Measuring the road traffic intensity using neural network with computer vision

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) t...

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Main Authors:	Hasan Gani, Muhammad Hamdan, Khalifa, Othman Omran, Gunawan, Teddy Surya
Format:	Article
Language:	English English
Published:	Indonesian Journal of Electrical Engineering and Computer Science ( IAES) 2018
Subjects:	TK7885 Computer engineering
Online Access:	http://irep.iium.edu.my/61796/ http://irep.iium.edu.my/61796/ http://irep.iium.edu.my/61796/ http://irep.iium.edu.my/61796/1/10890-15121-1-PBHamdanTraffic.pdf http://irep.iium.edu.my/61796/7/61796_Measuring%20the%20Road%20Traffic%20Intensity_scopus.pdf

id	iium-61796
recordtype	eprints
spelling	iium-617962018-02-13T03:17:40Z http://irep.iium.edu.my/61796/ Measuring the road traffic intensity using neural network with computer vision Hasan Gani, Muhammad Hamdan Khalifa, Othman Omran Gunawan, Teddy Surya TK7885 Computer engineering 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. Indonesian Journal of Electrical Engineering and Computer Science ( IAES) 2018-04 Article PeerReviewed application/pdf en http://irep.iium.edu.my/61796/1/10890-15121-1-PBHamdanTraffic.pdf application/pdf en http://irep.iium.edu.my/61796/7/61796_Measuring%20the%20Road%20Traffic%20Intensity_scopus.pdf 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 http://iaescore.com/journals/index.php/IJEECS/ 10.11591/ijeecs.v10.i1.pp184-190
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English English
topic	TK7885 Computer engineering
spellingShingle	TK7885 Computer engineering Hasan Gani, Muhammad Hamdan Khalifa, Othman Omran Gunawan, Teddy Surya Measuring the road traffic intensity using neural network with computer vision
description	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.
format	Article
author	Hasan Gani, Muhammad Hamdan Khalifa, Othman Omran Gunawan, Teddy Surya
author_facet	Hasan Gani, Muhammad Hamdan Khalifa, Othman Omran Gunawan, Teddy Surya
author_sort	Hasan Gani, Muhammad Hamdan
title	Measuring the road traffic intensity using neural network with computer vision
title_short	Measuring the road traffic intensity using neural network with computer vision
title_full	Measuring the road traffic intensity using neural network with computer vision
title_fullStr	Measuring the road traffic intensity using neural network with computer vision
title_full_unstemmed	Measuring the road traffic intensity using neural network with computer vision
title_sort	measuring the road traffic intensity using neural network with computer vision
publisher	Indonesian Journal of Electrical Engineering and Computer Science ( IAES)
publishDate	2018
url	http://irep.iium.edu.my/61796/ http://irep.iium.edu.my/61796/ http://irep.iium.edu.my/61796/ http://irep.iium.edu.my/61796/1/10890-15121-1-PBHamdanTraffic.pdf http://irep.iium.edu.my/61796/7/61796_Measuring%20the%20Road%20Traffic%20Intensity_scopus.pdf
first_indexed	2023-09-18T21:27:38Z
last_indexed	2023-09-18T21:27:38Z
_version_	1777412298432839680

Measuring the road traffic intensity using neural network with computer vision

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