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 Tr...

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Main Authors:	Hasan Gani, Muhammad Hamdan, Khalifa, Othman Omran, Gunawan, Teddy Surya, Emran, Shamsan
Format:	Conference or Workshop Item
Language:	English
Published:	IEEE 2017
Subjects:	TK Electrical engineering. Electronics Nuclear engineering
Online Access:	http://irep.iium.edu.my/60067/ http://irep.iium.edu.my/60067/ http://irep.iium.edu.my/60067/20/60067%20Traffic%20intensity%20monitoring%20using%20multiple%20object.pdf

id	iium-60067
recordtype	eprints
spelling	iium-600672018-07-10T09:28:48Z http://irep.iium.edu.my/60067/ Traffic intensity monitoring using multiple object detection with traffic surveillance cameras Hasan Gani, Muhammad Hamdan Khalifa, Othman Omran Gunawan, Teddy Surya Emran, Shamsan TK Electrical engineering. Electronics Nuclear engineering 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. IEEE 2017-11-28 Conference or Workshop Item PeerReviewed application/pdf en http://irep.iium.edu.my/60067/20/60067%20Traffic%20intensity%20monitoring%20using%20multiple%20object.pdf Hasan Gani, Muhammad Hamdan and Khalifa, Othman Omran and Gunawan, Teddy Surya and Emran, Shamsan (2017) Traffic intensity monitoring using multiple object detection with traffic surveillance cameras. In: 2017 IEEE International Conference on Smart Instrumentation, Measurement and Applications (ICSIMA 2017), 27th-29th Nov. 2017, Putrajaya. http://icsima.ieeemy-ims.org/17/
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English
topic	TK Electrical engineering. Electronics Nuclear engineering
spellingShingle	TK Electrical engineering. Electronics Nuclear engineering Hasan Gani, Muhammad Hamdan Khalifa, Othman Omran Gunawan, Teddy Surya Emran, Shamsan 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 Gunawan, Teddy Surya Emran, Shamsan
author_facet	Hasan Gani, Muhammad Hamdan Khalifa, Othman Omran Gunawan, Teddy Surya Emran, Shamsan
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	IEEE
publishDate	2017
url	http://irep.iium.edu.my/60067/ http://irep.iium.edu.my/60067/ http://irep.iium.edu.my/60067/20/60067%20Traffic%20intensity%20monitoring%20using%20multiple%20object.pdf
first_indexed	2023-09-18T21:25:09Z
last_indexed	2023-09-18T21:25:09Z
_version_	1777412141540704256

Traffic intensity monitoring using multiple object detection with traffic surveillance cameras

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