RailRadar is a real-time train detection and arrival prediction system built for communities impacted by rail crossings.

Using a distributed network of camera-based tripwire sensors, RailRadar detects train movements at the edge and generates bias-corrected ETAs that adapt to real-world conditions. The system delivers timely, reliable alerts without relying on railroad-provided data or centralized tracking feeds.

RailRadar is designed for resilience and accuracy in the field. The platform supports community alerts, operational monitoring, and future integrations with municipal and transportation systems.

This project includes full-stack system design, edge sensing logic, backend services, alerting infrastructure, and deployment workflows focused on real-world reliability, not demos.