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An Efficient Route Selection Based on AODV Algorithm for VANET

Nassir Sallom , Kadhim and Mohammed, Muamer N. and Mazlina, Abdul Majid and Sinan Q., Mohamd (2016) An Efficient Route Selection Based on AODV Algorithm for VANET. In: The Fifth International Conference On Computer Science & Computational Mathematics (ICCSCM 2016), 5-6 May 2016 , Langkawi, Malaysia. pp. 1-6., 9 (38). ISSN (Print) 0974-6846; (Online) 0974-5645

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Abstract

Road safety is an all-time global concern. Every day a large number of human lives are lost with many sustaining a disability as a result of their injury due to car accidents and delay in calling the rescue services. Recently, intelligent transportation systems (ITS) have emerged as an efficient way of improving interpretation of transportation systems and enhancing travel safety. Accident detection systems are one of the most effective (ITS) tools. The accident detection system which based on Global Positioning System (GPS) and Global System for Mobile communication (GSM) can be accomplish though one or several sensors, the system can gathers the information and coordinates of accident spot then send this data to the rescues services center over a network link in shortest time, In this paper, we propose enhance system that composed of a GPS receiver, Vibration sensor, GSM Modem and integrated with Vehicular AD-Hoc Network (VANET). The employment of (VANET) assists to increase the data delivery by providing a second path to send an emergency message to the rescue services center (RSC) whenever an accident located at out of coverage area for GSM network. Simulation result shown that VANET modified algorithm based on average signal strength has the advantage of choosing the optimum route to deliver data and own enhanced ratio (17%) by comparing with a maximum signal strength route.

Item Type: Conference or Workshop Item (Speech)
Uncontrolled Keywords: global positioning system, global system for mobile, VANE, AODV
Subjects: Q Science > QA Mathematics > QA76 Computer software
Faculty/Division: Faculty of Computer System And Software Engineering
Depositing User: Mrs. Neng Sury Sulaiman
Date Deposited: 23 Dec 2016 05:21
Last Modified: 05 Feb 2018 03:21
URI: http://umpir.ump.edu.my/id/eprint/14041
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