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Blockchain and ANFIS empowered IoMT application for privacy preserved contact tracing in COVID-19 pandemic
Life-threatening novel severe acute respiratory syndrome coronavirus (SARS-CoV-2), also known as COVID-19, has engulfed the world and caused health and economic challenges. To control the spread of COVID-19, a mechanism is required to enforce physical distancing between people. This paper proposes a...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer London
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8295644/ https://www.ncbi.nlm.nih.gov/pubmed/34312582 http://dx.doi.org/10.1007/s00779-021-01596-3 |
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author | Aslam, Bakhtawar Javed, Abdul Rehman Chakraborty, Chinmay Nebhen, Jamel Raqib, Saira Rizwan, Muhammad |
author_facet | Aslam, Bakhtawar Javed, Abdul Rehman Chakraborty, Chinmay Nebhen, Jamel Raqib, Saira Rizwan, Muhammad |
author_sort | Aslam, Bakhtawar |
collection | PubMed |
description | Life-threatening novel severe acute respiratory syndrome coronavirus (SARS-CoV-2), also known as COVID-19, has engulfed the world and caused health and economic challenges. To control the spread of COVID-19, a mechanism is required to enforce physical distancing between people. This paper proposes a Blockchain-based framework that preserves patients’ anonymity while tracing their contacts with the help of Bluetooth-enabled smartphones. We use a smartphone application to interact with the proposed blockchain framework for contact tracing of the general public using Bluetooth and to store the obtained data over the cloud, which is accessible to health departments and government agencies to perform necessary and timely actions (e.g., like quarantine the infected people moving around). Thus, the proposed framework helps people perform their regular business and day-to-day activities with a controlled mechanism that keeps them safe from infected and exposed people. The smartphone application is capable enough to check their COVID status after analyzing the symptoms quickly and observes (based on given symptoms) either this person is infected or not. As a result, the proposed Adaptive Neuro-Fuzzy Interference System (ANFIS) system predicts the COVID status, and K-Nearest Neighbor (KNN) enhances the accuracy rate to 95.9% compared to state-of-the-art results. |
format | Online Article Text |
id | pubmed-8295644 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer London |
record_format | MEDLINE/PubMed |
spelling | pubmed-82956442021-07-22 Blockchain and ANFIS empowered IoMT application for privacy preserved contact tracing in COVID-19 pandemic Aslam, Bakhtawar Javed, Abdul Rehman Chakraborty, Chinmay Nebhen, Jamel Raqib, Saira Rizwan, Muhammad Pers Ubiquitous Comput Original Paper Life-threatening novel severe acute respiratory syndrome coronavirus (SARS-CoV-2), also known as COVID-19, has engulfed the world and caused health and economic challenges. To control the spread of COVID-19, a mechanism is required to enforce physical distancing between people. This paper proposes a Blockchain-based framework that preserves patients’ anonymity while tracing their contacts with the help of Bluetooth-enabled smartphones. We use a smartphone application to interact with the proposed blockchain framework for contact tracing of the general public using Bluetooth and to store the obtained data over the cloud, which is accessible to health departments and government agencies to perform necessary and timely actions (e.g., like quarantine the infected people moving around). Thus, the proposed framework helps people perform their regular business and day-to-day activities with a controlled mechanism that keeps them safe from infected and exposed people. The smartphone application is capable enough to check their COVID status after analyzing the symptoms quickly and observes (based on given symptoms) either this person is infected or not. As a result, the proposed Adaptive Neuro-Fuzzy Interference System (ANFIS) system predicts the COVID status, and K-Nearest Neighbor (KNN) enhances the accuracy rate to 95.9% compared to state-of-the-art results. Springer London 2021-07-22 /pmc/articles/PMC8295644/ /pubmed/34312582 http://dx.doi.org/10.1007/s00779-021-01596-3 Text en © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 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 Paper Aslam, Bakhtawar Javed, Abdul Rehman Chakraborty, Chinmay Nebhen, Jamel Raqib, Saira Rizwan, Muhammad Blockchain and ANFIS empowered IoMT application for privacy preserved contact tracing in COVID-19 pandemic |
title | Blockchain and ANFIS empowered IoMT application for privacy preserved contact tracing in COVID-19 pandemic |
title_full | Blockchain and ANFIS empowered IoMT application for privacy preserved contact tracing in COVID-19 pandemic |
title_fullStr | Blockchain and ANFIS empowered IoMT application for privacy preserved contact tracing in COVID-19 pandemic |
title_full_unstemmed | Blockchain and ANFIS empowered IoMT application for privacy preserved contact tracing in COVID-19 pandemic |
title_short | Blockchain and ANFIS empowered IoMT application for privacy preserved contact tracing in COVID-19 pandemic |
title_sort | blockchain and anfis empowered iomt application for privacy preserved contact tracing in covid-19 pandemic |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8295644/ https://www.ncbi.nlm.nih.gov/pubmed/34312582 http://dx.doi.org/10.1007/s00779-021-01596-3 |
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