Driver Drowsiness Alert System

A distracted driver poses a serious risk and leads to serious traffic accidents. This article presents a method using computer vision technology, specifically Python, OpenCV, and a DLib, to detect driver fatigue and warning issues. The system can measure sleepiness by analyzing facial expressions such as yawning, closed eyes, and head movements and can give audio warnings accordingly. Alerts range from mild drowsiness warnings to emergency contacts if the driver continues to shows drowsiness signs. The architecture of the system includes processing video from cameras and monitoring vital signs such as eye closing time and yawning frequency. In addition, the design of the system prioritizes the safety of the driver, helping to increase road safety and reduce accidents due to drowsy driving.