Towards a user-level self-management of COVID-19 using mobile devices supported by Artificial Intelligence, 5G and the Cloud

Ahmed, Sajjad and Shrestha, Anup ORCID: https://orcid.org/0000-0002-2952-0072 and Yong, Jianming (2021) Towards a user-level self-management of COVID-19 using mobile devices supported by Artificial Intelligence, 5G and the Cloud. In: 10th International Conference on Health Information Science (HIS 2021), 25 Oct - 28 Oct 2021, Melbourne, Australia.


Abstract

The fatal outbreak of COVID-19 has placed its fear around the globe since it was first reported in Wuhan, China, in November 2019. COVID-19 has placed all countries and governments across the world in an unstable position. Most countries underwent partial or full lock down due to the dearth of resources to fight the COVID-19 outbreak, primarily due to the challenges of overloaded healthcare systems. The tally of confirmed COVID-19 cases via laboratory con-tinues to increase around the globe, with reportedly 60.5 million confirmed cases as of November 2020. Evidently, innovation has an imperative function to em-power the omnipresent health technologies in order to counter the impacts of COVID-19 in a post-pandemic period. More specifically, the Fifth Generation (5G) cellular network and 5G-empowered e-health and Artificial Intelligence (AI) based arrangements are of on the spotlight. This research explores the use of AI and 5G technologies to help alleviate the effects of COVID-19 spread. The novel approach is based on the premises that the COVID-19 vaccine may take years to rollout effectively, whereas the AI and 5G technologies offer effective solutions to reduce the Covid-19 spread within weeks. Currently, the approaches such as contact tracing and virus testing are not secure and reliable; and the cost of testing is high for end users. The proposed solution offers a self-diagnostic mechanism without any security risk of the users’ data with very low cost using cloud-based data analytics using mobile handsets.


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Item Type: Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)
Refereed: Yes
Item Status: Live Archive
Faculty/School / Institute/Centre: Current - Faculty of Business, Education, Law and Arts - School of Business (18 Jan 2021 -)
Faculty/School / Institute/Centre: Current - Faculty of Business, Education, Law and Arts - School of Business (18 Jan 2021 -)
Date Deposited: 13 Dec 2021 01:29
Last Modified: 11 Mar 2022 03:33
Uncontrolled Keywords: COVID-19, pandemic, AI, 5G, e-Health
Fields of Research (2008): 08 Information and Computing Sciences > 0806 Information Systems > 080699 Information Systems not elsewhere classified
Fields of Research (2020): 46 INFORMATION AND COMPUTING SCIENCES > 4601 Applied computing > 460102 Applications in health
Identification Number or DOI: https://doi.org/10.1007/978-3-030-90885-0
URI: http://eprints.usq.edu.au/id/eprint/44497

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