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A real-time system that watches a driver's eyes and head position through a camera and raises an alarm when signs of drowsiness or distraction appear. Runs on a laptop or a Raspberry Pi mounted on the dashboard.
Problem Statement
Driver fatigue is a major cause of highway accidents. Commercial fatigue monitoring systems are expensive and limited to premium vehicles.
Objectives
Detect face and eye landmarks in real time
Compute eye aspect ratio and yawning frequency
Trigger audio alerts when drowsiness crosses a threshold
Log incidents for later review
Modules
Video Capture
Reads frames from a webcam or Pi camera and handles low-light preprocessing.
Landmark Detection
Locates eyes and mouth using facial landmark models.
Drowsiness Classifier
Combines eye closure duration, blink rate, and yawns into a fatigue score.
Alert & Logging
Buzzer or speaker alert plus a local log of drowsiness events with timestamps.
Expected Output
A working prototype that sounds an alarm within seconds of the driver's eyes closing and stores a log of fatigue events.
Future Scope
Head pose based distraction detection, phone usage detection, fleet dashboard for transport companies, and vehicle CAN bus integration.