Drowsiness Detection According to the Number of Blinking Eyes Specified From Eye Aspect Ratio Value Modification

Abstract

The current accidents in road increase caused by driver's negligence. There are several reasons, that is fatigue, drowsiness, not concentration, and others. One of the drowsiness detectors is through the blinking of an eye. In normal people the blinking of the eye is 10 per minute, whereas in people who are sleepy eye blinks below 10 per minute. In this research we proposed the modified algorithm to have eye aspect ratio value. Experimental data are taken from video with 30 frames per second. Experiments were performed in the laboratory with driver simulation tools. Data are taken for 105 minutes and given the load test so that the driver will experience fatigue while driving. Keywords-modified of eye aspect ratio; drowsiness; blinking rate, , = / (2)

Design and Implementation of an IoT Drowsiness Detection System for Drivers

“…Eye closure pertains to the count of frames in which closed eyes are detected within a specified time interval. As outlined in [27], a driver is classified as drowsy when the number of consecutive frames depicting closed eyes surpasses 45 frames, equivalent to approximately 1.5 seconds. The detection of eye blinking occurs when the eye's state transitions from open to closed.…”

“…Based on existing literature, it is established that an average individual blinks approximately ten times per minute [27]. Therefore, if the frequency of eye blinking falls below this norm, the driver is deemed drowsy.…”