About: Enabling and Emerging Technologies for Social Distancing: A Comprehensive Survey

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An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Enabling and Emerging Technologies for Social Distancing: A Comprehensive Survey
Creator	Nguyen, Diep Chatzinotas, Symeon Dutkiewicz, Eryk Hoang, Dinh Nguyen, Cong Nguyen, Ngoc-Tan Ottersten, Björn Saputra, Yuris Tuan, Bui Van Huynh, Nguyen Viet Khoa, Tran Vu, Thang
Source	ArXiv
abstract	Social distancing is crucial for preventing the spread of viral diseases illnesses such as COVID-19. By minimizing the closely physical contact between people, we can reduce chances of catching the virus and spreading it to the community. This paper aims to provide a comprehensive survey on how emerging technologies, e.g., wireless and networking, AI can enable, encourage, and even enforce social distancing. To that end, we provide a fundamental background of social distancing including basic concepts, measurements, models and propose practical scenarios. We then discuss enabling wireless technologies which are especially effective and can be widely adopted in practice to keep distance and monitor people. After that, emerging technologies such as machine learning, computer vision, thermal, ultrasound, etc., are introduced. These technologies open many new solutions and directions to deal with problems in social distancing, e.g., symptom prediction, detection and monitoring quarantined people, and contact tracing. Finally, we provide important open issues and challenges (e.g., privacy-preserving, cybersecurity) in implementing social distancing in practice.
has issue date	2020-05-01(xsd:dateTime)
has license	arxiv
sha1sum (hex)	cae62fb7f84f1278c36521d50c55ec93d0c363b0
resource representing a document's title	Enabling and Emerging Technologies for Social Distancing: A Comprehensive Survey
resource representing a document's body	covid:cae62fb7f84f1278c36521d50c55ec93d0c363b0#body_text
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