{"title":"基于物联网的事故后援助系统","authors":"Neel Desai, P. Kulkarni, L. Joy, Prachi Raut","doi":"10.1109/ICOEI48184.2020.9142894","DOIUrl":null,"url":null,"abstract":"Road accidents are often fatal and result into major losses to families and nations. Precious lives can be saved if medical help is made available to the victims at the earliest. Several systems were proposed which provide automated accident detection and notification facility. However, majority of these systems depend on user's smartphones and applications. This paper presents an IoT based Post Crash Assistance system which used a vehicle's in-built hardware hence eliminating dependency on the smartphone. Also, the system is able to differentiate between various crash intensities and is able to respond accordingly. After exhaustive testing, it was determined that this system gives 98.33% accuracy and response time of 16.24s.","PeriodicalId":267795,"journal":{"name":"2020 4th International Conference on Trends in Electronics and Informatics (ICOEI)(48184)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"IoT based Post Crash Assistance System\",\"authors\":\"Neel Desai, P. Kulkarni, L. Joy, Prachi Raut\",\"doi\":\"10.1109/ICOEI48184.2020.9142894\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Road accidents are often fatal and result into major losses to families and nations. Precious lives can be saved if medical help is made available to the victims at the earliest. Several systems were proposed which provide automated accident detection and notification facility. However, majority of these systems depend on user's smartphones and applications. This paper presents an IoT based Post Crash Assistance system which used a vehicle's in-built hardware hence eliminating dependency on the smartphone. Also, the system is able to differentiate between various crash intensities and is able to respond accordingly. After exhaustive testing, it was determined that this system gives 98.33% accuracy and response time of 16.24s.\",\"PeriodicalId\":267795,\"journal\":{\"name\":\"2020 4th International Conference on Trends in Electronics and Informatics (ICOEI)(48184)\",\"volume\":\"27 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 4th International Conference on Trends in Electronics and Informatics (ICOEI)(48184)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICOEI48184.2020.9142894\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 4th International Conference on Trends in Electronics and Informatics (ICOEI)(48184)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICOEI48184.2020.9142894","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Road accidents are often fatal and result into major losses to families and nations. Precious lives can be saved if medical help is made available to the victims at the earliest. Several systems were proposed which provide automated accident detection and notification facility. However, majority of these systems depend on user's smartphones and applications. This paper presents an IoT based Post Crash Assistance system which used a vehicle's in-built hardware hence eliminating dependency on the smartphone. Also, the system is able to differentiate between various crash intensities and is able to respond accordingly. After exhaustive testing, it was determined that this system gives 98.33% accuracy and response time of 16.24s.