SIH26192Software
Flash Flood Prediction System for Hilly Regions using Multi-Source Data Theme
Ministry of Home Affairs
Official Description
• Background Hilly states in India are highly vulnerable to landslides and flash floods,which often occur with very short warning times. These sudden events result in significant loss of lives and property, and current early warning mechanisms are inadequate for hyper-local prediction and timely evacuation.
• Description The proposed initiative aims to develop a predictive system that integrates multiple data sources - rainfall data, soil moisture sensors,slope stability models, historical landslide inventories, and real-time IoT inputs. By combining these datasets, the system will generate hyper-local forecasts at the village or ward level, providing sufficient lead time for evacuation and risk mitigation.
• Expected Solution A comprehensive flash flood prediction system that Integrates rainfall,soil moisture, slope stability, and historical disaster data, utilizes IoT sensors for real-time monitoring, issues hyper-local early warnings at village/ward level, and provides actionable lead time for evacuation and disaster preparedness.
Official Hackathon Facts
Theme / DomainDisaster Management
Track TrackSoftware
Submission Deadline20 September 2026
Ideas Registered0/500
✨ SIH Fit Analysis
Estimated DifficultyBeginner
Social Impact Score (5/5)
🔥 High Impact🌍 High Social Impact
Primary Tech AreaAI-based Prediction / Recommendation
Technology Stack Tags
AI/MLPredictive AnalyticsIoTSensors
Suggested Skills
PythonTime-series modellingMQTT / IoT protocolsSensor interfacing
Notable Technology Combo
AI/ML + IoT
✦ Why This Problem is Interesting
Combines IoT, Predictive Analytics with the problem domain, creating a technically focused solution opportunity.
* Note: SIH Fit Analysis contains derived ratings and classification schemas generated to aid team selection; these are not official ratings from the Smart India Hackathon organizers.
