INDUSTRIAL INTERNET OF THINGS FOR ELECTRONIC INDUSTRY ENTERPRISES
Authors:
1.
Scientific and production enterprise “Istok” n. a. A. I. Shokin
Fryazino, Moscow, Russian Federation
Fryazino, Moscow, Russian Federation
2.
Scientific and production enterprise “Istok” n. a. A. I. Shokin
Fryazino, Moscow, Russian Federation
Fryazino, Moscow, Russian Federation
3.
Scientific-Industrial Company “Radiotechnika”
(Technical Director)
Moscow, Russian Federation
Moscow, Russian Federation
Type:
Article
Pages:
from 209
to 217
Status:
Published
Received:
20.06.2022
Accepted:
20.06.2022
Published:
28.06.2022
Subject area:
UDK 004.89 Прикладные системы искусственного интеллекта. Интеллектуальные системы, обладающие знаниями
UDK 65.011.56 Автоматизация в целом
UDK 65.011.56 Автоматизация в целом
Language:
Russian
Keywords:
Internet of Things, Big Data, intelligent analysis of data, predictive analysis, electronic industry
Funding:
Avtory blagodarny Minpromtorgu Rossii za predostavlennuyu subsidiyu na vypolnenie rabot
Abstract (English):
The industrial Internet of Things platform is described. It is focused on solving the problems that are relevant for the management of the electronic industry. It has been shown that the use of modern tools based on intelligent analysis of Big Data makes it possible to provide managers with reliable operational information for management decisions.
The industrial Internet of Things platform is described. It is focused on solving the problems that are relevant for the management of the electronic industry. It has been shown that the use of modern tools based on intelligent analysis of Big Data makes it possible to provide managers with reliable operational information for management decisions.
Keywords:
Internet of Things, Big Data, intelligent analysis of data, predictive analysis, electronic industry
Internet of Things, Big Data, intelligent analysis of data, predictive analysis, electronic industry
1. Y. Lei, N. Li, L. Guo, N. Li, T. Yan, and J. Lin, “Machinery health prognostics: a systematic review from data acquisition to RUL prediction,” Mech. Syst. Signal Process, vol. 104, pp. 799-834, 2018.
2. O. V. Chikalo, V. R. Alexandrov, and I. A. Obukhov, “System for early detection of problematic telecommunication equipment,” 30th Intern. Crimean Conf. “Microwave and telecommunication technology” - CriMiCo’2020 (Sevastopol, September 6-12, 2020), pp. 128-129, 2020. (In Russ.).
3. A. V. Nazarov and A. I. Loskutov, Neural network algorithms for forecasting and optimizing systems, Saint Petersburg: Nauka i Tekhnika, 2003. (In Russ.).
