The aging of the world’s population and the growth in the number of people with chronic diseases have increased expenses with medical care. Thus, the use of technological solutions has been widely adopted in the medical field to improve the patients’ health. In this context, approaches based on Cloud Computing have been used to store and process the information generated in these solutions. However, using Cloud can create delays that are intolerable for medical applications. Thus, the Fog Computing paradigm emerged as an alternative to overcome this problem, bringing computation and storage closer to the data sources. However, managing medical data stored in Fog is still a challenge. Moreover, characteristics of availability, performance, interoperability, and privacy need to be considered in approaches that aim to explore this problem. So, this article shows a software architecture based on Fog Computing and designed to facilitate the management of medical records. This architecture uses Blockchain concepts to provide the necessary privacy features and to allow Fog Nodes to carry out the authorization process in a distributed way. Finally, this paper describes a case study that evaluates the performance, privacy, and interoperability requirements of the proposed architecture in a home-centered healthcare scenario.
There is a global concern with the escalating number of patients at hospitals caused mainly by population aging, chronic diseases, and recently by the COVID-19 outbreak. To smooth this challenge, IoT emerges as an encouraging paradigm because it provides the scalability required for this purpose, supporting continuous and reliable health monitoring on a global scale. Based on this context, an IoT-based healthcare platform to provide remote monitoring for patients in a critical situation was proposed in the authors' previous works. Therefore, this paper aims to extend the platform by integrating wearable and unobtrusive sensors to monitor patients with coronavirus disease. Furthermore, we report a real deployment of our approach in an intensive care unit for COVID-19 patients in Brazil.INDEX TERMS Healthcare, Internet of Things, COVID-19, remote monitoring, platform.
IoT devices deployed in Smart Cities usually have significant resource limitations. For this reason, offload tasks or data to other layers such as fog or cloud is regularly adopted to smooth out this issue. Although data offloading is a well-known aspect of fog computing, the specification of offloading policies is still an open issue due to the lack of clear guidelines. Therefore, we propose OffFog—an approach to guide the definition of data offloading policies in the context of fog computing. In order to evaluate OffFog, we extended the well-known simulator iFogSim and conducted an experimental study based on an urban surveillance system. The results demonstrated the benefits of implementing data offloading based on OffFog recommended policies. Furthermore, we identified the best configuration involving design decisions such as data compression, data criticality, and storage thresholds. The best configuration produced at least 76% improvement in network latency and 5% in the average execution time compared to the iFogSim default strategy. We believe these results represent a significant step towards establishing a systematic decision framework for data offloading policies in the context of fog computing.
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