Application of the Methodology and Tools of Bayesian Intelligent Technologies and Intelligent IIoT in the Management of Cyber-Physical Systems under Conditions of Uncertainty

Abstract

AbstractThe effectiveness of the functioning of cyber-physical systems is based primarily on the use of powerful methods of obtaining and processing information. The complexity of the structures and properties of cybernetic systems, as well as the conditions of their functioning, determines special requirements for the methods of measurements and calculations performed in such systems. As a rule, the uncertainty of CPS models, as well as the uncertainty of the influence of external environment factors and their interrelations with the properties of systems, primarily determine the requirements for the intellectualization of measurements and computational information processing. This article offers methods and tools of Bayesian intelligent measurements (BIM) to ensure the effectiveness of managing cyber-physical systems under conditions of uncertainty. The concept and methodology of creating an intelligent industrial Internet of Things (IIoT) is proposed, the distinctive feature of which is the intellectualization of measurement methods and predictive data processing. For this purpose, the IIoT includes an intelligent DATALAKE, which is built on the basis of a Bayesian intelligent measurement system that implements not only the functions of measurement and data integration, but also support for management decision-making. Examples of real cyber-physical systems with control based on Bayesian intelligent measurement tools are given. The prospects of using the proposed solutions based on BIM in various modern technologies based on the principles of BIG DATA, DATA SCIENCE, neural networks, IIoT, DATA MINING and others are considered.KeywordsArtificial intelligenceMeasurement theoryUncertaintyRegularizing bayesian approachCyberphysical systems