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Bei der Datenerhebung und -verarbeitung durch AAL-Infrastruktur im Pflegesektor sind rechtliche Rahmenbedingungen zu prüfen, die die Nutzung der Messdaten juristisch zulässig machen. Hierzu wurden die in der praxisnahen Pflegeliteratur dargestellten Rechtsnormen zusammengefasst und kategorisiert. Somit ließ sich ermitteln, welche Daten als schützenswert zu definieren und mit welchen Sicherungsmaßnahmen zu versehen sind. Auf dieser Basis kann ein Ansatz präsentiert werden, der eine rechtlich unbedenkliche Absicherung aller technischen Elemente bei der Implementierung einer AAL-Infrastruktur in der Pflege ermöglicht.
In this article we argue that smart items and cloud computing can be powerful enablers of servitization as business trend. This is exemplified by an application scenario in healthcare that was developed in the context of the OpSIT-Project in Germany. We present a three-level architecture for a smart healthcare infrastructure. The approach is based on a service-oriented architecture and extends established architectural approaches developed previously at our group. More specifically, it integrates a role model, a layered cloud computing architecture, as well as a fog-computing-informed paradigm in order to provide a viable architecture for healthcare and elderly-care applications. The integration of established paradigms is beneficial with respect to providing adequate quality of service and governance (e.g., data privacy and compliance). It has been verified by expert interviews with healthcare specialists and IT professionals. To further demonstrate the validity of this architectural model, we provide an example use-case as a template for any kind of smart sensor-based healthcare infrastructure.
Use of cloud computing in healthcare is a promising trend, particularly in utilization of smart items. Access, affordability and quality to proper healthcare is a great challenge in world society. With the utilization of smart sensors, there are possibilities to improve the quality of healthcare services whenever needed. Hence, such smart items services lead to economic advantages for the whole healthcare system. Keeping in mind these opportunities as well as challenges such as security or legal issues, it is important to bring healthcare and IT together. As a result, healthcare business processes need to be modeled in order to provide IT solutions tailored for practice-oriented applications. In this paper, we present a three-level architecture for a smart healthcare infrastructure. Our approach is based on recent literature work and results from conducted expert interviews with healthcare specialists and IT professionals. To demonstrate the applicability of this architecture model, we provide an example use-case as a template for any kind of smart sensor-based healthcare infrastructure.
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.