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http://ir.futminna.edu.ng:8080/jspui/handle/123456789/8680
Title: | In-Vehicle Traffic Accident Detection and Alerting System Using Distance-Time Based Parameters and Radar Range Algorithm |
Authors: | Ajao, Lukman Adewale Kolo, Jonathan Gana Abisoye, Blessing Olatunde Jibril, Ibrahim Zakariyawu Jonah, Udeme Monday |
Keywords: | Accelerometer Emergency unit Internet of things Road traffic Wireless sensors |
Issue Date: | 2020 |
Publisher: | 2020 IEEE PES/IAS PowerAfrica Conference |
Citation: | Lukman Adewale Ajao, Jonathan Gana Kolo, Blessing Olatunde Abisoye, Ibrahim Zakariyawu Jibril, Udeme Monday Jonah, "In-Vehicle Traffic Accident Detection and Alerting System Using Distance-Time Based Parameters and Radar Range Algorithm", 2020 IEEE PES/IAS PowerAfrica Conference, http://dx.doi.org/10.1109/PowerAfrica49420.2020 |
Abstract: | The high proportion number of citizen death rates with little or severe sustained injury is commonly recorded from road-traffic accidents (RTA). The effect of a road traffic accident is brutal, and it usually leads to mortality and deformity in human physiological anatomy. This work aims to develop an embedded in-vehicle automatic accident detection and barrier detection notification system. A radar range algorithm (RRA) is proposed for the barrier detection on the road before collision occurrence. Also, distance-time based parameters (DTBP) algorithm was developed for the detection of accident geo-location coordinates using the Haversine formula. An Internet of Things (IoT) approach was adopted by integrating the wireless communication devices and sensors embedded into a single chip for the design purposes. This developed system alerts the driver before collision occurrence and eliminates the delay time between accident occurrence and emergency personnel arrival. The use of this system will save more lives from road hazards and decrease mortality. |
URI: | http://repository.futminna.edu.ng:8080/jspui/handle/123456789/8680 |
Appears in Collections: | Electrical/Electronic Engineering |
Files in This Item:
File | Description | Size | Format | |
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2020 IEEE PESIAS PowerAfrica_In-Vehicle Traffic Accident.pdf | 129.63 kB | Adobe PDF | View/Open |
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