Terjaga App

Challenge

Build a real-time driver monitoring system that detects drowsiness using camera-based ML models to prevent accidents and improve road safety. The challenge was implementing accurate facial landmark detection and drowsiness recognition with minimal latency.

Solution

Developed a Flutter app with integrated camera access and PyTorch-based ML model for real-time drowsiness detection. Built a Flask API backend that processes video frames and provides alerts. Implemented audio/haptic alerts and logging system to track driver safety metrics.

Results

Gallery