Methodology for Predicting Failures in a Smart Home based on Machine Learning Methods

Zhebka, V. та Skladannyi, Pavlo та Zhebka, S. та Shlianchak, S. та Bondarchuk, A. (2024) Methodology for Predicting Failures in a Smart Home based on Machine Learning Methods Cybersecurity Providing in Information and Telecommunication Systems 2024, 3654. с. 322-332. ISSN 1613-0073

Текст V_Zhebka_P_Skladannyi_S_Zhebka_S_Shlianchak_A_Bondarchuk_CPITS_3654_2024.pdf Download (780kB)

Анотація

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.

Тип елементу :	Стаття
Ключові слова:	Failures; machine learning methods; predicting; methodology; information technology; IoT; smart home
Типологія:	Статті у базах даних > Scopus
Підрозділи:	Факультет інформаційних технологій та математики > Кафедра інформаційної та кібернетичної безпеки ім. професора Володимира Бурячка
Користувач, що депонує:	Павло Миколайович Складанний
Дата внесення:	08 Квіт 2024 07:15
Останні зміни:	08 Квіт 2024 07:15
URI:	https://elibrary.kubg.edu.ua/id/eprint/48556

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