The effectiveness of the functioning of cyberphysical 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, determine special requirements for measurement methods and computing, performed in such systems. As a rule, the uncertainty of CPS models, as well as the uncertainty of the influence of environmental factors and their interrelations with the properties of systems, primarily define the requirements for the intellectualization of measurements and computational processing of information. In this article, methods and tools of Bayesian intelligent measurements (BII) are proposed to ensure the effectiveness of management of cyberphysical 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 data preprocessing. For this purpose, IIoT includes an intelligent DATALAKE, which is built on the basis of a Bayesian intelligent measurement systems that implements not only measurement and data integration functions, but also management decision support. Examples of real cyberphysical systems with control based on Bayesian intelligent measuring instruments are given. The prospects of using the proposed solutions based on BII in various modern technologies based on the principles of BIG DATA, DATA SCIENCE, neural networks, IIoT, DATA MINING and others are considered.
Mathematical Modeling of Changes During Time of Metrological Characteristics of Intelligent Measurement Systems