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  5. Novel MEC based Approaches for Smart Hospitals to Combat COVID-19 Pandemic
 
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Novel MEC based Approaches for Smart Hospitals to Combat COVID-19 Pandemic

Author(s)
Ranaweera, Pasika  
Liyanage, Madhusanka  
Jurcut, Anca Delia  
Uri
http://hdl.handle.net/10197/11643
Date Issued
2021-03-01
Date Available
2020-10-29T16:06:04Z
Abstract
COVID-19 or Coronavirus has thrilled the entire world population with uncertainty over their survival and well-being. The impact this pathogen has caused over the globe has been profound due to its unique transmission features; that urges for contact-less strategies to interact and treat the infected. The impending 5G mobile technology is immersing the applications that enable the provisioning of medical and healthcare services in a contact-less manner. The edge computing paradigms offer a de-centralized and versatile networking infrastructure capable of adhering to the novel demands of 5G. In this article, we are considering Multi-Access Edge Computing (MEC) flavour of the edge paradigms for realizing the contact-less approaches that assist the mediation of COVID-19 and the future of healthcare. In order to formulate this ideology, we propose three use cases and discuss their implementation in the MEC context. Further, the requirements for launching these services are provided. Additionally, we validate our proposed approaches through simulations.
Sponsorship
European Commission
Other Sponsorship
Academy of Finland
Type of Material
Journal Article
Publisher
IEEE
Journal
IEEE Consumer Electronics Magazine
Volume
10
Issue
2
Start Page
80
End Page
91
Copyright (Published Version)
2020 IEEE
Subjects

COVID-19

Robots

Surgery

Monitoring

Biomedical imaging

5G mobile communicati...

Coronavirus

DOI
10.1109/MCE.2020.3031261
Language
English
Status of Item
Peer reviewed
ISSN
2162-2248
This item is made available under a Creative Commons License
https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
File(s)
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IEEE_CE_Magazine___MEC_for_COVID19_2020_Final.pdf

Size

2.03 MB

Format

Adobe PDF

Checksum (MD5)

66f69f98bd38935a018a9ef6be9b9005

Owning collection
Computer Science Research Collection

Item descriptive metadata is released under a CC-0 (public domain) license: https://creativecommons.org/public-domain/cc0/.
All other content is subject to copyright.

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