The System for Driver Fatigue Monitoring Using Decision Tree via Wireless Sensor Network for Intelligent Transport System

Worawut Yimyam, M. Ketcham
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引用次数: 18

Abstract

Researchers propose new algorithm to monitor fatigue of driver by tracking the movements of the eyes. This can classify the opening and closing eyes by using Haar-Like Features and Region of Interest techniques. The fatique can be classified by decision tree classification. The system works in real time and sends message to the mobile phone to alert the driver via Line Application. The results showed that the program can detect face and classify opening and closing eyes accurately at 99.93 percent in which it yielded higher accuracy than other algorithms.
基于无线传感器网络的智能交通系统驾驶员疲劳监测系统
研究人员提出了一种新的算法,通过跟踪眼睛的运动来监测司机的疲劳。利用Haar-Like feature和感兴趣区域技术对睁眼和闭眼进行分类。采用决策树分类法对疲劳进行分类。该系统实时工作,并通过Line Application向手机发送信息,提醒司机。结果表明,该程序对人脸的检测和睁眼和闭眼的分类准确率达到99.93%,比其他算法的准确率更高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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