{"title":"睡意和打哈欠检测系统的设计","authors":"Vishwas Dehankar, Pranjali M. Jumle, S. Tadse","doi":"10.1109/ICEARS56392.2023.10085310","DOIUrl":null,"url":null,"abstract":"The goal of this study is to demonstrate a non- invasive method for assessing driver tiredness and yawning utilising behavioural and vehicle-based methodologies. Today's traffic accidents occur as the result of driver negligence. The drivers gross recklessness and intoxicated behaviour were on display. On this problem many research works was going on to overcome such accidents, which depends on abnormal behaviour of drivers, drunken driver detections, and many more. The driver tiredness and yawning detection system is one of the research work on the same domain which employs a Raspberry Pi microcontroller to focus on the driver's unusual behaviour. The suggested method uses computer vision techniques to provide a non- intrusive driver drowsiness and yawning monitoring system. The system can detect driver fatigue in two to three seconds, irrespective of whether driver is wearing spectacles or the inside of the vehicle is dark.","PeriodicalId":338611,"journal":{"name":"2023 Second International Conference on Electronics and Renewable Systems (ICEARS)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Design of Drowsiness and Yawning Detection System\",\"authors\":\"Vishwas Dehankar, Pranjali M. Jumle, S. Tadse\",\"doi\":\"10.1109/ICEARS56392.2023.10085310\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The goal of this study is to demonstrate a non- invasive method for assessing driver tiredness and yawning utilising behavioural and vehicle-based methodologies. Today's traffic accidents occur as the result of driver negligence. The drivers gross recklessness and intoxicated behaviour were on display. On this problem many research works was going on to overcome such accidents, which depends on abnormal behaviour of drivers, drunken driver detections, and many more. The driver tiredness and yawning detection system is one of the research work on the same domain which employs a Raspberry Pi microcontroller to focus on the driver's unusual behaviour. The suggested method uses computer vision techniques to provide a non- intrusive driver drowsiness and yawning monitoring system. The system can detect driver fatigue in two to three seconds, irrespective of whether driver is wearing spectacles or the inside of the vehicle is dark.\",\"PeriodicalId\":338611,\"journal\":{\"name\":\"2023 Second International Conference on Electronics and Renewable Systems (ICEARS)\",\"volume\":\"6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-03-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 Second International Conference on Electronics and Renewable Systems (ICEARS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICEARS56392.2023.10085310\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 Second International Conference on Electronics and Renewable Systems (ICEARS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICEARS56392.2023.10085310","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The goal of this study is to demonstrate a non- invasive method for assessing driver tiredness and yawning utilising behavioural and vehicle-based methodologies. Today's traffic accidents occur as the result of driver negligence. The drivers gross recklessness and intoxicated behaviour were on display. On this problem many research works was going on to overcome such accidents, which depends on abnormal behaviour of drivers, drunken driver detections, and many more. The driver tiredness and yawning detection system is one of the research work on the same domain which employs a Raspberry Pi microcontroller to focus on the driver's unusual behaviour. The suggested method uses computer vision techniques to provide a non- intrusive driver drowsiness and yawning monitoring system. The system can detect driver fatigue in two to three seconds, irrespective of whether driver is wearing spectacles or the inside of the vehicle is dark.