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Fog computing architectures for healthcare: Wireless performance and semantic opportunities

  • Purpose – The purpose of this study is to analyze how embedding of self-powered wireless sensors into cloud computing further enables such a system to become a sustainable part of work environment. Design/methodology/approach – This is exemplified by an application scenario in healthcare that was developed in the context of the OpSIT project in Germany. A clearly outlined three-layer architecture, in the sense of Internet of Things, is presented. It provides the basis for integrating a broad range of sensors into smart healthcare infrastructure. More specifically, by making use of short-range communication sensors (sensing layer), gateways which implement data transmission and low-level computation (fog layer) and cloud computing for processing the data (application layer). Findings – A technical in-depth analysis of the first two layers of the infrastructure is given to provereliability and to determine the communication quality and availability in real-world scenarios. Furthermore, two example use-cases that directly apply toPurpose – The purpose of this study is to analyze how embedding of self-powered wireless sensors into cloud computing further enables such a system to become a sustainable part of work environment. Design/methodology/approach – This is exemplified by an application scenario in healthcare that was developed in the context of the OpSIT project in Germany. A clearly outlined three-layer architecture, in the sense of Internet of Things, is presented. It provides the basis for integrating a broad range of sensors into smart healthcare infrastructure. More specifically, by making use of short-range communication sensors (sensing layer), gateways which implement data transmission and low-level computation (fog layer) and cloud computing for processing the data (application layer). Findings – A technical in-depth analysis of the first two layers of the infrastructure is given to provereliability and to determine the communication quality and availability in real-world scenarios. Furthermore, two example use-cases that directly apply to a healthcare environment are examined,concluding with the feasibility of the presented approach. Practical implications – Finally, the next research steps, oriented towards the semantic tagging and classification of data received from sensors, and the usage of advanced artificial intelligence-based algorithms on this information to produce useful knowledge, are described together with the derived social benefits. Originality/value – The work presents an innovative, extensible and scalable system, proven to be useful in healthcare environments.show moreshow less
Metadaten
Author:Ph.D. Lisardo Prieto-González, Corvin Jaedicke, Johannes Schubert, Prof. Dr. rer. nat Vladimir Stantchev
Parent Title (English):Journal of Information, Communication and Ethics in Society
Publisher:Emerald
Place of publication:Bingley
Document Type:Article
Language:English
Date of Publication (online):2018/02/13
Date of first Publication:2016/08/17
Publishing Institution:SRH Berlin University of Applied Sciences
Release Date:2018/02/13
Tag:Cloud computing; Healthcare; Ontologies
Volume:14
Issue:4
First Page:334
Last Page:349
Note:
Volltext aus urheberrechtlichen Gründen nicht verfügbar.
Full text due to copyright no available.
Link author profile:https://www.srh-berlin.de/hochschule/hochschulteam/stantchev-vladimir/
Peer-reviewed:Keine Angabe - No details
JEL-Classification:I Health, Education, and Welfare
Licence (German):License LogoCreative Commons - Namensnennung-Nicht kommerziell-Keine Bearbeitung
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