Automated Driver Drowsiness Detection System using Computer Vision and Machine Learning

In recent years, road safety has become an increasingly pressing issue due to the increase in the number of fatal accidents throughout the world. Accidents are a major threat to road safety, and fatigue and drowsiness are the Primary causes of such incidents. In order to prevent such accidents, it is essential to detect and aware of signs that cause drowsiness or fatigue in a driver, and issue a timely warning. A range of technologies have been created to detect drowsy driving; however, computer vision and image processing technology can efficiently detect the drowsiness using facial expressions. As described, a system has been proposed that continuously monitors the driver’s facial expression by analyzing the eyes and mouth movement in order to detect any signs of drowsiness or emotional shifts. If any such changes are detected, the system will alert the driver and helps in avoiding potential danger. This system provides a low-cost and resource-efficient approach to monitoring driver behavior and it utilizes facial landmark analysis to assess a driver’s performance without the need for additional sensors or equipment.