Sonjoy Rana, Shounak Sengupta, Sourav Jana, Rahul Dan, Mahamuda Sultana, D. Sengupta
{"title":"Prototype Proposal for Quick Accident Detection and Response System","authors":"Sonjoy Rana, Shounak Sengupta, Sourav Jana, Rahul Dan, Mahamuda Sultana, D. Sengupta","doi":"10.1109/ICRCICN50933.2020.9296153","DOIUrl":null,"url":null,"abstract":"Traffic accidents contribute to an annual death toll of 1.25 million marking one of the primary causes of fatality. The Post Accident Response for such an alarming Figure calls for an immediate and effective Emergency Care which takes into account a series of time critical procedures beginning with the activation of the Quick Accident Response System (QARS) proposed in this communication. The implementation of Internet of Things (IoT) in QARS helps to detect an accident using multi-functional accelerometer and ultrasonic/proximity sensors. The video recording of the accident along with the exact location of the accident site fetched using a GPS-GSM module, along with the driver details will be immediately notified via internet to the nearest Emergency Response Units (ERU) through the Emergency Services portal of a dedicated mobile application. Pedestrians can also use the Pedestrian portal in the application to send live image and video feed to the Emergency services. An offline feature, allows sending accident alert and exact accident location to the nearest ERUs/pre-saved emergency contact numbers in the form of a simple text message. The work in this paper provides an automated system for emergency support in case of accidents.","PeriodicalId":138966,"journal":{"name":"2020 Fifth International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 Fifth International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICRCICN50933.2020.9296153","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
Traffic accidents contribute to an annual death toll of 1.25 million marking one of the primary causes of fatality. The Post Accident Response for such an alarming Figure calls for an immediate and effective Emergency Care which takes into account a series of time critical procedures beginning with the activation of the Quick Accident Response System (QARS) proposed in this communication. The implementation of Internet of Things (IoT) in QARS helps to detect an accident using multi-functional accelerometer and ultrasonic/proximity sensors. The video recording of the accident along with the exact location of the accident site fetched using a GPS-GSM module, along with the driver details will be immediately notified via internet to the nearest Emergency Response Units (ERU) through the Emergency Services portal of a dedicated mobile application. Pedestrians can also use the Pedestrian portal in the application to send live image and video feed to the Emergency services. An offline feature, allows sending accident alert and exact accident location to the nearest ERUs/pre-saved emergency contact numbers in the form of a simple text message. The work in this paper provides an automated system for emergency support in case of accidents.