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Project: RoadWatch (Metropolitan Traffic Accident Pattern Recognition & Road Safety Engine)

Architecture

  • Frontend: Next.js 14/15 TypeScript application (frontend/), Tailwind CSS, Leaflet/Mapbox interactive visualization, responsive dark glassmorphism dashboard UI.
  • Backend API: Java 21 Spring Boot 3.3 Hexagonal/Clean Architecture (backend/), REST controllers, domain ports/adapters, data models.
  • ML Engine: Python 3.12 FastAPI microservice (ml-engine/), HDBSCAN spatial blackspot clustering, land-bound coordinate verification, climate rule engines.
  • Data Ingestion: Data generation/ingestion pipeline (data/), support for Ghana NRSA, UK DfT STATS19, US NHTSA FARS, EU CARE schemas.

Milestones

# Name Scope Dependencies Status
M0 E2E Testing Suite Opaque-box requirement-driven testing track (Tiers 1-4) None PLANNED
M1 UI/UX & Interactive Design High-density dashboard, dark glassmorphism, responsive UI None PLANNED
M2 Authentic Data & Spatial Ingestion Real open data schemas, HDBSCAN 6-pt clustering, land bounds, climate rules None PLANNED
M3 Backend & API Audit Java Spring Boot Hexagonal refactoring, Python FastAPI schema sync, remove mocks None PLANNED
M4 Institutional Use Cases Safety audits, Blackspot interventions, Telemetry ticker, Route navigation M1, M2, M3 PLANNED
M5 Health Audit, Verification & Git Push Full codebase cleanup, 100% E2E pass, Tier 5 hardening, push to GitHub M0, M1, M2, M3, M4 PLANNED

Interface Contracts

Frontend ↔ Backend REST API

  • GET /api/accidents: Query filtered accident incidents.
  • GET /api/blackspots: Spatial blackspots extracted from ML engine.
  • POST /api/analysis/safety-audit: Municipal traffic safety audit report.
  • POST /api/navigation/safe-route: Multi-modal route safety calculation.
  • GET /api/telemetry/live: Real-time emergency telemetry ticker stream.

Backend ↔ ML Engine REST API

  • POST /api/v1/ml/cluster: HDBSCAN spatial clustering on lat/lon coordinates.
  • POST /api/v1/ml/classify-risk: Risk assessment model inference.
  • POST /api/v1/ml/climate-validate: Enforce tropical climate rules & land boundaries.

Code Layout

  • frontend/: Next.js TypeScript web application.
  • backend/: Java Spring Boot 3.3 microservice (src/main/java/..., src/test/java/...).
  • ml-engine/: Python FastAPI service (main.py, app/...).
  • data/: Ingestion pipelines and datasets (synthetic_traffic_accidents.json, generate_dataset.py).