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Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/6422
Title: A FRAMEWORK FOR INTEGRATION OF WIRELESS SENSORS NETWORK AND OBJECT DETECTION SYSTEM TO MONITOR CARELESS DRIVING: THE CASE OF ADDIS ABABA
Authors: Mesfin, Birhanu
Keywords: Wireless sensor network, object detection system, Intelligent Transportation Systems, MonitorCarDriving
Issue Date: Feb-2021
Publisher: ST. MARY’S UNIVERSITY
Abstract: Road traffic accidents are a global problem affecting all sectors of society. An accident is an error that occurs in the driver-vehicle-roadway system. According to the literature reviewed different things in the driver-vehicle-roadway system contribute to traffic accident among which Careless driving is a very common reason especially in developing countries like Ethiopia. As a result of car accidents, the death of human and property loss has been part of our news menu every day. Every morning we see dead animals (beginning from small birds to the bigger Mammals like hyena and other) on the street. Previous research works on Wireless Sensor Network proposed different solutions to reduce accidents with the mechanism of prevention, warning, and reporting, but they are not enough to bring a strong solution. As the survey made shows the cases of most car accidents are a result of violating traffic rules such as over-speeding, abrupt lane change, and traffic light violation. This research demonstrates that the Ethiopian traffic management system has been using very old systems which has very limited capacity. In this proposed work, monitoring driving behavior with the help of wireless sensor technology is the target. So the proposed research work focused on developing a framework for integrating wireless sensor network and object detection system which used python socket programming, Doppler vehicle speed sensor, surveillance camera, light-emitting diodes, and proximity sensor nodes to develop the system. It is shown that the functionality of the proposed framework help in reducing abrupt lane-changing behavior, traffic light violation, and over speeding.
URI: .
http://hdl.handle.net/123456789/6422
Appears in Collections:Master of computer science

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