Saad Ur Rehman, Shaheryar Ahmad Khan, A. Arif, U. S. Khan
{"title":"基于物联网的摩托车事故检测与应急报警系统","authors":"Saad Ur Rehman, Shaheryar Ahmad Khan, A. Arif, U. S. Khan","doi":"10.1109/AIMS52415.2021.9466055","DOIUrl":null,"url":null,"abstract":"This paper proposes the design of an accident detection system for motorcycles that notifies the emergency contact of the injured motorcycle driver about their precise location so that necessary medical help can be provided timely. The proposed system is based on a tilt sensor that calculates the inclination of the motorcycle and then transmits notification to the concerned people through SMS and GPRS via an online server using a GSM module. The main contribution of this paper is that the developed system has extensively been tested in real time scenario and data has been collected from ten different bikes to determine an optimum tilt angle. Moreover, crash tests have also been performed. The system has a detection rate of 97.33%.","PeriodicalId":299121,"journal":{"name":"2021 International Conference on Artificial Intelligence and Mechatronics Systems (AIMS)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"IoT-based Accident Detection and Emergency Alert System for Motorbikes\",\"authors\":\"Saad Ur Rehman, Shaheryar Ahmad Khan, A. Arif, U. S. Khan\",\"doi\":\"10.1109/AIMS52415.2021.9466055\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes the design of an accident detection system for motorcycles that notifies the emergency contact of the injured motorcycle driver about their precise location so that necessary medical help can be provided timely. The proposed system is based on a tilt sensor that calculates the inclination of the motorcycle and then transmits notification to the concerned people through SMS and GPRS via an online server using a GSM module. The main contribution of this paper is that the developed system has extensively been tested in real time scenario and data has been collected from ten different bikes to determine an optimum tilt angle. Moreover, crash tests have also been performed. The system has a detection rate of 97.33%.\",\"PeriodicalId\":299121,\"journal\":{\"name\":\"2021 International Conference on Artificial Intelligence and Mechatronics Systems (AIMS)\",\"volume\":\"41 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-04-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 International Conference on Artificial Intelligence and Mechatronics Systems (AIMS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/AIMS52415.2021.9466055\",\"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 Artificial Intelligence and Mechatronics Systems (AIMS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AIMS52415.2021.9466055","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
IoT-based Accident Detection and Emergency Alert System for Motorbikes
This paper proposes the design of an accident detection system for motorcycles that notifies the emergency contact of the injured motorcycle driver about their precise location so that necessary medical help can be provided timely. The proposed system is based on a tilt sensor that calculates the inclination of the motorcycle and then transmits notification to the concerned people through SMS and GPRS via an online server using a GSM module. The main contribution of this paper is that the developed system has extensively been tested in real time scenario and data has been collected from ten different bikes to determine an optimum tilt angle. Moreover, crash tests have also been performed. The system has a detection rate of 97.33%.