Big Data Analysis in IIoT Systems Using the Federated Machine Learning Method
- Resource Type
- Conference
- Authors
- Klymash, Mykhailo; Hordiichuk-Bublivska, Olena; Kyryk, Marian; Fabri, Liudvih; Kopets, Halyna
- Source
- 2022 IEEE 16th International Conference on Advanced Trends in Radioelectronics, Telecommunications and Computer Engineering (TCSET) Advanced Trends in Radioelectronics, Telecommunications and Computer Engineering (TCSET), 2022 IEEE 16th International Conference on. :248-252 Feb, 2022
- Subject
- Bioengineering
Components, Circuits, Devices and Systems
Computing and Processing
Fields, Waves and Electromagnetics
Signal Processing and Analysis
Machine learning algorithms
Software algorithms
Machine learning
Big Data
Prediction algorithms
Software
Telecommunications
Industrial Internet of Things
Federated Machine Learning
Recommender Systems
Singular Value Decomposition
- Language
The problem of effective Big Data processing in the Industrial Internet of Things was investigated in the work. The method of Federated Machine Learning as a tool for the analysis of large volumes of information in IIoT was described. The algorithm of Singular Value Decomposition was analyzed, which effectively analyzes the user data and the possibility of its modification. The increase of computational reliability using the FedSVD algorithm was investigated. The software modeling which confirms the efficiency of the proposed method has been carried out.