Advances in crowd analysis for urban applications through urban event detection Authors

Mohammed Shamim Kaiser, Khin Lwin, Mufti Mahmud, Donya Hajializadeh, Tawee Chaipimonplin, Ahmed Sarhan, Alamgir Hossain

Research output: Contribution to journalArticlepeer-review

374 Downloads (Pure)

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
Pages (from-to)3092-3112
JournalIEEE Transactions on Intelligent Transportation Systems
Volume19
Issue number10
Early online date13 Dec 2017
DOIs
Publication statusPublished - 3 Oct 2018

Fingerprint

Dive into the research topics of 'Advances in crowd analysis for urban applications through urban event detection Authors'. Together they form a unique fingerprint.

Cite this