AI for Disaster Relief Planning
Optimizing resource supply chains through satellite and social predictive modeling
ResQ-AI Disaster Deployment
Aggregating weather feeds, high-resolution topology, and civic messages to predict and tackle supply chain blocks during critical monsoon seasons. The platform routes essential medicine, food, and water units directly to isolated coordinates.
The Challenge
Limited access to nearby healthcare services made it difficult for rural families to receive timely medical attention and proper guidance.
- ✓Washed out supply roads causing localized severe shortages
- ✓Traditional satellite imagery taking 24 hours to process
- ✓Unstructured flood emergency requests across multiple social channels
- ✓Excessive relief stockpiling in accessible camps leaving others empty
The Solution
We brought essential healthcare services closer to communities through accessible, reliable, and community driven initiatives.
- ✓Implemented machine-learning route blockage detectors
- ✓Used low-bandwidth localized mesh devices to coordinate supply trucks
- ✓Created a single aggregated urgent message queue powered by NLP
- ✓Automated regional inventory planning to distribute aid balancedly
By forecasting route blockages and tracking request densities, we successfully routed over 25 tons of medical and food supplies directly to the isolated coastal nodes 30 hours faster.
”Overall Program Impact
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