K. Nikolskaia, V. Bessonov, A. Starkov, A. Minbaleev
{"title":"Prototype of Driver Fatigue Detection System Using Convolutional Neural Network","authors":"K. Nikolskaia, V. Bessonov, A. Starkov, A. Minbaleev","doi":"10.1109/IT&QM&IS.2019.8928341","DOIUrl":null,"url":null,"abstract":"Driver fatigue is one of the major causes of accidents in the world. Detecting the drowsiness of the driver is one of the surest ways of measuring driver fatigue. In this paper we aim to develop a prototype drowsiness detection system. Presents a method for detecting the early signs of fatigue/drowsiness during driving. Analysing some environmental variables, it is possible to detect the loss of alertness prior to the driver falling asleep. This system works by monitoring the eyes of the driver and sounding an alarm when he/she is drowsy. As a result of this analysis, the system will determine if the subject is able to drive.","PeriodicalId":285904,"journal":{"name":"2019 International Conference \"Quality Management, Transport and Information Security, Information Technologies\" (IT&QM&IS)","volume":"80 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Conference \"Quality Management, Transport and Information Security, Information Technologies\" (IT&QM&IS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IT&QM&IS.2019.8928341","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
Driver fatigue is one of the major causes of accidents in the world. Detecting the drowsiness of the driver is one of the surest ways of measuring driver fatigue. In this paper we aim to develop a prototype drowsiness detection system. Presents a method for detecting the early signs of fatigue/drowsiness during driving. Analysing some environmental variables, it is possible to detect the loss of alertness prior to the driver falling asleep. This system works by monitoring the eyes of the driver and sounding an alarm when he/she is drowsy. As a result of this analysis, the system will determine if the subject is able to drive.
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