Zhai, Y., Xu, X., Chen, B. et al. (7 more authors) (2021) 5G-network-enabled smart ambulance : architecture, application, and evaluation. IEEE Network, 35 (1). pp. 190-196. ISSN 0890-8044
Abstract
As the fifth generation (5G) network comes to the fore, the realization of 5G-enabled service has attracted much attention from both healthcare academics and practitioners. In particular, 5G-enabled emergency ambulance service allows to connect a patient and an ambulance crew at an accident scene or in transit with the awaiting emergency department team at the destination hospital seamlessly so as to improve the rescue rate of patients. However, the application of the 5G network in ambulance service currently lacks a reliable solution and simulation testing of performance in the existing literature. To achieve this end, the primary aim of this study is to propose a 5G-enabled smart ambulance service and then test the quality of service of the proposed solution in experimental settings. We also consider emergency scenarios to investigate the task completion and accuracy of 5G-enabled smart ambulance, and to verify the superiority of our proposed solution. Our study explores the value of a 5G-en-abled smart ambulance and provides practical insights for 5G network construction, business development, and network optimization of smart ambulance service.
Metadata
Item Type: | Article |
---|---|
Authors/Creators: |
|
Copyright, Publisher and Additional Information: | © 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. Reproduced in accordance with the publisher's self-archiving policy. |
Dates: |
|
Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Social Sciences (Sheffield) > Management School (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 07 Apr 2021 06:43 |
Last Modified: | 16 Feb 2022 01:38 |
Status: | Published |
Publisher: | Institute of Electrical and Electronics Engineers (IEEE) |
Refereed: | Yes |
Identification Number: | 10.1109/mnet.011.2000014 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:172834 |