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Application of cognitive Internet of Medical Things for COVID-19 pandemic

BACKGROUND AND AIM: In the age of advanced digital technology, smart healthcare based on the Internet of Things (IoT) is gaining importance to deal with the current COVID-19 pandemic. In this paper, the novel application of cognitive radio (CR) based IoT specific for the medical domain referred to a...

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Detalles Bibliográficos
Autores principales: Swayamsiddha, Swati, Mohanty, Chandana
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Diabetes India. Published by Elsevier Ltd. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7287427/
https://www.ncbi.nlm.nih.gov/pubmed/32570016
http://dx.doi.org/10.1016/j.dsx.2020.06.014
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author Swayamsiddha, Swati
Mohanty, Chandana
author_facet Swayamsiddha, Swati
Mohanty, Chandana
author_sort Swayamsiddha, Swati
collection PubMed
description BACKGROUND AND AIM: In the age of advanced digital technology, smart healthcare based on the Internet of Things (IoT) is gaining importance to deal with the current COVID-19 pandemic. In this paper, the novel application of cognitive radio (CR) based IoT specific for the medical domain referred to as Cognitive Internet of Medical Things (CIoMT) is explored to tackle the global challenge. This concept of CIoT is best suited to this pandemic as every person is to be connected and monitored through a massive network that requires efficient spectrum management. METHODS: An extensive literature survey is conducted in the Google Scholar, Scopus, PubMed, Research Gate, and IEEE Xplore databases using the terms “COVID-19” and “Cognitive IoT” or “Corona virus” and “IoMT”. The latest data and inputs from official websites and reports are used for further investigation and analysis of the application areas. RESULTS: This review encompasses different novel applications of CIoMT for fighting the ongoing COVID-19 health crisis. The CR based dynamic spectrum allocation technique is the solution for accommodating a massive number of devices and a wide number of applications. The CIoMT platform enables real-time tracking, remote health monitoring, rapid diagnosis of the cases, contact tracking, clustering, screening, and surveillance thus, reducing the workload on the medical industry for prevention and control of the infection. The challenges and future research directions are also identified. CONCLUSIONS: CIoMT is a promising technology for rapid diagnosis, dynamic monitoring and tracking, better treatment and control without spreading the virus to others.
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spelling pubmed-72874272020-06-11 Application of cognitive Internet of Medical Things for COVID-19 pandemic Swayamsiddha, Swati Mohanty, Chandana Diabetes Metab Syndr Article BACKGROUND AND AIM: In the age of advanced digital technology, smart healthcare based on the Internet of Things (IoT) is gaining importance to deal with the current COVID-19 pandemic. In this paper, the novel application of cognitive radio (CR) based IoT specific for the medical domain referred to as Cognitive Internet of Medical Things (CIoMT) is explored to tackle the global challenge. This concept of CIoT is best suited to this pandemic as every person is to be connected and monitored through a massive network that requires efficient spectrum management. METHODS: An extensive literature survey is conducted in the Google Scholar, Scopus, PubMed, Research Gate, and IEEE Xplore databases using the terms “COVID-19” and “Cognitive IoT” or “Corona virus” and “IoMT”. The latest data and inputs from official websites and reports are used for further investigation and analysis of the application areas. RESULTS: This review encompasses different novel applications of CIoMT for fighting the ongoing COVID-19 health crisis. The CR based dynamic spectrum allocation technique is the solution for accommodating a massive number of devices and a wide number of applications. The CIoMT platform enables real-time tracking, remote health monitoring, rapid diagnosis of the cases, contact tracking, clustering, screening, and surveillance thus, reducing the workload on the medical industry for prevention and control of the infection. The challenges and future research directions are also identified. CONCLUSIONS: CIoMT is a promising technology for rapid diagnosis, dynamic monitoring and tracking, better treatment and control without spreading the virus to others. Diabetes India. Published by Elsevier Ltd. 2020 2020-06-11 /pmc/articles/PMC7287427/ /pubmed/32570016 http://dx.doi.org/10.1016/j.dsx.2020.06.014 Text en © 2020 Diabetes India. Published by Elsevier Ltd. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Article
Swayamsiddha, Swati
Mohanty, Chandana
Application of cognitive Internet of Medical Things for COVID-19 pandemic
title Application of cognitive Internet of Medical Things for COVID-19 pandemic
title_full Application of cognitive Internet of Medical Things for COVID-19 pandemic
title_fullStr Application of cognitive Internet of Medical Things for COVID-19 pandemic
title_full_unstemmed Application of cognitive Internet of Medical Things for COVID-19 pandemic
title_short Application of cognitive Internet of Medical Things for COVID-19 pandemic
title_sort application of cognitive internet of medical things for covid-19 pandemic
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7287427/
https://www.ncbi.nlm.nih.gov/pubmed/32570016
http://dx.doi.org/10.1016/j.dsx.2020.06.014
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