학술논문

A Comprehensive Survey of Enabling and Emerging Technologies for Social Distancing: Part I Fundamentals and Enabling Technologies
Document Type
Source
IEEE Access. 8:153479-153507
Subject
AI
COVID-19
data analytics
incentive mechanism
localization
machine learning
networking
pandemic
positioning systems
privacy-preserving
scheduling
Social distancing
wireless
Language
English
ISSN
21693536
Abstract
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.