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Advances in crowd analysis for urban applications through urban event detection

  • Mohammed Shamim Kaiser*
  • , Khin T. Lwin
  • , Mufti Mahmud
  • , Donya Hajializadeh
  • , Tawee Chaipimonplin
  • , Ahmed Sarhan
  • , Mohammed Alamgir Hossain
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

89 Scopus citations

Abstract

The recent expansion of pervasive computing technology has contributed with novel means to pursue human activities in urban space. The urban dynamics unveiled by these means generate an enormous amount of data. These data are mainly endowed by portable and radio-frequency devices, transportation systems, video surveillance, satellites, unmanned aerial vehicles, and social networking services. This has opened a new avenue of opportunities, to understand and predict urban dynamics in detail, and plan various real-time services and applications in response to that. Over the last decade, certain aspects of the crowd, e.g., mobility, sentimental, size estimation and behavioral, have been analyzed in detail and the outcomes have been reported. This paper mainly conducted an extensive survey on various data sources used for different urban applications, the state-of-the-art on urban data generation techniques and associated processing methods in order to demonstrate their merits and capabilities. Then, available open-access crowd data sets for urban event detection are provided along with relevant application programming interfaces. In addition, an outlook on a support system for urban application is provided which fuses data from all the available pervasive technology sources and finally, some open challenges and promising research directions are outlined.

Original languageEnglish
Article number8194870
Pages (from-to)3092-3112
Number of pages21
JournalIEEE Transactions on Intelligent Transportation Systems
Volume19
Issue number10
DOIs
StatePublished - Oct 2018
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2018 IEEE.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 11 - Sustainable Cities and Communities
    SDG 11 Sustainable Cities and Communities

Keywords

  • Urban sensing
  • benchmark datasets
  • crowd mobility and management
  • decision support system
  • information fusion
  • pervasive technology

ASJC Scopus subject areas

  • Automotive Engineering
  • Mechanical Engineering
  • Computer Science Applications

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