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QoS-Aware Smart Phone-Based User Tracking Application to Prevent Outbreak of COVID-19 in Saudi Arabia
Diverse variants of COVID-19 are repeatedly making everyday living unstable. In reality, the conclusive retort of this highly contagious virus still is in incognito mode. The health experts' primary guideline on the possible prevention of this disease outbreak, including a list of restrictions...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9002939/ https://www.ncbi.nlm.nih.gov/pubmed/35422855 http://dx.doi.org/10.1155/2022/2273910 |
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author | Mashat, Arwa Alabdali, Aliaa M. |
author_facet | Mashat, Arwa Alabdali, Aliaa M. |
author_sort | Mashat, Arwa |
collection | PubMed |
description | Diverse variants of COVID-19 are repeatedly making everyday living unstable. In reality, the conclusive retort of this highly contagious virus still is in incognito mode. The health experts' primary guideline on the possible prevention of this disease outbreak, including a list of restrictions and confinements, is insufficient in case of any public congregation. As a result, the demand for precise and upgraded real-time COVID-19 tracking and prevention-based applications increases. However, most of the existing android-based applications face a lack of data security and reliability that cannot satisfy the additional quality of service (QoS) requirements. This paper proposes an easy-to-operate android-based multifunctional application to track individuals' health situations, allow uploading scanning report by the authorized organization like universities, mosques, school, and hospitals and helps the users to maintain guidelines via manageable steps. This article offers a three-layered QoS aware service-oriented task scheduling model upon multitasking android-based frontend focusing the cognitive-based AI applications in healthcare with a continual learning paradigm. Designed model is competent to optimize heterogeneous service scheduling and can minimize data delivery time, as well as the resource cost. |
format | Online Article Text |
id | pubmed-9002939 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-90029392022-04-13 QoS-Aware Smart Phone-Based User Tracking Application to Prevent Outbreak of COVID-19 in Saudi Arabia Mashat, Arwa Alabdali, Aliaa M. Comput Intell Neurosci Research Article Diverse variants of COVID-19 are repeatedly making everyday living unstable. In reality, the conclusive retort of this highly contagious virus still is in incognito mode. The health experts' primary guideline on the possible prevention of this disease outbreak, including a list of restrictions and confinements, is insufficient in case of any public congregation. As a result, the demand for precise and upgraded real-time COVID-19 tracking and prevention-based applications increases. However, most of the existing android-based applications face a lack of data security and reliability that cannot satisfy the additional quality of service (QoS) requirements. This paper proposes an easy-to-operate android-based multifunctional application to track individuals' health situations, allow uploading scanning report by the authorized organization like universities, mosques, school, and hospitals and helps the users to maintain guidelines via manageable steps. This article offers a three-layered QoS aware service-oriented task scheduling model upon multitasking android-based frontend focusing the cognitive-based AI applications in healthcare with a continual learning paradigm. Designed model is competent to optimize heterogeneous service scheduling and can minimize data delivery time, as well as the resource cost. Hindawi 2022-04-11 /pmc/articles/PMC9002939/ /pubmed/35422855 http://dx.doi.org/10.1155/2022/2273910 Text en Copyright © 2022 Arwa Mashat and Aliaa M. Alabdali. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Mashat, Arwa Alabdali, Aliaa M. QoS-Aware Smart Phone-Based User Tracking Application to Prevent Outbreak of COVID-19 in Saudi Arabia |
title | QoS-Aware Smart Phone-Based User Tracking Application to Prevent Outbreak of COVID-19 in Saudi Arabia |
title_full | QoS-Aware Smart Phone-Based User Tracking Application to Prevent Outbreak of COVID-19 in Saudi Arabia |
title_fullStr | QoS-Aware Smart Phone-Based User Tracking Application to Prevent Outbreak of COVID-19 in Saudi Arabia |
title_full_unstemmed | QoS-Aware Smart Phone-Based User Tracking Application to Prevent Outbreak of COVID-19 in Saudi Arabia |
title_short | QoS-Aware Smart Phone-Based User Tracking Application to Prevent Outbreak of COVID-19 in Saudi Arabia |
title_sort | qos-aware smart phone-based user tracking application to prevent outbreak of covid-19 in saudi arabia |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9002939/ https://www.ncbi.nlm.nih.gov/pubmed/35422855 http://dx.doi.org/10.1155/2022/2273910 |
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