AI-powered geospatial intelligence that predicts landslides, floods, wildfires, and drought — giving communities, responders, and administrators the time to act.
Four-stage pipeline processing satellite feeds, sensor data, and community reports into life-saving alerts.
ISRO, IMD, MODIS satellites + IoT ground sensors feed real-time data across 13 districts
ML models (Random Forest, LSTM, XGBoost) analyze patterns across 15+ years of historical data
Multi-channel alerts: push notifications, SMS, FM radio, siren integration for zero-connectivity zones
Coordinated SDRF/NDRF dispatch, shelter management, evacuation route optimization
Real-time monitoring, historical analysis, and AI prediction for Uttarakhand's four most devastating natural hazards.
Slope stability analysis using InSAR, rainfall correlation, and seismic triggers. ML predictions with Random Forest models.
River gauge monitoring, LSTM-based discharge prediction, glacial lake outburst (GLOF) tracking, and inundation mapping.
MODIS/VIIRS hotspot detection, fuel moisture indices, and XGBoost fire spread modeling. Real-time Forest Department alerts.
NDVI vegetation monitoring, SPI rainfall anomaly tracking, groundwater decline analysis, and crop stress early warnings.
A unified command center for district magistrates, SDRF teams, and community responders with real-time hazard overlays on an interactive map.
Works without internet in remote valleys. Pre-cached tiles, local SQLite, delta sync when connectivity returns. Critical for Char Dham corridor.
Random Forest for landslides, LSTM for floods, XGBoost for fire spread. Trained on 15+ years of Uttarakhand disaster data from ISRO/NRSC.
Push notifications, SMS via bulk gateway, sirens integration, FM radio API. Reaches communities even in zero-connectivity zones.
Citizens report cracks, water level changes, smoke sightings. Photos with GPS. Ground-truth data feeds into the ML models.
Task assignment for SDRF/NDRF teams. Shelter management. Evacuation route optimization. Real-time team GPS tracking.
Built on GeoJSON, WMS/WMTS, CAP (Common Alerting Protocol). Integrates with IMD, CWC, ISRO APIs. No vendor lock-in.
Each of these could have had fewer casualties with better early warning and coordination.
Glacial collapse in Nanda Devi triggered a massive debris flow down the Rishi Ganga and Dhauli Ganga valleys, destroying two hydropower projects.
Entire town sinking due to land subsidence. 868+ buildings cracked. 4,500+ residents at risk. InSAR data showed movement months before the crisis became visible.
Massive wildfire season burned 1,800+ hectares of forest. Pine needle buildup + delayed monsoon. Smoke affected air quality across 5 districts.
Severe rainfall deficit in Kumaon division. Springs dried up across 400+ villages. Agricultural losses exceeded ₹800 Cr. Drinking water crisis in Almora and Bageshwar.
All-Rust backend for reliability and performance. Flutter for cross-platform reach. PostGIS for geospatial intelligence.
See the multi-hazard intelligence dashboard in action with real Uttarakhand geospatial data.
We are looking for government partners, disaster management agencies, research institutions, and NGOs to pilot UttaraRaksha.