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Article

A Computer Vision-Based Roadside Occupation Surveillance System for Intelligent Transport in Smart Cities

1
Department of Supply Chain and Information Management, The Hang Seng University of Hong Kong, Shatin, Hong Kong, China
2
Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hunghom, Hong Kong, China
*
Author to whom correspondence should be addressed.
Sensors 2019, 19(8), 1796; https://doi.org/10.3390/s19081796
Received: 14 March 2019 / Revised: 6 April 2019 / Accepted: 12 April 2019 / Published: 15 April 2019
(This article belongs to the Special Issue Smart Energy and Cities in the IoT Era)
In digital and green city initiatives, smart mobility is a key aspect of developing smart cities and it is important for built-up areas worldwide. Double-parking and busy roadside activities such as frequent loading and unloading of trucks, have a negative impact on traffic situations, especially in cities with high transportation density. Hence, a real-time internet of things (IoT)-based system for surveillance of roadside loading and unloading bays is needed. In this paper, a fully integrated solution is developed by equipping high-definition smart cameras with wireless communication for traffic surveillance. Henceforth, this system is referred to as a computer vision-based roadside occupation surveillance system (CVROSS). Through a vision-based network, real-time roadside traffic images, such as images of loading or unloading activities, are captured automatically. By making use of the collected data, decision support on roadside occupancy and vacancy can be evaluated by means of fuzzy logic and visualized for users, thus enhancing the transparency of roadside activities. The CVROSS was designed and tested in Hong Kong to validate the accuracy of parking-gap estimation and system performance, aiming at facilitating traffic and fleet management for smart mobility. View Full-Text
Keywords: smart mobility; computer vision; roadside occupation; traffic surveillance; smart city smart mobility; computer vision; roadside occupation; traffic surveillance; smart city
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MDPI and ACS Style

Ho, G.T.S.; Tsang, Y.P.; Wu, C.H.; Wong, W.H.; Choy, K.L. A Computer Vision-Based Roadside Occupation Surveillance System for Intelligent Transport in Smart Cities. Sensors 2019, 19, 1796. https://doi.org/10.3390/s19081796

AMA Style

Ho GTS, Tsang YP, Wu CH, Wong WH, Choy KL. A Computer Vision-Based Roadside Occupation Surveillance System for Intelligent Transport in Smart Cities. Sensors. 2019; 19(8):1796. https://doi.org/10.3390/s19081796

Chicago/Turabian Style

Ho, George T.S., Yung P. Tsang, Chun H. Wu, Wai H. Wong, and King L. Choy 2019. "A Computer Vision-Based Roadside Occupation Surveillance System for Intelligent Transport in Smart Cities" Sensors 19, no. 8: 1796. https://doi.org/10.3390/s19081796

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