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http://dx.doi.org/10.6109/jkiice.2022.26.6.859

Driver Drowsiness Detection System using Image Recognition and Bio-signals  

Lee, Min-Hye (Center for General Education, Wonkwang University)
Shin, Seong-Yoon (School of Computer Information & Communication Engineering, Kunsan National University)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.26, no.6, 2022 , pp. 859-864 More about this Journal
Abstract
Drowsy driving, one of the biggest causes of traffic accidents every year, is accompanied by various factors. As a general method to check whether or not there is drowsiness, a method of identifying a driver's expression and driving pattern, and a method of analyzing bio-signals are being studied. This paper proposes a driver fatigue detection system using deep learning technology and bio-signal measurement technology. As the first step in the proposed method, deep learning is used to detect the driver's eye shape, yawning presence, and body movement to detect drowsiness. In the second stage, it was designed to increase the accuracy of the system by identifying the driver's fatigue state using the pulse wave signal and body temperature. As a result of the experiment, it was possible to reliably determine the driver's drowsiness and fatigue in real-time images.
Keywords
Deep learning; Bio-signals; Image recognition; Drowsy driving; Fatigue detection;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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