TY - JOUR
AU - Nguyen, Cong T.
AU - Saputra, Yuris Mulya
AU - Van Huynh, Nguyen
AU - Nguyen, Ngoc-Tan
AU - Khoa, Tran Viet
AU - Tuan, Bui Minh
AU - Nguyen, Diep N.
AU - Hoang, Dinh Thai
AU - Vu, Thang X.
AU - Dutkiewicz, Eryk
AU - Chatzinotas, Symeon
AU - Ottersten, Bjorn
PY - 2020
DA - August
TI - A Comprehensive Survey of Enabling and Emerging Technologies for Social Distancing—Part II: Emerging Technologies and Open Issues
JO - IEEE Access
EP - 154236
VL - 8
DO - https://doi.org/10.1109/access.2020.3018124
AB - 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 Part I, an extensive background of social distancing is provided, and enabling wireless technologies are thoroughly surveyed. In this Part II, 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 discuss open issues and challenges (e.g., privacy-preserving, scheduling, and incentive mechanisms) in implementing social distancing in practice. As an example, instead of reacting with ad-hoc responses to COVID-19-like pandemics in the future, smart infrastructures (e.g., next-generation wireless systems like 6G, smart home/building, smart city, intelligent transportation systems) should incorporate a pandemic mode in their standard architectures/designs.
PB - IEEE
UR - http://researchrepository.napier.ac.uk/Output/3057412
KW - Coronavirus (COVID-19)
ER