A Comprehensive Survey of Enabling and Emerging Technologies for Social Distancing-Part II: Emerging Technologies and Open Issues

IEEE Access. 2020 Aug 20;8:154209-154236. doi: 10.1109/ACCESS.2020.3018124. eCollection 2020.


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.

Keywords: AI; COVID-19; Social distancing; data analytics; incentive mechanism; localization; machine learning; networking; pandemic; positioning systems; privacy-preserving; scheduling; wireless.

Grant support

This work was supported in part by the Joint Technology and Innovation Research Centre—a partnership between the University of Technology Sydney (UTS), in part by the Vietnam National University, University of Engineering and Technology Hanoi (VNU UET), and in part by the Vietnam National University, Ho Chi Minh City University of Technology (VNU HCMUT).