Our project is an advanced GLOF early warning system that uses multiple sensors and AI analytics to monitor flood risks real-time, enabling timely alerts and evacuation. It’s currently in the prototype phase with research, module planning, and tech stack finalized, and backend development underway.
- Real-time multi-sensor data monitoring and fusion
- AI/ML-based hazard prediction and anomaly detection
- Dynamic evacuation zone classification (Red, Yellow, Green)
- GPS-based population tracking and evacuation management
- Renewable energy-powered sensor network (solar and wind)
- Interactive dashboards and alert notifications
- Drone surveillance for aerial hazard assessment
- Completed in-depth research and module planning
- Finalized technology stack and system architecture
- Designed UI/UX for dashboards and resident app
- Developed backend infrastructure to simulate sensor data streams
- Built initial AI models for hazard prediction
- Working on prototype integration and live demos
- Frontend: React Native, Google Maps API
- Backend: Node.js, Express, MongoDB
- AI/ML: Python (TensorFlow, PyTorch)
- Communication: WebSocket, LoRaWAN, 4G/5G
- Deployment: Cloud platforms (AWS/Azure/GCP)
- Clone the repo
- Setup environment dependencies
- Run backend simulation server
- Launch frontend app and connect to backend
- Explore live sensor data simulation and evacuation UI
- Complete prototype development and integration
- Field test with simulated data
- Enhance AI prediction accuracy
- Develop offline capabilities for mobile app
- Collaborate for pilot deployment in GLOF-prone regions
Contributions are welcome! Please open issues or pull requests for improvements, bug fixes, or new features.
This README provides comprehensive insights into the project for collaborators, judges, and contributors.