Project AgniRakshak
Real-Time Forest Fire Risk Prediction System
Created on 14th November 2025
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Project AgniRakshak
Real-Time Forest Fire Risk Prediction System
The problem Project AgniRakshak solves
People can use this system to identify forest areas at risk before a fire starts, making their work safer and more efficient. Forest officers can plan patrols, allocate resources, and take preventive actions in high-risk zones instead of reacting after a fire has already spread. Disaster-management teams can use the risk map to respond faster and with better coordination. Local communities living near forests get early warnings, making their surroundings safer. Overall, the system reduces guesswork, saves time, prevents huge losses, and makes environmental protection more proactive and effective.
Challenges we ran into
One major hurdle we faced while building this project was handling real data integration, especially trying to load environmental datasets from external sources like AWS S3. Since proper cloud configuration requires access keys, IAM setup, and bucket permissions, the data initially failed to load, which broke our model training. To overcome this, we added a smart fallback system: if S3 or any external source fails, the app automatically switches to clean sample data so the dashboard still works smoothly. This made the system much more reliable and allowed us to continue development without blocking progress. It also taught us how to gracefully handle data errors—an essential part of building real-world applications.
Tracks Applied (1)
Sustainability
Technologies used