An AI-powered web application that automatically detects and classifies waste materials using YOLO object detection, helping users dispose of waste responsibly and promote sustainable waste management.
The AI-Powered Smart Waste Segregation System is a full-stack web application that uses YOLO object detection to identify waste materials from uploaded images or captured photos. The system classifies waste into different categories and provides disposal recommendations, making waste management more efficient and environmentally friendly.
The application also includes secure user authentication, report generation, email notifications, analytics, and an admin dashboard for monitoring system usage.
- 🔍 AI-powered waste detection using YOLO
- 📷 Upload image or capture using camera
- ♻️ Waste classification into multiple categories
- 💡 Disposal recommendations
- 👤 User Registration & Login (JWT Authentication)
- 🔒 Forgot Password with OTP
- 📧 Email notifications using Gmail SMTP
- 📄 PDF Detection Reports
- 📊 Admin Dashboard & Analytics
- 📈 Detection History
- 🌙 Dark / Light Theme
- 📱 Fully Responsive UI
- Biodegradable
- Cardboard
- Glass
- Metal
- Paper
- Plastic
- React
- Vite
- Tailwind CSS
- Axios
- React Router
- Lucide Icons
- Flask
- Python
- SQLite
- JWT Authentication
- SMTP Email Integration
- Ultralytics YOLO
- OpenCV
- NumPy
AI-Powered-Smart-Waste-Segregation-System/
│
├── frontend/ # React Frontend
│ ├── src/
│ ├── public/
│ └── package.json
│
├── services/ # Backend Services
├── templates/
├── app.py
├── config.py
├── predict.py
├── train.py
├── evaluate.py
├── requirements.txt
├── .gitignore
└── README.md
git clone https://github.com/ashishkumar817/AI-Powered-Smart-Waste-Segregation-System.git
cd AI-Powered-Smart-Waste-Segregation-SystemCreate Virtual Environment
python -m venv venvActivate
Windows
venv\Scripts\activateInstall Dependencies
pip install -r requirements.txtRun Flask Server
python app.pycd frontend
npm install
npm run devThis project uses Ultralytics YOLO for object detection.
The model detects waste objects and classifies them into six categories.
Note: The trained model weights are not included in this repository if they exceed GitHub's file size limits.
- Live Camera Detection
- Video Detection
- Mobile Application
- Cloud Deployment
- Multi-language Support
- Smart Bin Integration
- Real-time Analytics
- More Waste Categories
Contributions are welcome.
- Fork the repository
- Create your feature branch
git checkout -b feature-name- Commit your changes
git commit -m "Add new feature"- Push
git push origin feature-name- Open a Pull Request
This project is licensed under the MIT License.
Ashish Kumar
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