@article{Nguyen_C-2020_124767,
title = {A Comprehensive Survey of Enabling and Emerging Technologies for Social Distancing—Part II: Emerging Technologies and Open Issues},
author = {Nguyen, C. and Saputra, Y. and Van Huynh, N. and Nguyen, N. and Khoa, T. and Tuan, B. and Nguyen, D. and Hoang, D. and Vu, T. and Dutkiewicz, E. and Chatzinotas, S. and Ottersten, B.},
month = {aug},
year = {2020},
abstract = {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.},
pages = {154209-154236},
volume = {8},
journal = {IEEE Access},
publisher = {IEEE},
url = {https://doi.org/10.1109/access.2020.3018124},
}
