PS-01Safe & Smart Communities
JanRakshak
AI-Assisted Emergency Response and Resource Coordination
SDG 11SDG 13
The challenge
During fires, floods, accidents, local infrastructure failures or other emergencies, information about affected people, available responders, nearby shelters, medical support and blocked routes is often fragmented across calls and messages. Build an AI-assisted coordination system that combines incident reports, location, urgency, available resources and route conditions to create a shared operational picture. The system should help authorised coordinators identify high-priority cases, avoid duplicate dispatches, recommend suitable nearby resources and update the response plan as new information arrives. The challenge is decision support and coordination, not autonomous emergency command.
What a working submission needs
Build a working web or mobile prototype that accepts simulated incident reports, classifies urgency, places incidents and resources on a map, recommends a response/resource match, and shows a live coordinator dashboard.
The minimum prototype should demonstrate at least three incident types and an auditable explanation for prioritisation.
Stretch goals
multilingual voice intake, offline capture, responder ETA prediction or dynamic rerouting.
Optional. A working core counts for more than feature count.Suggested stack
Web/mobile application, AI/ML models, a mapping or dashboard interface, and open APIs as appropriate to the problem.
Scope and responsibility
Healthcare, safety and public-sector challenges are decision-support tools, not autonomous clinical, legal, emergency-command or enforcement systems. Name your prototype’s limitations in the demo. Judging weighs a working core, justified use of AI, technical quality, real-world impact and responsible design above feature count.
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