Traffic intensity monitoring using multiple object detection with traffic surveillance cameras

Object detection and tracking is a field of research that has many applications in the current generation with increasing number of cameras on the streets and lower cost for Internet of Things(IoT). In this paper, a traffic intensity monitoring system is implemented based on the Macroscopic Urban...

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Main Authors:	Hasan Gani, Muhammad Hamdan, Khalifa, Othman Omran
Format:	Conference or Workshop Item
Language:	English English
Published:	IOP Publishing 2017
Subjects:	T Technology (General) TL1 Motor vehicles
Online Access:	http://irep.iium.edu.my/59584/ http://irep.iium.edu.my/59584/ http://irep.iium.edu.my/59584/ http://irep.iium.edu.my/59584/1/Traffic%20intensity%20monitoring%20using%20multiple%20object%20Muhammad_Hamdan_2017_IOP_Conf._Ser.%253A_Mater._Sci._Eng._260_012009.pdf http://irep.iium.edu.my/59584/12/59584%20Traffic%20intensity%20monitoring%20using%20multiple%20object%20detection%20SCOPUS.pdf

id	iium-59584
recordtype	eprints
spelling	iium-595842018-03-22T08:28:11Z http://irep.iium.edu.my/59584/ Traffic intensity monitoring using multiple object detection with traffic surveillance cameras Hasan Gani, Muhammad Hamdan Khalifa, Othman Omran T Technology (General) TL1 Motor vehicles Object detection and tracking is a field of research that has many applications in the current generation with increasing number of cameras on the streets and lower cost for Internet of Things(IoT). In this paper, a traffic intensity monitoring system is implemented based on the Macroscopic Urban Traffic model is proposed using computer vision as its source. The input of this program is extracted from a traffic surveillance camera which has another program running a neural network classification which can identify and differentiate the vehicle type is implanted. 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. relevant articles in literature searches, great care should be taken in constructing both. Lastly the limitation and the future work is concluded. IOP Publishing 2017-11-07 Conference or Workshop Item PeerReviewed application/pdf en http://irep.iium.edu.my/59584/1/Traffic%20intensity%20monitoring%20using%20multiple%20object%20Muhammad_Hamdan_2017_IOP_Conf._Ser.%253A_Mater._Sci._Eng._260_012009.pdf application/pdf en http://irep.iium.edu.my/59584/12/59584%20Traffic%20intensity%20monitoring%20using%20multiple%20object%20detection%20SCOPUS.pdf Hasan Gani, Muhammad Hamdan and Khalifa, Othman Omran (2017) Traffic intensity monitoring using multiple object detection with traffic surveillance cameras. In: 6th International Conference on Mechatronics - ICOM'17, 8th–9th August 2017, Kuala Lumpur. http://iopscience.iop.org/article/10.1088/1757-899X/260/1/012009 10.1088/1757-899X/260/1/012009
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English English
topic	T Technology (General) TL1 Motor vehicles
spellingShingle	T Technology (General) TL1 Motor vehicles Hasan Gani, Muhammad Hamdan Khalifa, Othman Omran Traffic intensity monitoring using multiple object detection with traffic surveillance cameras
description	Object detection and tracking is a field of research that has many applications in the current generation with increasing number of cameras on the streets and lower cost for Internet of Things(IoT). In this paper, a traffic intensity monitoring system is implemented based on the Macroscopic Urban Traffic model is proposed using computer vision as its source. The input of this program is extracted from a traffic surveillance camera which has another program running a neural network classification which can identify and differentiate the vehicle type is implanted. 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. relevant articles in literature searches, great care should be taken in constructing both. Lastly the limitation and the future work is concluded.
format	Conference or Workshop Item
author	Hasan Gani, Muhammad Hamdan Khalifa, Othman Omran
author_facet	Hasan Gani, Muhammad Hamdan Khalifa, Othman Omran
author_sort	Hasan Gani, Muhammad Hamdan
title	Traffic intensity monitoring using multiple object detection with traffic surveillance cameras
title_short	Traffic intensity monitoring using multiple object detection with traffic surveillance cameras
title_full	Traffic intensity monitoring using multiple object detection with traffic surveillance cameras
title_fullStr	Traffic intensity monitoring using multiple object detection with traffic surveillance cameras
title_full_unstemmed	Traffic intensity monitoring using multiple object detection with traffic surveillance cameras
title_sort	traffic intensity monitoring using multiple object detection with traffic surveillance cameras
publisher	IOP Publishing
publishDate	2017
url	http://irep.iium.edu.my/59584/ http://irep.iium.edu.my/59584/ http://irep.iium.edu.my/59584/ http://irep.iium.edu.my/59584/1/Traffic%20intensity%20monitoring%20using%20multiple%20object%20Muhammad_Hamdan_2017_IOP_Conf._Ser.%253A_Mater._Sci._Eng._260_012009.pdf http://irep.iium.edu.my/59584/12/59584%20Traffic%20intensity%20monitoring%20using%20multiple%20object%20detection%20SCOPUS.pdf
first_indexed	2023-09-18T21:24:25Z
last_indexed	2023-09-18T21:24:25Z
_version_	1777412096126877696

Traffic intensity monitoring using multiple object detection with traffic surveillance cameras

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