Full Text:   <1908>

Summary:  <534>

CLC number: TP399

On-line Access: 2024-08-27

Received: 2023-10-17

Revision Accepted: 2024-05-08

Crosschecked: 2023-11-06

Cited: 0

Clicked: 2452

Citations:  Bibtex RefMan EndNote GB/T7714

 ORCID:

Zhiguang SHAN

https://orcid.org/0000-0002-0253-5151

Lei SHI

https://orcid.org/0000-0002-1965-2602

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Article info.
Open peer comments

Frontiers of Information Technology & Electronic Engineering  2024 Vol.25 No.2 P.286-307

http://doi.org/10.1631/FITEE.2300453


Empowering smart city situational awareness via big mobile data


Author(s):  Zhiguang SHAN, Lei SHI, Bo LI, Yanqiang ZHANG, Xiatian ZHANG, Wei CHEN

Affiliation(s):  State Information Center, Beijing 100045, China; more

Corresponding email(s):   shanzg@sic.gov.cn, leishi@buaa.edu.cn, libo@act.buaa.edu.cn, zhangyanqiang@163.com

Key Words:  Smart city, Mobile data, Situational awareness



Abstract: 
smart city situational awareness has recently emerged as a hot topic in research societies, industries, and governments because of its potential to integrate cutting-edge information technology and solve urgent challenges that modern cities face. For example, in the latest five-year plan, the Chinese government has highlighted the demand to empower smart city management with new technologies such as big data and Internet of Things, for which situational awareness is normally the crucial first step. While traditional static surveillance data on cities have been available for decades, this review reports a type of relatively new yet highly important urban data source, i.e., the big mobile data collected by devices with various levels of mobility representing the movement and distribution of public and private agents in the city. We especially focus on smart city situational awareness enabled by synthesizing the localization of hundreds of thousands of mobile software Apps using the Global Positioning System (GPS). This technique enjoys advantages such as a large penetration rate (~50% urban population covered), uniform spatiotemporal coverage, and high localization precision. We first discuss the pragmatic requirements for smart city situational awareness and the challenges faced. Then we introduce two suites of empowering technologies that help fulfill the requirements of (1) cybersecurity insurance for smart cities and (2) spatiotemporal modeling and visualization for situational awareness, both via big mobile data. The main contributions of this review lie in the description of a comprehensive technological framework for smart city situational awareness and the demonstration of its feasibility via real-world applications.

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