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Disaster Coordination Network — Real-Time Disaster Management System
A real-time disaster coordination platform with PostGIS-based geospatial data, DBSCAN clustering, and AI-powered vehicle recommendations using MCDM algorithms.
Python FastAPI PostgreSQL PostGIS SQLAlchemy JWT Scikit-learn Docker
Problem
During disasters, lack of coordination, resource waste, and slow response times reduce life-saving capacity. A real-time, geospatial data-based coordination system was needed.
Approach
Worked as Backend Developer in a 4-person team:
- Geospatial Infrastructure: Location-based disaster reporting and querying with PostgreSQL + PostGIS
- Data Integration: AFAD and Kandilli Observatory API integrations
- AI Algorithms: Automatic task packaging with DBSCAN clustering; real-time ETA calculation with Haversine formula
- Decision Support: AI-powered vehicle recommendation using Multi-Criteria Decision Making (MCDM)
- Security: JWT-based authentication, Role-Based Access Control (RBAC)
- Deployment: Container-based deployment with Docker Compose
Outcome
A scalable system equipped with AI-driven decision mechanisms enabling disaster coordinators to manage real-time location, resource, and response data.