Driver Drowsiness Detection using Artificial Intelligence

Abstract

The goal of the research is to show how artificial intelligence may be used to identify driver tiredness using visual processing. Experts estimate that over a quarter of all serious car accidents are brought on by drivers who are too sleepy to pay attention to the road. As a result, we know that tiredness is a more common contributor to car accidents than intoxication. Vision-based ideas were used to design the Drowsiness Detection System. The gadget relies on a small camera to detect drowsiness in drivers by examining their eyes and scanning their face. The Viola-Jones and Hough transform are the techniques utilised by the system to first scan the driver's face, then the eyes, and then check whether the eyes are open or closed using artificial intelligence software. The system works with binary pictures to scan the sides of the face, reducing the space where the eyes will be located. Let's say that the eyes are shown to be closed for five or more consecutive frames. When this occurs, the system tracks the driver's level of activity and determines that the driver is dozing off, so it sounds an alert or produces an alarm signal to wake him up.