Disaster-Ready Community Network
An AI early-warning system for floods and wildfires, paired with trained volunteer first responders and regular simulation drills.
The Challenge
False alarms undermining trust, equipment damage in the field, and sustained community engagement with drills.
What We Are Trying To Do
Build a community-level AI early-warning system using satellite and radar data to give advance alerts for floods and wildfires, backed by trained volunteer first responders.
Who It Serves
8,000 residents across flood-prone and wildfire-risk villages in 3 districts.
Key Activities
- Integrate satellite/radar data feeds into Azure ML early-warning prediction models
- Install community alert systems (sirens, SMS broadcast, WhatsApp bots) in 15 villages
- Equip 5 rapid-response teams with communication kits and emergency supplies
- Train 200 community volunteers in first aid, evacuation and emergency coordination
- Conduct 4 full-scale disaster simulation drills annually
Targets
Volunteers trained
200 certified emergency responders (target)
Annual drills
4 per year (target)
Alert lead time
6-hour advance warning (target)
Prediction accuracy
90%+ after calibration (target)
Loss reduction
40% (target)
Training
200 community volunteers proposed for training in first aid, evacuation and emergency coordination; connects naturally with Learn & Train's First Aid, CPR & Rescue school.
Connects with the Water, Climate & Disaster Resilience and First Aid, CPR & Rescue schools in Learn & Train.
Volunteering
200 trained community volunteers form the core first-responder network; 15 volunteer data scientists proposed for model calibration.
Partnership Opportunities
Microsoft Ask: Azure ML compute credits ($50K), AI for Good fund application, 15 volunteer data scientists, AI Nonprofit Advisor programme access.
Discuss This ProgrammeNo verified results have been recorded for this programme yet. Targets above represent proposed goals, not achieved outcomes.