A comprehensive platform for energy monitoring, waste management, and sustainable living.

• Real-time energy usage monitoring
• Waste segregation tracking
• Food waste management
• Carbon footprint calculator
• Environmental impact dashboard
• AI-powered recommendations

• Framework: Python Flask
• Database: MongoDB
• AI/ML: Google Gemini AI, scikit-learn
• Authentication: JWT

• Framework: HTML5, CSS3, JavaScript
• Responsive Design: Bootstrap
• Interactive UI: jQuery, AJAX

• Python 3.8 or higher
• MongoDB
• Google API Key for Gemini AI
• Required Python packages (listed in requirements.txt)

1. Clone the repository
2. Create a virtual environment:

   python -m venv venv
   source venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install dependencies:

   pip install -r requirements.txt

4. Set up environment variables in .env:

   MONGODB_URI=your_mongodb_uri
   GOOGLE_API_KEY=your_google_api_key
   SECRET_KEY=your_secret_key
   

5. Run the application:

   python app.py

1. Create a new Web Service on Render
2. Connect your GitHub repository
3. Use the following settings:
   • Environment: Python
   • Build Command: pip install -r requirements.txt
   • Start Command: gunicorn app:app
4. Add environment variables:
   • MONGODB_URI: Your MongoDB Atlas connection string
   • GOOGLE_API_KEY: Your Google API key
   • SECRET_KEY: A secure random string

• MONGODB_URI: MongoDB connection string
• GOOGLE_API_KEY: Google API key for AI features
• SECRET_KEY: Flask secret key for session management

.
├── app.py              # Main application file
├── requirements.txt    # Python dependencies
├── gunicorn.conf.py   # Gunicorn configuration
├── render.yaml        # Render deployment configuration
├── .env              # Environment variables (local development)
├── .gitignore        # Git ignore rules
└── templates/        # HTML templates
    ├── base.html
    ├── index.html
    ├── energy_monitor.html
    └── ...

Shrey Shukla 💻

Prasham Shah 💻

This project follows the MIT License.