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Towards a User-Level Self-management of COVID-19 Using Mobile Devices Supported by Artificial Intelligence, 5G and the Cloud
10th International Conference on Health Information Science, HIS 2021 ; 13079 LNCS:33-43, 2021.
Article in English | Scopus | ID: covidwho-1549379
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 continues to increase around the globe, with reportedly 60.5 million confirmed cases as of November 2020. Evidently, innovation has an imperative function to empower 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. © 2021, Springer Nature Switzerland AG.

Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: 10th International Conference on Health Information Science, HIS 2021 Year: 2021 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: 10th International Conference on Health Information Science, HIS 2021 Year: 2021 Document Type: Article