Big Data for Energy Management and Energy-Efficient Buildings

European buildings are producing a massive amount of data from a wide spectrum of energy-related sources, such as smart meters’ data, sensors and other Internet of things devices, creating new research challenges. In this context, the aim of this paper is to present a high-level data-driven architec...

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Vydáno v:Energies (Basel) Ročník 13; číslo 7; s. 1555
Hlavní autor: Marinakis, Vangelis
Médium: Journal Article
Jazyk:angličtina
Vydáno: Basel MDPI AG 2020
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ISSN:1996-1073, 1996-1073
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Shrnutí:European buildings are producing a massive amount of data from a wide spectrum of energy-related sources, such as smart meters’ data, sensors and other Internet of things devices, creating new research challenges. In this context, the aim of this paper is to present a high-level data-driven architecture for buildings data exchange, management and real-time processing. This multi-disciplinary big data environment enables the integration of cross-domain data, combined with emerging artificial intelligence algorithms and distributed ledgers technology. Semantically enhanced, interlinked and multilingual repositories of heterogeneous types of data are coupled with a set of visualization, querying and exploration tools, suitable application programming interfaces (APIs) for data exchange, as well as a suite of configurable and ready-to-use analytical components that implement a series of advanced machine learning and deep learning algorithms. The results from the pilot application of the proposed framework are presented and discussed. The data-driven architecture enables reliable and effective policymaking, as well as supports the creation and exploitation of innovative energy efficiency services through the utilization of a wide variety of data, for the effective operation of buildings.
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ISSN:1996-1073
1996-1073
DOI:10.3390/en13071555