Abstract
The world has been facing a challenging issue of COVID-19, which has infected 223 countries and 223 billion deaths worldwide. It is believed that the world will need to take preventive measures against the COVID-19 pandemic until a vaccine is developed. Early detection of COVID19 infections is a major challenge for healthcare professionals, governments, and organizations to combat against the virus. Therefore, its need an intelligent monitoring system that detects COVID19 and tracks the infected person may improve clinical decision-making and stop spreading the virus among people. The Internet of things (IoT), machine learning, and the Deep learning approach changed our lives in the healthcare sector. This survey presents how IoT, machine learning, and deep learning are incorporated into the pandemic prevention and control system by detection, diagnosis, monitoring, tracing, and social distance finding. We examine and review the most recent literature and present the role of IoT, machine learning, and deep learning in combating the current COVID-19 pandemic. Further, we have also identified a few issues and research directions while using IoT during the COVID-19 pandemic.
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Imad, M., Hussain, A., Hassan, M.A., Butt, Z., Sahar, N.U. (2022). IoT Based Machine Learning and Deep Learning Platform for COVID-19 Prevention and Control: A Systematic Review. In: Boulouard, Z., Ouaissa, M., Ouaissa, M., El Himer, S. (eds) AI and IoT for Sustainable Development in Emerging Countries. Lecture Notes on Data Engineering and Communications Technologies, vol 105. Springer, Cham. https://doi.org/10.1007/978-3-030-90618-4_26
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