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 language | English |
|---|---|
| Article number | 8194870 |
| Pages (from-to) | 3092-3112 |
| Number of pages | 21 |
| Journal | IEEE Transactions on Intelligent Transportation Systems |
| Volume | 19 |
| Issue number | 10 |
| DOIs | |
| State | Published - Oct 2018 |
| Externally published | Yes |
Bibliographical note
Publisher Copyright:© 2018 IEEE.
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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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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