TY  - JOUR
ID  - SisLab4333
UR  - https://eprints.uet.vnu.edu.vn/eprints/id/eprint/4333/
A1  - Nguyen, Thanh Cong
A1  - Yuris Mulya, Saputra
A1  - Huynh, Van Nguyen
A1  - Nguyen, Ngoc Tan
A1  - Tran, Viet Khoa
A1  - Bui Minh, Tuan
A1  - Diep, Nguyen
A1  - Dinh, Thai Hoang
A1  - Vu, Xuan Thang
A1  - Eryk, Dutkiewicz
A1  - Symeon, Chatzinotas
A1  - Bjorn, Ottersten
N2  - 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
JF  - IEEE Access
SN  - 2169-3536
TI  - A Comprehensive Survey of Enabling and Emerging Technologies for Social Distancing??Part II: Emerging Technologies and Open Issues
AV  - public
ER  -