Персона: Киреев, Василий Сергеевич
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Association Rules Mining for Predictive Analytics in IoT Cloud System
© 2019, Springer Nature Switzerland AG. 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.
Monitoring System for the Housing and Utility Services Based on the Digital Technologies IIoT, Big Data, Data Mining, Edge and Cloud Computing
© 2019, Springer Nature Switzerland AG.This article discusses the development of an information system for monitoring, remote control and support of technical conditions in a housing infrastructure engineering system. The monitoring system is based on the concept of edge computing - cloud computing and is designed to collect and analyze Big data procured via the Industrial Internet of Things (IIoT). Author acknowledges support from the MEPhI Academic Excellence Project (Contract No. 02.a03.21.0005).