@article{PrietoGonzalezJaedickeSchubertetal.2016, author = {Prieto-Gonz{\´a}lez, Lisardo and Jaedicke, Corvin and Schubert, Johannes and Stantchev, Vladimir}, title = {Fog computing architectures for healthcare: Wireless performance and semantic opportunities}, series = {Journal of Information, Communication and Ethics in Society}, volume = {14}, journal = {Journal of Information, Communication and Ethics in Society}, number = {4}, publisher = {Emerald}, address = {Bingley}, pages = {334 -- 349}, year = {2016}, abstract = {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 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.}, language = {en} }