G. Roshini, Y. Kavya, R. Hareesh, M. Suma, N. Sunny
{"title":"驾驶员分心和困倦检测系统","authors":"G. Roshini, Y. Kavya, R. Hareesh, M. Suma, N. Sunny","doi":"10.1109/CONIT51480.2021.9498348","DOIUrl":null,"url":null,"abstract":"The major cause of deaths in our world is a car accident. Nearly around 1.5 billion people die due to car accidents and majority are happening just due to a simple factor that is drowsiness of driver. Most of the people travel for long distances without any sleep and using mobile phones while driving this results to the issue of tiredness and as a result to the drowsiness. This can be avoided just by alerting the driver when there is any such case of occurrence. So we are proposing a system which can alert the driver using a alarm when the driver gets distracted or feels drowsy. The aim of this project is to build the driver distraction prediction system that will detect whether persons eyes are closed or not.","PeriodicalId":426131,"journal":{"name":"2021 International Conference on Intelligent Technologies (CONIT)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Driver Distraction and Drowsiness Detection System\",\"authors\":\"G. Roshini, Y. Kavya, R. Hareesh, M. Suma, N. Sunny\",\"doi\":\"10.1109/CONIT51480.2021.9498348\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The major cause of deaths in our world is a car accident. Nearly around 1.5 billion people die due to car accidents and majority are happening just due to a simple factor that is drowsiness of driver. Most of the people travel for long distances without any sleep and using mobile phones while driving this results to the issue of tiredness and as a result to the drowsiness. This can be avoided just by alerting the driver when there is any such case of occurrence. So we are proposing a system which can alert the driver using a alarm when the driver gets distracted or feels drowsy. The aim of this project is to build the driver distraction prediction system that will detect whether persons eyes are closed or not.\",\"PeriodicalId\":426131,\"journal\":{\"name\":\"2021 International Conference on Intelligent Technologies (CONIT)\",\"volume\":\"19 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-06-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 International Conference on Intelligent Technologies (CONIT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CONIT51480.2021.9498348\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 International Conference on Intelligent Technologies (CONIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CONIT51480.2021.9498348","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Driver Distraction and Drowsiness Detection System
The major cause of deaths in our world is a car accident. Nearly around 1.5 billion people die due to car accidents and majority are happening just due to a simple factor that is drowsiness of driver. Most of the people travel for long distances without any sleep and using mobile phones while driving this results to the issue of tiredness and as a result to the drowsiness. This can be avoided just by alerting the driver when there is any such case of occurrence. So we are proposing a system which can alert the driver using a alarm when the driver gets distracted or feels drowsy. The aim of this project is to build the driver distraction prediction system that will detect whether persons eyes are closed or not.