Context
Commuters navigating unfamiliar or high-incident routes lack localized safety advisories, structured incident reporting, and verified safe-pathway routing across municipal transit corridors.
What I built
- Engineered Django REST Framework spatial and route-planning endpoints mapping localized safety zones, incident hot-spots, and commuter alert corridors.
- Implemented relational schemas in PostgreSQL to store geocoded waypoint coordinates, hazard classifications, and time-stamped incident logs.
- Containerized backend API services and database configurations with Docker Compose for reproducible local development and staging environments.
Technical approach
- Client map and pathing requests from React communicate with Django REST viewsets designed around coordinate boundary queries.
- Waypoints and danger-flagged sectors are indexed with relational coordinates and spatial bounding boxes to prevent full-table scans during route evaluation.
- Structured API validation contracts verify incoming community incident reports (timestamps, category codes, latitude/longitude bounds) before database persistence.
- Docker Compose orchestrates the Python web service, PostgreSQL database container, and network isolation boundaries.
Security and verification
- Incident submission endpoints enforce payload sanitization, coordinate boundary validation, and rate limiting to prevent automated coordinate spoofing.
- Django test cases validate CRUD endpoints, coordinate format parsers, and permission checks for administrative incident verification.
- Environment configurations isolate database secrets and API credentials across container boundaries.
Current limits
- Route calculations currently run on bounding-box approximations rather than a dedicated external routing graph engine (such as pgRouting or OSRM).
- Incidents rely on synthetic community verification data; real-time transit telemetry integration is planned for future iterations.