Collaborative data analytics for smart buildings: opportunities and models

Sanja Lazarova-Molnar*, Nader Mohamed

*Kontaktforfatter for dette arbejde

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Resumé

Smart buildings equipped with state-of-the-art sensors and meters are becoming more common. Large quantities of data are being collected by these devices. For a single building to benefit from its own collected data, it will need to wait for a long time to collect sufficient data to build accurate models to help improve the smart buildings systems. Therefore, multiple buildings need to cooperate to amplify the benefits from the collected data and speed up the model building processes. Apparently, this is not so trivial and there are associated challenges. In this paper, we study the importance of collaborative data analytics for smart buildings, its benefits, as well as presently possible models of carrying it out. Furthermore, we present a framework for collaborative fault detection and diagnosis as a case of collaborative data analytics for smart buildings. We also provide a preliminary analysis of the energy efficiency benefit of such collaborative framework for smart buildings. The result shows that significant energy savings can be achieved for smart buildings using collaborative data analytics.
OriginalsprogEngelsk
TidsskriftCluster Computing: The Journal of Networks, Software Tools and Applications
Vol/bind22
Udgave nummerSupplement. 1
Sider (fra-til)1065-1077
ISSN1386-7857
DOI
StatusUdgivet - 16. jan. 2019

Fingeraftryk

Intelligent buildings
Fault detection
Failure analysis
Energy efficiency
Energy conservation
Sensors

Citer dette

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Collaborative data analytics for smart buildings: opportunities and models. / Lazarova-Molnar, Sanja; Mohamed, Nader.

I: Cluster Computing: The Journal of Networks, Software Tools and Applications, Bind 22, Nr. Supplement. 1, 16.01.2019, s. 1065-1077.

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

TY - JOUR

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AU - Mohamed, Nader

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KW - Energy efficiency

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