roshnn24 commited on
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  1. Dockerfile +53 -0
  2. app.py +171 -0
  3. code_flow +15 -0
  4. prasunethon.html +143 -0
Dockerfile ADDED
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+ FROM python:3.9-slim
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+
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+ # Install necessary system dependencies
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+ RUN apt-get update && apt-get install -y \
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+ libgl1-mesa-glx \
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+ libglib2.0-0 \
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+ wget \
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+ unzip \
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+ curl \
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+ ca-certificates \
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+ gnupg \
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+ fonts-liberation \
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+ libnss3 \
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+ libxss1 \
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+ libappindicator1 \
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+ libgbm-dev \
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+ libgtk-3-0 \
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+ gcc \
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+ libffi-dev \
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+ libxml2-dev \
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+ libxslt1-dev \
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+ libjpeg-dev \
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+ zlib1g-dev \
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+ && rm -rf /var/lib/apt/lists/*
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+
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+ # Set the working directory
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+ WORKDIR /code
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+
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+ # Create necessary directories
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+ RUN mkdir -p /code/uploads
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+
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+ # Add and use a non-root user
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+ RUN useradd -ms /bin/sh myuser
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+
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+ # Set ownership and permissions
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+ RUN chown -R myuser:myuser /code && \
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+
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+ chmod -R 775 /code/uploads
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+
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+ RUN apt-get update && apt-get install -y
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+
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+ # Switch to non-root user
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+ USER myuser
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+
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+ # Copy and install Python dependencies
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+ COPY --chown=myuser:myuser ./requirements.txt /code/requirements.txt
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+ RUN pip install --no-cache-dir --upgrade -r /code/requirements.txt
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+
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+ # Copy the application code
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+ COPY --chown=myuser:myuser . /code
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+
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+ # Default command to run the application
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+ CMD ["python", "app.py"]
app.py ADDED
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+ from flask import Flask, render_template, request, jsonify, send_from_directory
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+ import pymysql
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+ import matplotlib.pyplot as plt
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+ import io
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+ import base64
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+ from gtts import gTTS
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+ import os
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+ import random
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+ from ai71 import AI71
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+
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+ app = Flask(__name__)
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+ '''db = pymysql.connect(host="localhost", user="root", password="1234", database="tea_farm")
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+ cursor = db.cursor()'''
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+
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+ UPLOAD_FOLDER = 'uploads'
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+ OUTPUT_DIRECTORY = 'audio'
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+ if not os.path.exists(UPLOAD_FOLDER):
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+ os.makedirs(UPLOAD_FOLDER)
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+ if not os.path.exists(OUTPUT_DIRECTORY):
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+ os.makedirs(OUTPUT_DIRECTORY)
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+
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+ # Text for pest and disease
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+ pest_text = '''tea mosquito bugs,to get rid,spray with neem oil and garlic,use sticky traps, and trap crops like castor . Expect results in 2 to 4 weeks.চা মশার বাগ, পরিত্রাণ পেতে, নিম তেল এবং রসুন দিয়ে স্প্রে করুন, আঠালো ফাঁদ ব্যবহার করুন এবং ক্যাস্টরের মতো ফসল ফাঁদ করুন। 2-4 সপ্তাহের মধ্যে ফলাফল আশা করুন।'''
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+ disease_text = '''Detected Disease: Brown Blight is a fungal disease To treat it spray a mix of baking soda, water and apply organic mulch to keep soil healthy.ব্রাউন ব্লাইট একটি ছত্রাকজনিত রোগের চিকিৎসার জন্য বেকিং সোডা, পানির মিশ্রণ স্প্রে করুন এবং মাটি সুস্থ রাখতে জৈব মালচ প্রয়োগ করুন'''
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+
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+ @app.route('/home')
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+ def home():
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+ return render_template('index.html')
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+
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+ @app.route('/notification')
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+ def notification():
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+ return render_template('notification.html')
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+
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+ @app.route('/', methods=['GET', 'POST'])
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+ def upload_file():
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+ pest_filename = None
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+ disease_filename = None
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+ pest_audio_file = "pest.mp3"
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+ disease_audio_file = "disease.mp3"
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+
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+ if request.method == 'POST':
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+ if 'pest_file' in request.files:
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+ pest_file = request.files['pest_file']
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+ if pest_file.filename != '':
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+ pest_filename = pest_file.filename
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+ pest_file.save(os.path.join(UPLOAD_FOLDER, pest_filename))
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+ tts_pest = gTTS(text=pest_text, lang='en', slow=False)
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+ tts_pest.save(os.path.join(OUTPUT_DIRECTORY, pest_audio_file))
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+
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+ if 'disease_file' in request.files:
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+ disease_file = request.files['disease_file']
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+ if disease_file.filename != '':
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+ disease_filename = disease_file.filename
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+ disease_file.save(os.path.join(UPLOAD_FOLDER, disease_filename))
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+ tts_disease = gTTS(text=disease_text, lang='en', slow=False)
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+ tts_disease.save(os.path.join(OUTPUT_DIRECTORY, disease_audio_file))
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+
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+ return render_template('index.html', pest_filename=pest_filename, disease_filename=disease_filename,
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+ pest_audio_file=pest_audio_file, disease_audio_file=disease_audio_file)
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+
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+ AI71_API_KEY = "api71-api-20725a9d-46d6-4baf-9e26-abfca35ab242"
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+ @app.route('/chat', methods=['POST'])
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+ def chat():
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+ message = request.json['message']
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+ ai71 = AI71(AI71_API_KEY)
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+ response = ""
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+ for chunk in ai71.chat.completions.create(
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+ model="tiiuae/falcon-180b-chat",
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+ messages=[
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+ {"role": "system", "content": "You are a helpful assistant for a farming system.Guide the user properly to increase the yield."},
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+ {"role": "user", "content": message},
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+ ],
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+ stream=True,
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+ ):
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+ if chunk.choices[0].delta.content:
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+ response += chunk.choices[0].delta.content
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+ return jsonify({'response': response.replace('\n','<br>')})
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+ @app.route('/uploads/<filename>')
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+ def uploaded_file(filename):
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+ return send_from_directory(UPLOAD_FOLDER, filename)
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+
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+ @app.route('/audio/<filename>')
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+ def audio_file(filename):
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+ return send_from_directory(OUTPUT_DIRECTORY, filename)
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+
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+ @app.route('/sensors')
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+ def sensors():
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+ # Fetch a random row from the database
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+ sensor_data=False
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+
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+ if sensor_data:
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+ sensor_dict = {
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+ 'id': sensor_data[0],
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+ 'temperature': sensor_data[1],
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+ 'humidity': sensor_data[2],
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+ 'irValue': sensor_data[3],
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+ 'distance': sensor_data[4],
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+ 'timestamp': sensor_data[5]
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+ }
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+ else:
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+ sensor_dict = {
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+ 'temperature': None,
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+ 'humidity': None,
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+ 'irValue': None,
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+ 'distance': None,
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+ 'timestamp': None
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+ }
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+
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+ return render_template('sensors.html', sensor_data=sensor_dict)
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+
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+ @app.route('/zones')
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+ def zones():
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+ return render_template('zones.html')
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+
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+ @app.route('/activity-log')
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+ def activity_log():
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+
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+ # Fetch data for IR value distribution plot
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+ cursor.execute("SELECT ir_value FROM sensor_data")
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+ ir_values = cursor.fetchall()
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+ count_0 = ir_values.count((0,))
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+ count_1 = ir_values.count((1,))
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+ labels = ['Pest Swarm Detected', 'No Pest Swarm Detected']
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+ sizes = [count_0, count_1]
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+ plt.figure(figsize=(6, 6))
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+ plt.pie(sizes, labels=labels, autopct='%1.1f%%')
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+ plt.title('IR Value Distribution')
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+ plt.axis('equal')
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+ ir_buffer = io.BytesIO()
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+ plt.savefig(ir_buffer, format='png')
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+ ir_buffer.seek(0)
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+ ir_plot_data = base64.b64encode(ir_buffer.getvalue()).decode('utf-8')
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+ plt.close()
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+
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+ # Fetch data for average closeness of pests plot
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+ cursor.execute("SELECT timestamp, distance FROM sensor_data WHERE distance < 500")
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+ data = cursor.fetchall()
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+ timestamps = [row[0] for row in data]
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+ distances = [row[1] for row in data]
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+ average_distance = sum(distances) / len(distances)
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+ plt.figure(figsize=(10, 6))
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+ plt.plot(timestamps, distances, marker='o', linestyle='-')
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+ plt.xlabel('Timestamp')
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+ plt.ylabel('Distance (cm)')
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+ plt.title('Average Closeness of Pests over Time')
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+ plt.xticks(rotation=45)
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+ plt.grid(True)
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+ distance_buffer = io.BytesIO()
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+ plt.savefig(distance_buffer, format='png')
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+ distance_buffer.seek(0)
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+ distance_plot_data = base64.b64encode(distance_buffer.getvalue()).decode('utf-8')
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+ plt.close()
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+
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+ return render_template('activity-log.html', ir_plot_data=ir_plot_data, distance_plot_data=distance_plot_data)
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+
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+ @app.route('/sensor-data', methods=['POST'])
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+ def update_sensor_data():
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+ data = request.get_json()
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+ temperature = data.get('temperature')
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+ humidity = data.get('humidity')
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+ ir_value = data.get('irValue')
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+ distance = data.get('distance')
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+ sql = "INSERT INTO sensor_data (temperature, humidity, ir_value, distance) VALUES (%s, %s, %s, %s)"
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+ val = (temperature, humidity, ir_value, distance)
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+ cursor.execute(sql, val)
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+ db.commit()
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+ return jsonify(success=True)
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+
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+ if __name__ == "__main__":
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+
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+ app.run(host='0.0.0.0', port=7860,debug=1==1)
code_flow ADDED
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+ digraph {
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+ node [fillcolor=lightblue shape=box style=filled]
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+ line0 [label="def example_function(x):"]
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+ line1 [label="if x < 0:"]
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+ line1 -> line2 [label=True]
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+ line2 [label="return 'Negative'" shape=oval]
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+ line2 -> line3
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+ line3 [label="elif x == 0:"]
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+ line3 -> line4 [label=True]
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+ line4 [label="return 'Zero'" shape=oval]
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+ line4 -> line5
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+ line5 [label="else:"]
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+ line5 -> line6 [label=True]
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+ line6 [label="return 'Positive'" shape=oval]
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+ }
prasunethon.html ADDED
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+ <!DOCTYPE html>
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+ <html lang="en">
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+ <head>
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+ <meta charset="UTF-8">
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+ <meta name="viewport" content="width=device-width, initial-scale=1.0">
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+ <title>Resource Consumption Monitor</title>
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+ <style>
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+ body {
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+ font-family: 'Arial', sans-serif;
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+ background-color: #f7f7f7;
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+ margin: 0;
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+ padding: 20px;
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+ color: #333;
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+ }
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+ h1 {
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+ text-align: center;
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+ color: #4CAF50;
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+ margin-bottom: 40px;
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+ }
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+ .resource-card {
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+ background-color: #fff;
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+ padding: 20px;
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+ border-radius: 10px;
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+ box-shadow: 0 4px 8px rgba(0, 0, 0, 0.1);
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+ margin-bottom: 20px;
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+ display: flex;
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+ align-items: center;
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+ transition: transform 0.2s ease;
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+ }
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+ .resource-card:hover {
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+ transform: translateY(-5px);
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+ }
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+ .resource-card img {
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+ width: 60px;
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+ height: 60px;
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+ margin-right: 20px;
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+ }
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+ .card-content {
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+ flex: 1;
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+ display: flex;
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+ flex-direction: column;
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+ justify-content: center;
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+ }
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+ .card-title {
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+ font-weight: bold;
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+ font-size: 1.2em;
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+ color: #333;
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+ margin-bottom: 5px;
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+ }
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+ .data-value {
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+ font-size: 1em;
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+ color: #777;
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+ }
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+ .chart-container {
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+ width: 50%;
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+ max-width: 300px;
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+ }
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+ </style>
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+ <script src="https://cdn.jsdelivr.net/npm/chart.js"></script>
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+ </head>
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+ <body>
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+ <h1>Resource Consumption</h1>
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+ <div id="resource-cards"></div>
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+
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+ <script>
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+ function fetchData() {
67
+ const resources = [
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+ { name: "Electricity", icon: "path/to/electricity.png", yesterday: 20, predicted: 710, unit: "MU(Million Units)", data: [21,24,25,22.5,27,22, 33] },
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+ { name: "Water", icon: "path/to/water.png", yesterday: 192, predicted: 3698, unit: "Million Liters", data: [198,193,215,206,214,200,219]},
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+ { name: "Gas", icon: "path/to/gas.png", yesterday: 179, predicted: 4982, unit: "kilo m³", data: [175,176,174,177,175,147,190] },
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+ { name: "Internet", icon: "path/to/internet.png", yesterday: 1.38, predicted: 34.9, unit: "PB", data: [1.22,1.38,1.24,1.24,1.36,1.35,2.78] },
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+ { name: "Waste", icon: "path/to/waste.png", yesterday: 864, predicted: 21850, unit: "metric tons", data: [874,859,847,841,853,864,845] },
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+ // Add more resources here with their details
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+ ];
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+
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+ const resourceCards = document.getElementById("resource-cards");
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+
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+ resources.forEach((resource, index) => {
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+ const card = document.createElement("div");
80
+ card.classList.add("resource-card");
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+
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+ const img = document.createElement("img");
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+ img.src = resource.icon;
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+ card.appendChild(img);
85
+
86
+ const cardContent = document.createElement("div");
87
+ cardContent.classList.add("card-content");
88
+
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+ const title = document.createElement("h3");
90
+ title.classList.add("card-title");
91
+ title.textContent = resource.name;
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+ cardContent.appendChild(title);
93
+
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+ const yesterdayData = document.createElement("p");
95
+ yesterdayData.textContent = Yesterday: ${resource.yesterday} ${resource.unit};
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+ cardContent.appendChild(yesterdayData);
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+
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+ const predictedData = document.createElement("p");
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+ predictedData.textContent = Predicted (Next Month(July)): ${resource.predicted} ${resource.unit};
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+ predictedData.classList.add("data-value");
101
+ cardContent.appendChild(predictedData);
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+
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+ card.appendChild(cardContent);
104
+
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+ const chartContainer = document.createElement("div");
106
+ chartContainer.classList.add("chart-container");
107
+ const canvas = document.createElement("canvas");
108
+ canvas.id = chart-${index};
109
+ chartContainer.appendChild(canvas);
110
+ card.appendChild(chartContainer);
111
+
112
+ resourceCards.appendChild(card);
113
+
114
+ // Initialize the chart
115
+ const ctx = canvas.getContext('2d');
116
+ new Chart(ctx, {
117
+ type: 'line',
118
+ data: {
119
+ labels: ['Monday', 'Tuesday', 'wednesday', 'Thursday', 'Friday', 'Saturday', 'Sunday'],
120
+ datasets: [{
121
+ label: resource.name,
122
+ data: resource.data,
123
+ backgroundColor: 'rgba(75, 192, 192, 0.2)',
124
+ borderColor: 'rgba(75, 192, 192, 1)',
125
+ borderWidth: 1,
126
+ fill: true
127
+ }]
128
+ },
129
+ options: {
130
+ scales: {
131
+ y: {
132
+ beginAtZero: false
133
+ }
134
+ }
135
+ }
136
+ });
137
+ });
138
+ }
139
+
140
+ fetchData();
141
+ </script>
142
+ </body>
143
+ </html>