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An Enhanced IoT Based Tracing and Tracking Model for COVID -19 Cases

The COVID-19 pandemic has alarmed the world nations to impose strict curfews and emergencies to prevent the social transmission of the disease. In order to achieve this, effective Tracing and Tracking of the suspected COVID-19 cases need to be achieved. In view of the enormous number of cases being...

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Autor principal: Rajasekar, Sakthi Jaya Sundar
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Singapore 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7812980/
https://www.ncbi.nlm.nih.gov/pubmed/33490971
http://dx.doi.org/10.1007/s42979-020-00400-y
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author Rajasekar, Sakthi Jaya Sundar
author_facet Rajasekar, Sakthi Jaya Sundar
author_sort Rajasekar, Sakthi Jaya Sundar
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description The COVID-19 pandemic has alarmed the world nations to impose strict curfews and emergencies to prevent the social transmission of the disease. In order to achieve this, effective Tracing and Tracking of the suspected COVID-19 cases need to be achieved. In view of the enormous number of cases being recorded each day, this process couldn’t be performed effectively with simple manual tracing. Hence, we have proposed an Internet of Things (IoT) based automated Tracing and Tracking method for identification of the possible contacts with deployment of cost-effective RFID Tags and the mobile of the individuals which act as a reader. Thereby, tracing of persons who have crossed the subject would be possible even without the knowledge of the suspected cases. This would enable cent percent quarantine of possible primary and secondary contacts and monitoring of the same by the administrative agencies. This would augment the nations’ capability of managing the pandemic.
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spelling pubmed-78129802021-01-18 An Enhanced IoT Based Tracing and Tracking Model for COVID -19 Cases Rajasekar, Sakthi Jaya Sundar SN Comput Sci Original Research The COVID-19 pandemic has alarmed the world nations to impose strict curfews and emergencies to prevent the social transmission of the disease. In order to achieve this, effective Tracing and Tracking of the suspected COVID-19 cases need to be achieved. In view of the enormous number of cases being recorded each day, this process couldn’t be performed effectively with simple manual tracing. Hence, we have proposed an Internet of Things (IoT) based automated Tracing and Tracking method for identification of the possible contacts with deployment of cost-effective RFID Tags and the mobile of the individuals which act as a reader. Thereby, tracing of persons who have crossed the subject would be possible even without the knowledge of the suspected cases. This would enable cent percent quarantine of possible primary and secondary contacts and monitoring of the same by the administrative agencies. This would augment the nations’ capability of managing the pandemic. Springer Singapore 2021-01-18 2021 /pmc/articles/PMC7812980/ /pubmed/33490971 http://dx.doi.org/10.1007/s42979-020-00400-y Text en © Springer Nature Singapore Pte Ltd 2021 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Original Research
Rajasekar, Sakthi Jaya Sundar
An Enhanced IoT Based Tracing and Tracking Model for COVID -19 Cases
title An Enhanced IoT Based Tracing and Tracking Model for COVID -19 Cases
title_full An Enhanced IoT Based Tracing and Tracking Model for COVID -19 Cases
title_fullStr An Enhanced IoT Based Tracing and Tracking Model for COVID -19 Cases
title_full_unstemmed An Enhanced IoT Based Tracing and Tracking Model for COVID -19 Cases
title_short An Enhanced IoT Based Tracing and Tracking Model for COVID -19 Cases
title_sort enhanced iot based tracing and tracking model for covid -19 cases
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7812980/
https://www.ncbi.nlm.nih.gov/pubmed/33490971
http://dx.doi.org/10.1007/s42979-020-00400-y
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