Empowering smart city situational awareness via big mobile data

IF 2.7 3区 工程技术 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS
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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.

通过移动大数据增强智慧城市态势感知能力
摘 要 智慧城市态势感知是近期研究机构、行业和政府的热门话题,因为它具有整合前沿信息技术、解决现代城市面临的紧迫挑战的潜力。例如,在最新的五年计划中,中国政府强调了利用大数据和物联网等新技术加强智慧城市管理的需求,而态势感知通常是其中至关重要的第一步。传统的城市静态监控数据已有几十年的历史,而本综述报告的是一种相对较新但非常重要的城市数据源,即由不同移动程度的设备收集的移动大数据,这些设备代表了城市中公共和私人主体的移动和分布情况。我们尤其关注通过使用全球定位系统(GPS)综合数十万移动软件应用程序的定位来实现的智慧城市态势感知。这种技术具有渗透率高(覆盖城市人口的 50%)、时空覆盖均匀和定位精度高等优势。我们首先讨论了智慧城市态势感知的实际需求和面临的挑战。然后,我们介绍了两套赋能技术,它们有助于满足以下要求:(1) 智慧城市网络安全保险;(2) 通过移动大数据实现时空建模和可视化态势感知。本综述的主要贡献在于描述了智慧城市态势感知的综合技术框架,并通过实际应用展示了其可行性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Frontiers of Information Technology & Electronic Engineering
Frontiers of Information Technology & Electronic Engineering COMPUTER SCIENCE, INFORMATION SYSTEMSCOMPU-COMPUTER SCIENCE, SOFTWARE ENGINEERING
CiteScore
6.00
自引率
10.00%
发文量
1372
期刊介绍: Frontiers of Information Technology & Electronic Engineering (ISSN 2095-9184, monthly), formerly known as Journal of Zhejiang University SCIENCE C (Computers & Electronics) (2010-2014), is an international peer-reviewed journal launched by Chinese Academy of Engineering (CAE) and Zhejiang University, co-published by Springer & Zhejiang University Press. FITEE is aimed to publish the latest implementation of applications, principles, and algorithms in the broad area of Electrical and Electronic Engineering, including but not limited to Computer Science, Information Sciences, Control, Automation, Telecommunications. There are different types of articles for your choice, including research articles, review articles, science letters, perspective, new technical notes and methods, etc.
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