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IoT-Based COVID-19 Diagnosing and Monitoring Systems: A Survey

  • University of Gloucestershire
  • Department of Signal Theory and Communications
  • Universidad Carlos III de Madrid
  • Kongju National University
  • Shaheed Benazir Bhutto Women University
  • Prince Sattam Bin Abdulaziz University
  • Aswan University
  • Public University of Navarre
  • Instituto Tecnológico de Estudios Superiores de Monterrey

Research output: Contribution to a Journal (Peer & Non Peer)Articlepeer-review

11 Citations (Scopus)

Abstract

To date, the novel Coronavirus (SARS-CoV-2) has infected millions and has caused the deaths of thousands of people around the world. At the moment, five antibodies, two from China, two from the U.S., and one from the UK, have already been widely utilized and numerous vaccines are under the trail process. In order to reach herd immunity, around 70% of the population would need to be inoculated. It may take several years to hinder the spread of SARS-CoV-2. Governments and concerned authorities have taken stringent measurements such as enforcing partial, complete, or smart lockdowns, building temporary medical facilities, advocating social distancing, and mandating masks in public as well as setting up awareness campaigns. Furthermore, there have been massive efforts in various research areas and a wide variety of tools, technologies and techniques have been explored and developed to combat the war against this pandemic. Interestingly, machine learning (ML) algorithms and internet of Things (IoTs) technology are the pioneers in this race. Up till now, several real-time and intelligent IoT-based COVID-19 diagnosing, and monitoring systems have been proposed to tackle the pandemic. In this article we have analyzed a wide range of IoTs technologies which can be used in diagnosing and monitoring the infected individuals and hotspot areas. Furthermore, we identify the challenges and also provide our vision about the future research on COVID-19.

Original languageEnglish
Pages (from-to)87168-87181
Number of pages14
JournalIEEE Access
Volume10
DOIs
Publication statusPublished - 2022
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Artificial intelligence (AI)
  • Coronavirus
  • COVID-19 pandemic
  • Internet of Things (IoTs)
  • Machine learning algorithms

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