| Project Name | AI/ML-Based Nearest Recovery Point Recommendation |
|---|---|
| Technologies | Python, ML, GIS, Mobile App |
| Problem Statement | People often cannot locate nearest recovery/disaster points during emergencies |
| AI Component | Location-based predictive modeling |
| Solution | ML-powered mobile system recommending nearest safe points based on GPS & risk zones |
| Impact | Improves global disaster preparedness & enhances safety |
| Location ID | Name | Latitude | Longitude | Capacity | Type |
|---|---|---|---|---|---|
| R001 | City Central Relief Camp | 19.0760 | 72.8777 | 450 | Flood Shelter |
| R002 | Westside Emergency Point | 19.2183 | 73.0033 | 320 | Medical Aid Center |
| R003 | North Zone Recovery Hub | 18.5204 | 73.8567 | 500 | Earthquake Relief |
| User ID | Latitude | Longitude | Timestamp | Risk Zone Level |
|---|---|---|---|---|
| U101 | 19.0900 | 72.8800 | 2025-11-18 10:45 | High |
| U102 | 18.6000 | 73.9000 | 2025-11-18 10:47 | Medium |
| U103 | 19.2200 | 73.0500 | 2025-11-18 10:51 | Low |
| Recommendation ID | User ID | Recommended Point | Distance (km) | Estimated Arrival Time | Confidence Score |
|---|---|---|---|---|---|
| REC001 | U101 | R001 | 1.4 | 6 mins | 0.92 |
| REC002 | U102 | R003 | 3.2 | 14 mins | 0.88 |
| REC003 | U103 | R002 | 2.1 | 10 mins | 0.94 |