Muhammad Tanveer Jan, Ali Hashemi, Jinwoo Jang, Kwangsoo Yang, Jiannan Zhai, David Newman, Ruth Tappen, Borko Furht
{"title":"NON-INTRUSIVE DROWSINESS DETECTION TECHNIQUES AND THEIR APPLICATION IN DETECTING EARLY DEMENTIA IN OLDER DRIVERS.","authors":"Muhammad Tanveer Jan, Ali Hashemi, Jinwoo Jang, Kwangsoo Yang, Jiannan Zhai, David Newman, Ruth Tappen, Borko Furht","doi":"10.1007/978-3-031-18458-1_53","DOIUrl":null,"url":null,"abstract":"<p><p>Drowsy drivers cause the most car accidents thus, adopting an efficient drowsiness detection system can alert the driver promptly and precisely which will reduce the numbers of accidents and also save a lot of money. This paper discusses many tactics and methods for drowsy driving warning. The non-intrusive nature of most of the strategies mentioned and contrasted means both vehicular and behavioural techniques are examined here. Thus, the latest strategies are studied and discussed for both groups, together with their benefits and drawbacks. The goal of this review was to identify a practical and low-cost approach for analysing elder drivers' behaviour.</p>","PeriodicalId":74543,"journal":{"name":"Proceedings of the Future Technologies Conference (FTC) 2022. Volume 2. Future Technologies Conference (7th : 2022 : Vancouver, B.C.; Online)","volume":"560 V2","pages":"776-796"},"PeriodicalIF":0.0000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10037317/pdf/nihms-1881839.pdf","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Future Technologies Conference (FTC) 2022. Volume 2. Future Technologies Conference (7th : 2022 : Vancouver, B.C.; Online)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/978-3-031-18458-1_53","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
Drowsy drivers cause the most car accidents thus, adopting an efficient drowsiness detection system can alert the driver promptly and precisely which will reduce the numbers of accidents and also save a lot of money. This paper discusses many tactics and methods for drowsy driving warning. The non-intrusive nature of most of the strategies mentioned and contrasted means both vehicular and behavioural techniques are examined here. Thus, the latest strategies are studied and discussed for both groups, together with their benefits and drawbacks. The goal of this review was to identify a practical and low-cost approach for analysing elder drivers' behaviour.