'] | [] | ['css3', 'figma', 'html5'] | 52 |
9,979 | https://devpost.com/software/personalteacher | Inspiration
Teachers give handouts during class, and for many teachers, it's a good way to assess their students' skill levels. Many teachers use handouts and ask students to finish them in class because they can get one-on-one support from the teacher. In primary school (not so much in high school), the teacher would walk around the classroom while the students are busy working on their worksheets, and a primary teacher could easily see if a student is struggling with a question based on their work, and they could then help the student directly by pointing them in the right direction. Since COVID-19, classes have shifted online. While there are a lot of advantages to online learning, we believe that it's lacking this one-to-one attention that many students need. We created HandoutLive to help solve this problem.
What it does
HandoutLive is a web app. The two main users of HandoutLive are teachers and students. Teachers create a room on their computer. Teachers can send the room code (shown at the top left of their screen) to their students so that they can join. Teachers and students are able to draw on the room's whiteboard using their mouse. To make drawing/writing easier, teachers and students are able to connect their mobile device simply by going to the same web app on their phone and entering their unique secret code (shown at the top left of their screen). We have a mobile-friendly version where the teacher can pan the canvas and toggle between panning and editing.
Teachers can upload images of worksheets, and the students can complete them by writing/drawing either on their computer or their phone. The teacher can see every student's worksheet update in realtime as each student solves the problems there. If they spot that the student is struggling or has made a mistake, the teacher can let them know and catch these mistakes before the student makes them on a real test.
We also have a messaging feature, where the students and teachers can ask questions. The teacher also has access to a "teacher canvas," a canvas that all students can see but can't write to. This is where, for example, the teacher would take up the worksheets.
As well, our platform also brings more accountability to the students. Many students, including myself, find it sometimes hard to concentrate and become involved with the online lesson, so our app would allow the students to work, knowing that the teacher could be checking up on them at any time. This also prevents the students from not doing the worksheet from laziness, and would ensure that they follow along with the lesson like they would in school.
How we built it
We created the web app using Vue.js and Vuetify. We extensively used the capabilities of HTML5 Canvas and also the Material Design UI component library for Vue.js. We used Node.js for our backend server and Socket.io for the communication between the client and the server. Socket.io allowed us to update the client-side Vue app in real-time with low delay. We then hosted the web app on heroku.
Challenges we ran into
For all of us, it was the first time we worked with Vue.js. Additionally, there were some features we planned but ran out of time to implement. We had many other issues, especially with Socket.io networking, we managed to solve all of them in the end.
Accomplishments that we're proud of
We are proud that we were able to create such an advanced and really useful application over the weekend. We have gotten the application completely functional.
What we learned
We learned how to create a Material Design compliant client UI using Vue.js, Vuetify and connect them to a server backend using Socket.io.
What's next for HandoutLive
In the future, we could further take advantage of the digital format, perhaps by providing convenient and useful features like an undo/redo button and an option to add text. We could also add a colour picker so that teachers and students can write/draw in multiple colours on the virtual whiteboard.
Links
Web App:
http://handoutlive.herokuapp.com/
Web App Github Repo #1:
https://github.com/GeorgeShao/HandoutLive
Web App Github Repo #2:
https://github.com/leonzalion/HandoutLive
Web App Github Server Repo:
https://github.com/leonzalion/HandoutLiveServer
Video
https://www.youtube.com/watch?v=i73WpazAYcA
Built With
heroku
html5
javascript
node.js
socket.io
vue.js
vuetify
Try it out
github.com
github.com
handoutlive.herokuapp.com | HandoutLive | The virtual replacement for handouts; reducing the virtual barrier between teachers and their students | ['George Shao', 'Leon Si'] | [] | ['heroku', 'html5', 'javascript', 'node.js', 'socket.io', 'vue.js', 'vuetify'] | 53 |
9,982 | https://devpost.com/software/homesentry-2mon65 | The project
HomeSentry is an open source platform that turns your old phones or any devices into a distributed security camera system. Simply install our app on any mobile device and start monitoring your home (or any other place). HomeSentry gives a new life to your old devices while bringing you the peace of mind you deserve!
Inspiration
We all have old phones stored in the bottom of a drawer waiting to be used for something. This is where the inspiration for HomeSentry came from. Indeed, We wanted to give our old cellphone and electronic devices a new use so they don't only collect dust over time. Generally speaking, every cellphone have a camera that could be used for something, and we thought using it for security reason would be a great idea. Home surveillance camera systems are often very expensive, or are complicated to set up. Our solution is very simple and costs close to nothing since it's equipment you already have.
How it works
HomeSentry turns your old cellphones into a complete security system for your home. It's a modular solution where you can register as many devices as you have at your disposition. Every device are linked to your account and automatically stream their camera feed to your personnal dashboard in real time. You can view your security footage from anywhere by logging in to your HomeSentry dashboard.
How we built it
The HomeSentry platform is constituted of 3 main components :
1. HomeSentry Server
The server main responsibility is responsible to handle all authentication requests and orchestrate cameras connections. It is indeed in charge of connecting the mobile app to users' dashboard so that it may get the live stream footage. This server is built with node.js and uses a MongoDB to store user accounts.
2. HomeSentry Mobile app
The user goes on the app from his cellphone and enters his credentials. He may then start streaming the video from his camera to the server. The app is currently a web app build with the Angular Framework. We plan to convert it to an Android/iOS application using Apache Cordova at a later stage.
3. HomeSentry Dashboard
The dashboar is the user main management panel. It allows the user to watch all of the streams he his receiving from the connected cellphones. The website was also built with Angular.
Technology
On a more technical note, this app uses several open sources framework and library in order to accomplish it work. Here's a quick summary.
The NodeJS server is built with TypeScript, Express.JS. We use Passport.JS + MongoDB as our authentication system and SocketIO to exchange real time data between every user's devices (cameras) and the dashboard.
On mobile side we are using WebRTC to access the devices' camera stream and to link it to the dashboard. Every camera stream is distributed by a peer to peer connection with the web dashboard when it become active. This ensures the streams privacy and reduce video latency. We used Peer.JS and SocketIO to implement this mecanism.
Just like the mobile client, the web dashboard is built with Angular and frontend libraries such as Bootstrap or feather-icons.
Challenges we ran into (and what we've learned)
Overall we've learned that sending live streams is quite complicated !
We had underestimated the effort required to send and manage this feed. While working with this type of media, we learned how to communicate with WebRTC. At the begining, we tried to do all the stuff by oursef and use different protocols such as RTMP, but we come to a point where it was a little buggy. Late in the event, we found and used the PeerJS lib to manage those streams and it considerably simplified our code.
We found that working with mobile applications like Xamarin is much more complicated for this kind of project. The easiest way was clearly javascript, and it allow a greater type of device to be registered as cameras.
The project also help us improved our knowledge of real time messaging and WebSocket by using SocketIO to add a new stream without having to refresh the web page.
We also used an authentication library we haven't used yet, called PassportJS for Node. With this we were able to show only the streams of a specific user.
We hosted for the first time an appservice with NodeJS on Azure and we configure the CI from GitHub. It's nice to see that they use Github Action to automate this process.
We've finally perfected ourselves on various frontend technologies such as Angular.
What's next for HomeSentry
HomeSentry works very well for displaying feeds of a specific user. Now, what might be cool is to add some analytics on that feed to detect motion and different events. We could send a notification of these movements by sms/email or even send a push notification if we could compile this application in Cordova and distribute it to the AppStore and Google Play. Adding the ability to record and save the feed when motion is detected could be a great addition. With detection, we should store this data in local storage and in the cloud. Working offline could also be a great addition. At last improve quality assurance to ensure that the panel works on any device will be a great idea.
We believe that HomeSentry can be used in many residences and we hope this application will help people secure their homes without having to invest in expensive equipments.
Built With
angular.js
jwt
mongodb
node.js
opencv
peerjs
rest
socket.io
Try it out
homesentry.netlify.app
homesentry-mobile.netlify.app
github.com | HomeSentry | HomeSentry is an open source platform that turns your old phones into a distributed security camera system. Simply install our app on any mobile device and start monitoring your home easily ! | ['Vincent Constantin', 'Olivier Brassard', 'Christopher St-Pierre', 'Charles Piette'] | ['First Place Winner'] | ['angular.js', 'jwt', 'mongodb', 'node.js', 'opencv', 'peerjs', 'rest', 'socket.io'] | 0 |
9,982 | https://devpost.com/software/anti-bumper-car-a-collision-avoidance-system | Image detection, recognized rear image overlaid with AR panel, green panel for safe distance, 1 for drive forward
Inspiration
As lane-keep assist and adaptive cruise control features are becoming more available in commercial vehicles, we wanted to explore the potential of a dedicated collision avoidance system
What it does
We've created an adaptive, small-scale collision avoidance system that leverages Apple's AR technology to detect an oncoming vehicle in the system's field of view and respond appropriately, by braking, slowing down, and/or turning
How we built it
Using Swift and ARKit, we built an image-detecting app which was uploaded to an iOS device. The app was used to recognize a principal other vehicle (POV), get its position and velocity, and send data (corresponding to a certain driving mode) to an HTTP endpoint on Autocode. This data was then parsed and sent to an Arduino control board for actuating the motors of the automated vehicle
Challenges we ran into
One of the main challenges was transferring data from an iOS app/device to Arduino. We were able to solve this by hosting a web server on Autocode and transferring data via HTTP requests. Although this allowed us to fetch the data and transmit it via Bluetooth to the Arduino, latency was still an issue and led us to adjust the danger zones in the automated vehicle's field of view accordingly
Accomplishments that we're proud of
Our team was all-around unfamiliar with Swift and iOS development. Learning the Swift syntax and how to use ARKit's image detection feature in a day was definitely a proud moment. We used a variety of technologies in the project and finding a way to interface with all of them and have real-time data transfer between the mobile app and the car was another highlight!
What we learned
We learned about Swift and more generally about what goes into developing an iOS app. Working with ARKit has inspired us to build more AR apps in the future
What's next for Anti-Bumper Car - A Collision Avoidance System
Specifically for this project, solving an issue related to file IO and reducing latency would be the next step in providing a more reliable collision avoiding system. Hopefully one day this project can be expanded to a real-life system and help drivers stay safe on the road
Built With
arduino
arkit
autocode
c++
python
swift
Try it out
github.com | Anti-Bumper Car - A Collision Avoidance System | What's better than a collision avoidance system? A collision avoidance system that uses AR! | ['Ryun Kim', 'G Tipold', 'Mai Nguyen'] | ['Second Place Winner'] | ['arduino', 'arkit', 'autocode', 'c++', 'python', 'swift'] | 1 |
9,982 | https://devpost.com/software/ubank-t2z9ws | Login Page
Asset Portfolio Page
Account Balances Page
Transaction History Page
Dashboard Page
Voice Recognition Page
Contacts Page
The Team!!
Inspiration
In a world where finance is extremely important, everyone needs access to
banking services
. Citizens within
third world countries
are no exception, but they lack the banking technology infrastructure that many of us in first world countries take for granted. Mobile Applications and Web Portals don't work 100% for these people, so we decided to make software that requires nothing more than a
cellular connection to send SMS messages
in order to operate. This resulted in our hack,
UBank
.
What it does
UBank
allows users to operate their bank accounts entirely through
text messaging
. Users can deposit money, transfer funds between accounts, transfer accounts to other users, and even purchases shares of stock via SMS. In addition to this text messaging capability, UBank also provides a web portal so that when our users gain access to a steady internet connection or PC, they can view their financial information on a more comprehensive level.
How I built it
We set up a backend HTTP server in
Node.js
to receive and fulfill requests.
Twilio
with ngrok was used to send and receive the text messages through a webhook on the backend Node.js server and applicant data was stored in firebase. The frontend was primarily built with
HTML, CSS, and Javascript
and HTTP requests were sent to the Node.js backend to receive applicant information and display it on the browser. We utilized Mozilla's speech to text library to incorporate speech commands and chart.js to display client data with intuitive graphs.
Challenges I ran into
Some team members were new to Node.js, and therefore working with some of the server coding was a little complicated. However, we were able to leverage the experience of other group members which allowed all of us to learn and figure out everything in the end.
Using Twilio was a challenge because no team members had previous experience with the technology. We had difficulties making it communicate with our backend Node.js server, but after a few hours of hard work we eventually figured it out.
Accomplishments that I'm proud of
We are proud of making a
functioning
,
dynamic
, finished product. It feels great to design software that is adaptable and begging for the next steps of development. We're also super proud that we made an attempt at tackling a problem that is having severe negative effects on people all around the world, and we hope that someday our product can make it to those people.
What I learned
This was our first using
Twillio
so we learned a lot about utilizing that software. Front-end team members also got to learn and practice their
HTML/CSS/JS
skills which were a great experience.
What's next for UBank
The next step for UBank probably would be implementing an authentication/anti-fraud system. Being a banking service, it's imperative that our customers' transactions are secure at all times, and we would be unable to launch without such a feature.
We hope to continue the development of UBank and gain some beta users so that we can test our product and incorporate customer feedback in order to improve our software before making an attempt at launching the service.
Built With
css
firebase
html5
javascript
speechrecognizition
twilio
Try it out
github.com | UBank_HT62020 | SMS Banking for third world countries. | ['Dhruv Shah', 'Vedant Shah', 'Brayden Royston'] | ['Third Place Winner'] | ['css', 'firebase', 'html5', 'javascript', 'speechrecognizition', 'twilio'] | 2 |
9,982 | https://devpost.com/software/hush-t5hurf | Inspiration
Throughout high school, our team and other friends regularly called each other for many purposes. However, our parents coming into our rooms for various reasons would always lead to embarrassing moments in the call. Moving forward into university and starting our careers, the concurrent Covid-19 pandemic has amplified this problem to all workers around the world. We developed Hush to tackle concurrent and past issues that we faced in the past.
What it does
Hush is an application that makes sure your mic listens to only what you want it to. It connects a mobile device to your desktop and mutes our computer microphone when the mobile device detects movement of the door to your room.
How we built it
Hush was built using the Swift and integrations with Slack were deployed using autocode.
Challenges we ran into
Our inexperience building macOS applications made it a challenge to get the application working with smooth animations. Networking between iOS and macOS with MultipeerConnectivity with auto connection was quite challenging.
Accomplishments that we're proud of
As first time hackers, we’re really proud to have successfully made something that works and is practical.
What we learned
This was the first time our team had used autocode but we found it to be such an amazing platform. We were able to get the Slack bot connected to our Slack channel rather quickly. Setting up the webhook was also very simple. Many of us see ourselves using autocode in the future for fast prototyping and integrations.
What's next for Hush
This is a proof of concept that solves the problem at hand. However, many individuals will prefer to have their phones by their side. With this in mind, if we were to create a real, marketable product, it would be in the form of a small, single-button device that can be easily attached to any door. The device would be cheap to produce requiring only an accelerometer and Bluetooth pairing capabilities.
Built With
swift
Try it out
github.com | Hush | Hush is an application that makes sure your mic listens to only what you want it to. | ['Leo Pan', 'Richard Li', 'Gareth Lau', 'Alan Yan'] | ['1517 Fund: Most Novel Hack', 'Autocode: Best use of Autocode'] | ['swift'] | 3 |
9,982 | https://devpost.com/software/awesummarizer | Inspiration
Due to COVID-19, millions of students across the world have been forced to quickly adapt to video lectures and online education. To ease this transition and make studying more efficient, we wanted to help students by summarizing their lecture transcripts while also capturing the full lecture transcript so students can pay full attention to the lecture instead of being distracted with taking notes.
What it does
A website that summarizes video lectures for efficient studying. Users can upload their video lectures to receive a full text transcript and timestamps of the most important sentences. The video timestamps have not been formatted to "minutes : seconds" yet.
How We built it
We made made a microservice out of a pre-trained BERT model to summarize text, and an Express web server that works with Vue for the UI to make a web app. The web app accepts video uploads, sends the video to Azure's Speech-to-Text API to get a full transcript, sends the transcript to the microservice to get a summary with timestamps, and sends the summary and timestamps to Vue for display and video playback.
Challenges we ran into
Managing cloud platform credentials in a team of 4 was difficult. Coordinating ourselves to avoid duplicating work. Managing packages and dependencies. Scope creep. Timestamps need to formatted to "minutes : seconds".
Accomplishments that we're proud of
Most technically sophisticated hackathon project so far, as the project has many moving parts like Azure Media Services (for video playback), Azure Cognitive Services (for the Speech-to-Text API), and BERT (for text summarization).
Fun name ;)
What we learned
CORS, JavaScript Promises, Microservice Architecture
What's next for AweSummarizer
Adding video lecture subtitles automatically generated with Azure Media Services. Adding clickable timestamps to play the video at that timestamp for more convenient navigation.
Built With
azure
express.js
flask
javascript
python
pytorch
vue
Try it out
github.com | AweSummarizer | A website that summarizes video lectures for efficient studying. Also includes a full text transcript and timestamps of the most important sentences. | ['Michael Leung', 'Ethan Zhang', 'Denny Lee', 'Matthew Geng'] | ['Microsoft: Azure Challenge'] | ['azure', 'express.js', 'flask', 'javascript', 'python', 'pytorch', 'vue'] | 4 |
9,982 | https://devpost.com/software/busymap | Landing Page
Main interface
Inspiration
What inspired us to create BusyMap was the frustrations that arose when planning for trips during these socially distant months. A factor that we must weigh heavier nowadays in contrast to pre-COVID19 days is how crowded a destination may be. There were countless times during the past few months where we had to turn back from our desired location due to the lack of ability to socially distance responsibly.
What it does
BusyMap provides its users with a comprehensive and real-time platform to visually represent the busyness of areas in the form of heatmaps (using a combination of traffic data and hours of operations for places). That is, enabling users to visualize what areas are crowded during what time of day.
How We built it
BusyMap’s front-end is built with vanilla Javascript/CSS/HTML supported by a Python + Flask backend that connects to GeoTab and Google Maps’ API. Both the website and the supporting backend is hosted on a D2s v3 Microsoft Azure Ubuntu instance.
Front-end back-end communication is established through only RESTful calls. Our program has the potential to become fully stateless and be only running on server-less services.
We made use of GeoTab's UrbanInfrastructures/IdlingAreas dataset as the source of information for our traffic visualizations. Where, we can specify the hour of day and be given the congestion levels of a desired area.
Like mentioned above, we are using Microsoft Azure for hosting the entirety of our project on an Ubuntu instance with NGINX as our reverse-proxy. We see great potential in migrating our app to Azure Functions Serverless Compute to improve scalability and lessen the time needed for maintenance.
Challenges we ran into
Given that we are retrieving large quantities of data from Geotab, processing and displaying data quickly to create a seamless user experience was important to us.
What's next for BusyMap
Add new datasets including COVID-19 metrics and weather
Built With
azure
css
flask
geotab
google-maps
html5
javascript
python
sql | BusyMap | Plan you trips ahead of time and view real time data on a location's busyness, traffic congestion and more! | ['Mark Zhang', 'Nizar Alrifai', 'Vivian Liu', 'Jenny Lei'] | ['Geotab: Ignition Data Challenge'] | ['azure', 'css', 'flask', 'geotab', 'google-maps', 'html5', 'javascript', 'python', 'sql'] | 5 |
9,982 | https://devpost.com/software/smooth-claiminal | Dashboard Page
Claims List Page
Upload Page with Insights
Blockchain Database Claims Viewing Page
Inspiration
One of the biggest problems during this COVID-19 pandemic and these awful times in general is that thousands of people are filing for property and casualty insurance. As a result, insurance companies are receiving an influx of insurance claims, causing longer processing times. These delays not only hurt the company, but also negatively impact the people who filed the claims, as the payout could be essential.
We wanted to tackle these problems with our website, Smooth Claiminal. Our platform uses natural language algorithms to speed up the insurance claiming process. With the help and support from governments and businesses, our platform can save many lives during the current pandemic crisis, while easing the burdens on the employees working at insurance companies or banks.
What it does
Smooth Claiminal serves three main purposes:
Provides an analytics dashboard for insurance companies
Uses AI to extract insights from long insurance claims
Secures data from the claim using blockchain
The analytics dashboard provides insurance companies with information about the previously processed claims, as well as the overall company performance. The upload tab allows for a simplified claim submittal process, as they can be submitted digitally as a PDF or DOCX file.
Once the claim is submitted, our algorithm first scans the text for typos using the Bing Spell Check API by Microsoft Azure. Then, it intelligently summarizes the claim by creating a subset that only contains the most important and relevant information. The text is also passed through a natural language processing algorithm powered by Google Cloud. Our algorithm then parses and refines the information to extract insights such as names, dates, addresses, quotes, etc., and predict the type of insurance claim being processed (i.e. home, health, auto, dental).
Internally, the claim is also assigned a sentiment score, ranging from 0 (very unhappy) to 1 (very happy). The sentimental analysis is powered by GCP, and allows insurance companies to prioritize claims accordingly.
Finally, the claim submissions are stored in a blockchain database built with IPFS and OrbitDB. Our peer to peer network is fast, efficient, and maximizes data integrity through distribution. We also guarantee reliability, as it will remain functional even if the central server crashes.
How we built it
Website built with HTML, CSS, and JS for front end, with a Python and Flask back end
Blockchain database built with IPFS and OrbitDB
NLP algorithm built with Google Cloud's NL API, Microsoft Azure's Spell Check API, Gensim, and our own Python algorithms
Challenges we ran into
Setting up the front end was tough! We had lots of errors from misplaced files and missing dependencies, and resolving these took a lot more time than expected
Our original BigchainDB was too resource-intensive and didn't work on Windows, so we had to scrap the idea and switch to OrbitDB, which was completely new to all of us
Not being able to communicate face to face meant we had to rely on digital channels - this was exceptionally challenging when we had to work together to debug any issues
Accomplishments that we're proud of
Getting it to work! Most, if not all the technologies were new to us, so we're extremely proud and grateful to have a working NLP algorithm which accurately extracts insights and a working blockchain database. Oh yeah, and all in 36 hours!
Finishing everything on time! Building our hack and filming the video remotely were daunting tasks, but we were able to work efficiently through everybody's combined efforts
What we learned
For some of us, it was our first time using Python as a back end language, so we learned a lot about how it can be used to handle API requests and leverage AI tools
We explored a new APIs, frameworks, and technologies (like GCP, Azure, and OrbitDB)
What's next for Smooth Claiminal
We'd love to expand the number of classifiers for insurance claims, and perhaps increase the accuracy by training a new model with more data
We also hope to improve the accuracy of the claim summarization and insights extraction
Adding OCR so we can extract text from images of claims as well
Expanding this application to more than just insurance claims! We see a diverse use case for Smooth Claiminal, especially for any industry where long applications are still the norm! We're also hoping to build a consumer version of this application, which could help to simplify long documents like terms and conditions, or privacy policies.
Built With
azure
blockchain
css
flask
gensim
google-cloud
html
ipfs
javascript
orbitdb
python
Try it out
github.com | Smooth Claiminal | A faster way to process insurance claims, using AI and blockchain. | ['Willson Wang', 'Mihir Kachroo', 'Mark Liu', 'Thomas Leung'] | ['Intact: Insurance Hacker Challenge'] | ['azure', 'blockchain', 'css', 'flask', 'gensim', 'google-cloud', 'html', 'ipfs', 'javascript', 'orbitdb', 'python'] | 6 |
Subsets and Splits