Methodology for Predicting Failures in a Smart Home based on Machine Learning Methods - volodymyr-sokolov/publications GitHub Wiki
Conference Paper
Viktoriia Zhebka , Pavlo Skladannyi , Serhii Zhebka , Svitlana Shlianchak , Andrii Bondarchuk
Abstract
The article presents a platform for predicting failures in a smart home. A detailed algorithm of the predicting platform has been described. An algorithm for integrating the fault prediction platform into the smart home system has been developed. An algorithm for the functioning of a smart home with a failure prediction program based on machine learning has been presented. The software has been developed using the JHipster1 generator and the Java programming language. The use of machine learning methods in a smart home system expands its ability to analyze large amounts of data and identify patterns that may precede failures. This allows the system to predict possible problems and respond to them in advance. The use of preventive measures allows the system to automatically take measures to avoid failures, such as automatically adjusting the operation of devices or performing backups based on predictions.
Keywords
Failures; information technology; IoT; machine learning methods; methodology; predicting; smart home
SciVal Topics
Neural Network; Wireless Sensor Network; Quality of Service
Publisher
2024 Cybersecurity Providing in Information and Telecommunication Systems (CPITS)
28 February 2024 Kyiv, Ukraine
First Online: 20 March 2024
Indices
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ISSN: 1613-0073
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EID: 2-s2.0-85189144715
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DBLP: conf/cpits/ZhebkaSZSB24
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KUBG: 48556
Cite
APA
Zhebka, V., Skladannyi, P., Zhebka, S., Shlianchak, S., & Bondarchuk, A. (2024). Methodology for Predicting Failures in a Smart Home based on Machine Learning Methods. In Cybersecurity Providing in Information and Telecommunication Systems (Vol. 3654, pp. 322-332).
IEEE
V. Zhebka, P. Skladannyi, S. Zhebka, S. Shlianchak, and A. Bondarchuk, “Methodology for Predicting Failures in a Smart Home based on Machine Learning Methods,” Cybersecurity Providing in Information and Telecommunication Systems, vol. 3654, pp. 322-332, 2024.
CEUR-WS
V. Zhebka, et al., Methodology for Predicting Failures in a Smart Home based on Machine Learning Methods, in: Workshop on Cybersecurity Providing in Information and Telecommunication Systems, vol. 3654 (2024) 322-332.