System for Alcohol Detection and Drowsiness Monitoring Based on Face and Drowsiness Recognition Model

被引：0

作者：

Jang, Soyoung ^{[1
]}

Lee, Yeon Woo ^{[2
]}

Jung, Yuna ^{[2
]}

An, Eun Hyeon ^{[2
]}

Lee, Jaeho ^{[2
]}

机构：

[1] Department of Information & Communication Technology Convergence Engineering, Duksung University

[2] Department of Software, Duksung Universitys

来源：

Journal of Institute of Control, Robotics and Systems | 2025年 / 31卷 / 04期

关键词：

alcohol detection; drowsiness detection; facial recognition; real-time monitoring; Siamese Network;

D O I：

10.5302/J.ICROS.2025.25.0003

中图分类号：

学科分类号：

摘要：

This study introduces an integrated real-time monitoring system to enhance driver safety. The system incorporates facial recognition, alcohol detection, and drowsiness monitoring to comprehensively analyze the driver’s condition and provide appropriate responses. For facial recognition, it utilizes Google’s MediaPipe AI framework and a Siamese network model. Alcohol detection is achieved through real-time measurement of the driver’s alcohol level using an MQ3 sensor. Drowsiness monitoring is accomplished through a combination of blink detection using dlib and OpenCV with head-rotation techniques to assess driver fatigue in real time. The proposed system offers customized information to drivers via Android and web interfaces. This research demonstrates the potential of systems that analyze driver safety and respond accordingly in real time. © ICROS 2025.

引用

页码：343 / 350

页数：7

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