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Author:

Ju, Min (Ju, Min.) | Zhang, Xiaobo (Zhang, Xiaobo.) | Huang, Zhangqin (Huang, Zhangqin.)

Indexed by:

EI Scopus

Abstract:

With the rapid advancement of urban modernization and the sustainable development of economy, the problems of driving difficulty and parking difficulty are increasingly prominent in large, medium and small cities. In order to alleviate the contradiction between urban space and vehicle growth rate and improve the utilization efficiency of parking resources, based on the roadside parking data of Nanshan District in Shenzhen City, this paper combines the time series data visualization method and geospatial data visualization method in multi-dimensional data visualization, and adopts the mode of view collaborative interaction to design the intelligent roadside parking collaborative interactive visualization system. The system integrates multisource data, displays roadside parking data information in an all-round way, supports exploratory analysis of roadside parking data characteristics and laws, and helps to understand parking demand and parking distribution at different times and regions. It provides decision support for optimizing parking resource allocation and roadside parking management. © 2024 IEEE.

Keyword:

Decision support systems Data visualization Urban growth Smart city Visualization Roadsides

Author Community:

  • [ 1 ] [Ju, Min]Beijing University of Technology, Beijing Engineering Research Center for IoT Software and Systems, Beijing, China
  • [ 2 ] [Zhang, Xiaobo]Beijing University of Technology, Beijing Engineering Research Center for IoT Software and Systems, Beijing, China
  • [ 3 ] [Huang, Zhangqin]Beijing University of Technology, Beijing Engineering Research Center for IoT Software and Systems, Beijing, China

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Source :

ISSN: 2689-6621

Year: 2024

Page: 1618-1622

Language: English

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 2

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