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Federated Internet of Things and Cloud Computing Pervasive Patient Health Monitoring System

Open access
Abawajy, Jemal H., Hassan, Mohammad Mehedi·2017·IEEE Communications Magazine

Abstract

The exponentially growing healthcare costs coupled with the increasing interest of patients in receiving care in the comfort of their own homes have prompted a serious need to revolutionize healthcare systems. This has prompted active research in the development of solutions that enable healthcare providers to remotely monitor and evaluate the health of patients in the comfort of their residences. However, existing works lack flexibility, scalability, and energy efficiency. This article presents a pervasive patient health monitoring (PPHM) system infrastructure. PPHM is based on integrated cloud computing and Internet of Things technologies. In order to demonstrate the suitability of the proposed PPHM infrastructure, a case study for real-time monitoring of a patient suffering from congestive heart failure using ECG is presented. Experimental evaluation of the proposed PPHM infrastructure shows that PPHM is a flexible, scalable, and energy-efficient remote patient health monitoring system.

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Metadata

Authors
Abawajy, J. H., & Hassan, M. M.
Venue
IEEE Communications Magazine
Published
2017-01
Volume
55
Issue
1
Pages
48-53
ISSN
0163-6804 (ISSN-L)
OpenAlex
W2573554261
Cited by
277
References
0
FWCI
63.17
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Federated Internet of Things and Cloud Computing Pervasive Patient Health Monitoring System. https://app.cochat.ai/papers/10.1109/mcom.2017.1600374cm
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Abawajy, J. H., & Hassan, M. M. (2017). Federated Internet of Things and Cloud Computing Pervasive Patient Health Monitoring System. IEEE Communications Magazine. https://doi.org/10.1109/mcom.2017.1600374cm

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.