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Machine vision based smart parking system using internet of things

It is expected that in the next decade, majority of world population will be living in cities. Better public services and infrastructures in the city are needed to cope with the booming population. City vehicles that cruising for parking have indirectly causing traffic, making one harder to travel a...

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Main Authors:	Loong, D. N. C., Isaak, S., Yusof, Y.
Format:	Article
Language:	English
Published:	Universitas Ahmad Dahlan 2019
Subjects:	TK Electrical engineering. Electronics Nuclear engineering
Online Access:	http://eprints.utm.my/id/eprint/89967/1/YusmeerazYusof2019_MachineVisionBasedSmartParking.pdf http://eprints.utm.my/id/eprint/89967/ https://dx.doi.org/10.12928/TELKOMNIKA.v17i4.12772
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id	my.utm.89967
record_format	eprints
spelling	my.utm.899672021-03-29T05:57:24Z http://eprints.utm.my/id/eprint/89967/ Machine vision based smart parking system using internet of things Loong, D. N. C. Isaak, S. Yusof, Y. TK Electrical engineering. Electronics Nuclear engineering It is expected that in the next decade, majority of world population will be living in cities. Better public services and infrastructures in the city are needed to cope with the booming population. City vehicles that cruising for parking have indirectly causing traffic, making one harder to travel around the city. Thus, a smart parking system can certainly lays the foundation to build a smart city. This paper proposed a cost-effective IoT smart parking system to monitor city parking space and provide real-time parking information to drivers. Moreover, instead of the conventional approach that uses embedded sensors to detect vehicles in the parking area, camera image and machine vision technology are used to obtain the parking status. In the prototype, twenty outdoor parking lots are covered using a 5 megapixel camera connected to Raspberry Pi 3 installed at the 5th floor of the nearby building. Machine vision in this project that involved motion tracking and Canny edge detection are programmed in Python 2 using OpenCV technology. Corresponding data is uploaded to an IoT platform called Ubidots for possible monitoring activity. An Android mobile application is designed for user to download real-time data of parking information. This paper introduces a low cost smart parking system with the overall detection accuracy of 96.40%. Also, the mobile application allows users to alert other car owners for any emergency incidents and double parking blockage. The developed system can provide a platform for users to search for empty car parking with ease and reduce the traffic issues such as illegal double parking especially in the urban area. Universitas Ahmad Dahlan 2019 Article PeerReviewed application/pdf en http://eprints.utm.my/id/eprint/89967/1/YusmeerazYusof2019_MachineVisionBasedSmartParking.pdf Loong, D. N. C. and Isaak, S. and Yusof, Y. (2019) Machine vision based smart parking system using internet of things. Telkomnika (Telecommunication Computing Electronics and Control), 17 (4). ISSN 1693-6930 https://dx.doi.org/10.12928/TELKOMNIKA.v17i4.12772 DOI: 10.12928/TELKOMNIKA.v17i4.12772
institution	Universiti Teknologi Malaysia
building	UTM Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Teknologi Malaysia
content_source	UTM Institutional Repository
url_provider	http://eprints.utm.my/
language	English
topic	TK Electrical engineering. Electronics Nuclear engineering
spellingShingle	TK Electrical engineering. Electronics Nuclear engineering Loong, D. N. C. Isaak, S. Yusof, Y. Machine vision based smart parking system using internet of things
description	It is expected that in the next decade, majority of world population will be living in cities. Better public services and infrastructures in the city are needed to cope with the booming population. City vehicles that cruising for parking have indirectly causing traffic, making one harder to travel around the city. Thus, a smart parking system can certainly lays the foundation to build a smart city. This paper proposed a cost-effective IoT smart parking system to monitor city parking space and provide real-time parking information to drivers. Moreover, instead of the conventional approach that uses embedded sensors to detect vehicles in the parking area, camera image and machine vision technology are used to obtain the parking status. In the prototype, twenty outdoor parking lots are covered using a 5 megapixel camera connected to Raspberry Pi 3 installed at the 5th floor of the nearby building. Machine vision in this project that involved motion tracking and Canny edge detection are programmed in Python 2 using OpenCV technology. Corresponding data is uploaded to an IoT platform called Ubidots for possible monitoring activity. An Android mobile application is designed for user to download real-time data of parking information. This paper introduces a low cost smart parking system with the overall detection accuracy of 96.40%. Also, the mobile application allows users to alert other car owners for any emergency incidents and double parking blockage. The developed system can provide a platform for users to search for empty car parking with ease and reduce the traffic issues such as illegal double parking especially in the urban area.
format	Article
author	Loong, D. N. C. Isaak, S. Yusof, Y.
author_facet	Loong, D. N. C. Isaak, S. Yusof, Y.
author_sort	Loong, D. N. C.
title	Machine vision based smart parking system using internet of things
title_short	Machine vision based smart parking system using internet of things
title_full	Machine vision based smart parking system using internet of things
title_fullStr	Machine vision based smart parking system using internet of things
title_full_unstemmed	Machine vision based smart parking system using internet of things
title_sort	machine vision based smart parking system using internet of things
publisher	Universitas Ahmad Dahlan
publishDate	2019
url	http://eprints.utm.my/id/eprint/89967/1/YusmeerazYusof2019_MachineVisionBasedSmartParking.pdf http://eprints.utm.my/id/eprint/89967/ https://dx.doi.org/10.12928/TELKOMNIKA.v17i4.12772
_version_	1696976241967497216
score	13.211869

Machine vision based smart parking system using internet of things

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