This project implements a real-time, adaptive AI system designed for in-vehicle deployment. It detects speed breakers using vehicle sensor data and issues driver warnings or autonomous intervention decisions.
- Real-time sensor stream processing
- Country-agnostic adaptive baseline learning
- Offline validation on Los Angeles and Kenya road datasets
- Deployment-ready decision logic
Datasets are used only for offline validation. The deployed model does not depend on datasets or retraining.