A computer vision-based roadside occupation surveillance system for intelligent transport in smart cities

George To Sum Ho, Yung Po Tsang, Chun Ho Wu (Corresponding Author), Wai Hung Wong, King Lun Choy

Research output: Journal article publicationJournal articleAcademic researchpeer-review

59 Citations (Scopus)


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.

Original languageEnglish
Article number1796
JournalSensors (Switzerland)
Issue number8
Publication statusPublished - 2 Apr 2019


  • Computer vision
  • Roadside occupation
  • Smart city
  • Smart mobility
  • Traffic surveillance

ASJC Scopus subject areas

  • Analytical Chemistry
  • Biochemistry
  • Atomic and Molecular Physics, and Optics
  • Instrumentation
  • Electrical and Electronic Engineering


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