Reference : A Comprehensive Survey of Enabling and Emerging Technologies for Social Distancing—Pa...

	Document type :	Scientific journals : Article
	Discipline(s) :	Engineering, computing & technology : Electrical & electronics engineering
	To cite this reference:	http://hdl.handle.net/10993/45096

Title :	A Comprehensive Survey of Enabling and Emerging Technologies for Social Distancing—Part I: Fundamentals and Enabling Technologies
Language :	English
Author, co-author :	Nguyen, Cong T. []
	Saputra, Yuris M. []
	Nguyen, Huynh Van []
	Nguyen []
	Tran, Viet-Khoa []
	Bui, Minh Tuan []
	Nguyen, Diep N. []
	Dinh, Thai Hoang []
	Vu, Thang Xuan [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SigCom >]
	Dutkiewicz, Eryk []
	Chatzinotas, Symeon [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SigCom >]
	Ottersten, Björn [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Publication date :	Aug-2020
Journal title :	IEEE Access
Publisher :	Institute of Electrical and Electronics Engineers
Volume :	8
Pages :	153479 - 153507
Peer reviewed :	Yes (verified by ORBilu)
Audience :	International
ISSN :	2169-3536
City :	Piscataway
Country :	NJ
Keywords :	[en] social distancing ; COVID-19 ; machine learning
Abstract :	[en] Social distancing plays a pivotal role in preventing the spread of viral diseases illnesses such as COVID-19. By minimizing the close physical contact among people, we can reduce the chances of catching the virus and spreading it across the community. This two-part paper aims to provide a comprehensive survey on how emerging technologies, e.g., wireless and networking, artificial intelligence (AI) can enable, encourage, and even enforce social distancing practice. In this Part I, we provide a comprehensive background of social distancing including basic concepts, measurements, models, and propose various practical social distancing scenarios. We then discuss enabling wireless technologies which are especially effect in social distancing, e.g., symptom prediction, detection and monitoring quarantined people, and contact tracing. The companion paper Part II surveys other emerging and related technologies, such as machine learning, computer vision, thermal, ultrasound, etc., and discusses open issues and challenges (e.g., privacy preserving, scheduling, and incentive mechanisms) in implementing social distancing in practice
Permalink :	http://hdl.handle.net/10993/45096

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	Fulltext file(s): File Commentary Version Size Access Open access SurveyCovid-1.pdf Publisher postprint 4.96 MB View/Open

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