Detection of Driver Drowsiness Using Artificial Intelligence and Machine Learning

Drowsy driving can be caused by a variety of things, such as not getting enough sleep, long commutes, working shifts, and taking certain drugs. In addition, variables like drinking or using drugs and underlying medical illnesses like sleep disorders can make it worse when a person is driving while drowsy. It happens when a driver cannot retain complete focus and alertness while driving because of exhaustion or sleep deprivation. According to estimates, drowsy driving may contribute to up to 40% of traffic accidents, with potentially serious effects. It leads to the design of a system for real-time hardware and software solutions to detect and prevent drowsy driving to address this problem. On the hardware side, a camera is used to gather information regarding the conduct and physical condition of the driver. This considered things like camera distance, eye movements, and facial expressions. Software algorithms are created to examine this data in real time and find patterns that point to drowsy driving. The system can take several steps to warn the driver and avoid an accident when it detects drowsy driving. These procedures include alarm sounding and warning message display. This could help to avoid an accident. The accuracy of the proposed system is 86.34% and the time taken for detecting the drowsiness is 70.67 s. The estimated overall speed is 14.29 frames per second.