Nikhil Kumar, Anurag Barthwal, Divya Lohani, D. Acharya
{"title":"Modeling IoT Enabled Automotive System for Accident Detection and Classification","authors":"Nikhil Kumar, Anurag Barthwal, Divya Lohani, D. Acharya","doi":"10.1109/SAS48726.2020.9220030","DOIUrl":null,"url":null,"abstract":"Millions of people get injured, disabled or die in automotive accidents each year. Knowledge about the type of road accident is invaluable to the emergency medical services providers for optimal planning and execution of the rescue operation. An IoT based system has been developed in this work to report the occurrence, location as well as the type of road accident. The system uses in-built sensors of passenger smartphone to detect and classify the accident as head-on collision, rollover or fall-off. The accuracy of the proposed system, which uses Naïve Bayes classifier for classification, has been evaluated using precision, recall, F1 score and ROC curve.","PeriodicalId":223737,"journal":{"name":"2020 IEEE Sensors Applications Symposium (SAS)","volume":"46 18","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE Sensors Applications Symposium (SAS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SAS48726.2020.9220030","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9
Abstract
Millions of people get injured, disabled or die in automotive accidents each year. Knowledge about the type of road accident is invaluable to the emergency medical services providers for optimal planning and execution of the rescue operation. An IoT based system has been developed in this work to report the occurrence, location as well as the type of road accident. The system uses in-built sensors of passenger smartphone to detect and classify the accident as head-on collision, rollover or fall-off. The accuracy of the proposed system, which uses Naïve Bayes classifier for classification, has been evaluated using precision, recall, F1 score and ROC curve.
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