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Article

An Edge Computing Based Smart Healthcare Framework for Resource Management

by 1,†, 2,†, 3,*,†, 4,† and 5,†
1
Politehnica University of Bucharest, 060042 Bucharest, Romania
2
American University of the Middle East, Eqaila 250 St, Kuwait
3
Gnowit Inc., 7 Bayview Road, Ottawa, ON K1Y3B5, Canada
4
Jordan University of Science and Technology, Irbid 22110, Jordan
5
Liverpool John Moores University, Liverpool L3 3AF, UK
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Sensors 2018, 18(12), 4307; https://doi.org/10.3390/s18124307
Received: 9 October 2018 / Revised: 28 November 2018 / Accepted: 3 December 2018 / Published: 6 December 2018
(This article belongs to the Section Sensor Networks)
The revolution in information technologies, and the spread of the Internet of Things (IoT) and smart city industrial systems, have fostered widespread use of smart systems. As a complex, 24/7 service, healthcare requires efficient and reliable follow-up on daily operations, service and resources. Cloud and edge computing are essential for smart and efficient healthcare systems in smart cities. Emergency departments (ED) are real-time systems with complex dynamic behavior, and they require tailored techniques to model, simulate and optimize system resources and service flow. ED issues are mainly due to resource shortage and resource assignment efficiency. In this paper, we propose a resource preservation net (RPN) framework using Petri net, integrated with custom cloud and edge computing suitable for ED systems. The proposed framework is designed to model non-consumable resources and is theoretically described and validated. RPN is applicable to a real-life scenario where key performance indicators such as patient length of stay (LoS), resource utilization rate and average patient waiting time are modeled and optimized. As the system must be reliable, efficient and secure, the use of cloud and edge computing is critical. The proposed framework is simulated, which highlights significant improvements in LoS, resource utilization and patient waiting time. View Full-Text
Keywords: edge computing; cloud computing; smart city; smart healthcare management; emergency department; Petri net workflow; workflow soundness edge computing; cloud computing; smart city; smart healthcare management; emergency department; Petri net workflow; workflow soundness
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MDPI and ACS Style

Oueida, S.; Kotb, Y.; Aloqaily, M.; Jararweh, Y.; Baker, T. An Edge Computing Based Smart Healthcare Framework for Resource Management. Sensors 2018, 18, 4307. https://doi.org/10.3390/s18124307

AMA Style

Oueida S, Kotb Y, Aloqaily M, Jararweh Y, Baker T. An Edge Computing Based Smart Healthcare Framework for Resource Management. Sensors. 2018; 18(12):4307. https://doi.org/10.3390/s18124307

Chicago/Turabian Style

Oueida, Soraia, Yehia Kotb, Moayad Aloqaily, Yaser Jararweh, and Thar Baker. 2018. "An Edge Computing Based Smart Healthcare Framework for Resource Management" Sensors 18, no. 12: 4307. https://doi.org/10.3390/s18124307

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