Bike Lane Sentinel
Computer vision system monitoring illegal vehicle encroachment in NYC bike lanes with automated DOT alerts
Bike Lane Sentinel uses computer vision to detect vehicles illegally parked or driving in NYC bike lanes. The system processes live camera feeds, identifies vehicles, determines lane boundaries, and flags encroachment violations with timestamped evidence packages sent automatically to NYC DOT.
The full-stack application includes a React/TypeScript dashboard with real-time violation heatmaps, a Node.js backend with a violation database and analytics API, and a camera integration layer for live video processing. The system is designed for deployment at high-violation intersections across New York City.
Key Highlights
Real-time
Violation Detection
NYC DOT
Automated Alerts
127K+
Lines of Code
Full-Stack
Frontend + Backend
Architecture Details
- Object Detection: Vehicle classification and lane boundary analysis from live camera feeds.
- Violation Engine: Encroachment detection with evidence capture (screenshots, timestamps, location data).
- Interactive Dashboard: React + TypeScript frontend with real-time violation heatmaps and analytics.
- Backend API: Node.js server with violation database, search, and reporting endpoints.
- Civic Impact: Designed to improve cyclist safety by automating enforcement reporting to NYC DOT.
Tech Stack
Computer VisionTypeScriptReactNode.js
JavaScriptReal-time Processing