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Home / Archives / Volume-6 / Issue-2 / Article-4

Volume - 6 | Issue - 2 | june 2024

Enhancing Road Safety: A Driver Fatigue Detection and Behaviour Monitoring System using Advanced Computer Vision Techniques Open Access
Ramneet Singh Chadha  , Jugesh, Jasmehar Singh  893
Pages: 122-134
Cite this article
Chadha, Ramneet Singh, Jugesh, and Jasmehar Singh. "Enhancing Road Safety: A Driver Fatigue Detection and Behaviour Monitoring System using Advanced Computer Vision Techniques." Journal of Ubiquitous Computing and Communication Technologies 6, no. 2 (2024): 122-134
Published
21 May, 2024
Abstract

Driver drowsiness is a major hazard to road safety, necessitating the development of reliable detection technologies. This study describes a revolutionary driver fatigue detection system that uses cutting-edge computer vision technologies. This system uses the MediaPipe framework for accurate face and hand detection and the Eye Aspect Ratio (EAR) for drowsiness detection. Furthermore, it uses the OpenCV solvePnP function for estimating rotation vector, and converting it to a rotation angle of the head, to check driver attention. By continuously monitoring these indicators, when the system successfully detects any instances of driver tiredness or inattention, it records his or her behavior and delivers notifications to help prevent accidents. This study helps to improve road safety by utilizing cutting-edge computer vision techniques to prevent driver fatigue and boost attentive driving practices.

Keywords

Fatigue detection Eye aspect ratio Drowsiness detection Head pose estimation Hand detection Mediapipe

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