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: Proceeding Paper
Language:English
English
Published: IOP Publishing 2017
Subjects:
Online Access: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
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author Hasan Gani, Muhammad Hamdan
Khalifa, Othman Omran
author_facet Hasan Gani, Muhammad Hamdan
Khalifa, Othman Omran
author_sort Hasan Gani, Muhammad Hamdan
building IIUM Repository
collection Online Access
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.
first_indexed 2025-11-14T16:51:32Z
format Proceeding Paper
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institution International Islamic University Malaysia
institution_category Local University
language English
English
last_indexed 2025-11-14T16:51:32Z
publishDate 2017
publisher IOP Publishing
recordtype eprints
repository_type Digital Repository
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 Proceeding Paper 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
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
title 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_short Traffic intensity monitoring using multiple object detection with traffic surveillance cameras
title_sort traffic intensity monitoring using multiple object detection with traffic surveillance cameras
topic T Technology (General)
TL1 Motor vehicles
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