A Dual Stage Alert System for Drowsy Driving Prevention

Drowsy driving is a leading cause of road accidents, emphasizing the importance of an effective driver alert system. This study introduces an intelligent monitoring solution that identifies eyelid closure through a vision based method and employs a two step alert process. When prolonged eye closure is detected, the system first emits a beep sound and delivers a verbal warning. Additionally, it plays the driver’s favorite music to help them stay awake. By leveraging real time image processing and machine learning techniques, this approach ensures precise drowsiness detection. Experimental results show that this method significantly reduces reaction time and helps drivers remains attentive, providing a non-intrusive and adaptable safety solution.