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dc.contributor.author Dautov R.
dc.contributor.author Distefano S.
dc.contributor.author Buyya R.
dc.date.accessioned 2020-01-15T22:07:38Z
dc.date.available 2020-01-15T22:07:38Z
dc.date.issued 2019
dc.identifier.uri https://dspace.kpfu.ru/xmlui/handle/net/156661
dc.description.abstract © 2019, The Author(s). The Internet of Things (IoT) facilitates creation of smart spaces by converting existing environments into sensor-rich data-centric cyber-physical systems with an increasing degree of automation, giving rise to Industry 4.0. When adopted in commercial/industrial contexts, this trend is revolutionising many aspects of our everyday life, including the way people access and receive healthcare services. As we move towards Healthcare Industry 4.0, the underlying IoT systems of Smart Healthcare spaces are growing in size and complexity, making it important to ensure that extreme amounts of collected data are properly processed to provide valuable insights and decisions according to requirements in place. This paper focuses on the Smart Healthcare domain and addresses the issue of data fusion in the context of IoT networks, consisting of edge devices, network and communications units, and Cloud platforms. We propose a distributed hierarchical data fusion architecture, in which different data sources are combined at each level of the IoT taxonomy to produce timely and accurate results. This way, mission-critical decisions, as demonstrated by the presented Smart Healthcare scenario, are taken with minimum time delay, as soon as necessary information is generated and collected. The proposed approach was implemented using the Complex Event Processing technology, which natively supports the hierarchical processing model and specifically focuses on handling streaming data ‘on the fly’—a key requirement for storage-limited IoT devices and time-critical application domains. Initial experiments demonstrate that the proposed approach enables fine-grained decision taking at different data fusion levels and, as a result, improves the overall performance and reaction time of public healthcare services, thus promoting the adoption of the IoT technologies in Healthcare Industry 4.0.
dc.subject Cloud computing
dc.subject Complex Event Processing
dc.subject Data fusion
dc.subject Distributed architecture
dc.subject Edge computing
dc.subject Industry 4.0
dc.subject Internet of Things
dc.subject Smart Healthcare
dc.title Hierarchical data fusion for Smart Healthcare
dc.type Article
dc.relation.ispartofseries-issue 1
dc.relation.ispartofseries-volume 6
dc.collection Публикации сотрудников КФУ
dc.source.id SCOPUS-2019-6-1-SID85062549653


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  • Публикации сотрудников КФУ Scopus [20180]
    Коллекция содержит публикации сотрудников Казанского федерального (до 2010 года Казанского государственного) университета, проиндексированные в БД Scopus, начиная с 1970г.

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