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Measuring the road traffic intensity using neural network with computer vision

Hasan Gani, Muhammad Hamdan and Khalifa, Othman Omran and Gunawan, Teddy Surya (2018) Measuring the road traffic intensity using neural network with computer vision. Indonesian Journal of Electrical Engineering and Computer Science, 10 (1). pp. 184-190. ISSN 2502-4752 E-ISSN 2502-4760

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Abstract

Traffic congestion plagues all driver around the world. To solve this problem computer vision can be used as a tool to develop alternative routes and eliminate traffic congestions. In the current generation with increasing number of cameras on the streets and lower cost for Internet of Things(IoT) this solution will have a greater impact on current systems. In this paper, the Macroscopic Urban Traffic model is used using computer vision as its source and traffic intensity monitoring system is implemented. The input of this program is extracted from a traffic surveillance camera and another program running a neural network classification which can classify and distinguish the vehicle type is on the road. The neural network toolbox is trained with positive and negative input to increase accuracy. The accuracy of the program is compared to other related works done and the trends of the traffic intensity from a road is also calculated.

Item Type: Article (Journal)
Additional Information: 4119/61796
Uncontrolled Keywords: Neural Network; Object Detection; Traffic Intensity
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices > TK7885 Computer engineering
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): Kulliyyah of Engineering > Department of Electrical and Computer Engineering
Kulliyyah of Information and Communication Technology > Department of Information System
Kulliyyah of Information and Communication Technology > Department of Information System
Depositing User: Dr Teddy Surya Gunawan
Date Deposited: 13 Feb 2018 11:17
Last Modified: 13 Feb 2018 11:17
URI: http://irep.iium.edu.my/id/eprint/61796

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