{"title":"Safety of Drivers Against Drowsiness—An Urgent Need of Present Day World","authors":"Sidhant Gandotra, S. Mohan","doi":"10.1166/asem.2020.2607","DOIUrl":null,"url":null,"abstract":"The risks associated with driving have resulted in severe tragedies and amongst these drowsiness is one such major risk. The state of drowsiness in drivers has led to accidents resulting in significant monetary losses, serious injuries and even deaths. Drivers involved in driving for\n longer times and distances are more prone to the state of drowsiness. The issues related to drowsiness have encouraged many researchers to develop detection mechanisms so that accidents could be averted. Researchers have discovered that most common basis for the detection of drowsiness are\n physiological based measures, behavioral based measures, subjective base measures and vehicle based measures. However, many researchers still endeavor to find more efficient solution for the detection of driver drowsiness. In this paper, major causes for drowsiness have been discussed. Various\n systems based upon which drowsiness can be detected have also been elaborated. Moreover, the conclusion of this paper focuses upon the gaps which if worked upon will bring new ways and means for developing a better and reliable system for detecting drowsiness. This paper will significantly\n contribute to the automobile industry as it will bring forth existing methods to detect drowsiness, and will also serve as a strong basis for the development of a robust drowsiness detection system which can be used as a safety feature for every automobile.","PeriodicalId":7213,"journal":{"name":"Advanced Science, Engineering and Medicine","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advanced Science, Engineering and Medicine","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1166/asem.2020.2607","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The risks associated with driving have resulted in severe tragedies and amongst these drowsiness is one such major risk. The state of drowsiness in drivers has led to accidents resulting in significant monetary losses, serious injuries and even deaths. Drivers involved in driving for
longer times and distances are more prone to the state of drowsiness. The issues related to drowsiness have encouraged many researchers to develop detection mechanisms so that accidents could be averted. Researchers have discovered that most common basis for the detection of drowsiness are
physiological based measures, behavioral based measures, subjective base measures and vehicle based measures. However, many researchers still endeavor to find more efficient solution for the detection of driver drowsiness. In this paper, major causes for drowsiness have been discussed. Various
systems based upon which drowsiness can be detected have also been elaborated. Moreover, the conclusion of this paper focuses upon the gaps which if worked upon will bring new ways and means for developing a better and reliable system for detecting drowsiness. This paper will significantly
contribute to the automobile industry as it will bring forth existing methods to detect drowsiness, and will also serve as a strong basis for the development of a robust drowsiness detection system which can be used as a safety feature for every automobile.