Abstract
The Internet of Things is one of the fastest growing areas of research currently. A promising area for the introduction of this technology is housing and communal services, for which the reduction of accidents, increasing efficiency, in general, focus on transparency, personalization of services and payments for the end user are relevant. This article is devoted to the development and testing of predictive algorithm for predicting the need for repair of various units within the smart home, such as heating, ventilation and air conditioning. The basis for the algorithm is the association rules mining. The paper presents the results of experiments and the directions for further improvement of the algorithm.
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This study was financed through the Federal Target Program “Research and development on priority directions of scientific-technological complex of Russia for 2014–2020” (grant № RFMEF157917X0142).
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Kireev, V.S., Guseva, A.I., Bochkaryov, P.V., Kuznetsov, I.A., Filippov, S.A. (2019). Association Rules Mining for Predictive Analytics in IoT Cloud System. In: Samsonovich, A. (eds) Biologically Inspired Cognitive Architectures 2018. BICA 2018. Advances in Intelligent Systems and Computing, vol 848. Springer, Cham. https://doi.org/10.1007/978-3-319-99316-4_14
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DOI: https://doi.org/10.1007/978-3-319-99316-4_14
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