Driver Drowsiness Detection System Using Image Recognition

Drowsiness and driver fatigue are significant contributors to road traffic accidents worldwide. Effective detection and intervention are crucial to prevent fatigued individuals from driving. This research presents an innovative system utilizing facial recognition technology to monitor signs of driver fatigue, such as drooping eyelids and frequency of yawning. The system operates in real-time, providing immediate feedback and suggestions for the driver to take restorative actions, such as taking breaks or finding nearby rest areas. This technology holds particular promise for commercial long-haul drivers who are at high risk due to extended periods of driving. By encouraging timely rest, the system has the potential to reduce the incidence of fatigue-related accidents, enhancing road safety for all.