150 / 2023-09-26 13:49:58

Bayesian Intelligent Measurements: Artificial Intelligence Methodology in Modern Measurement Theory

Neural networks,Bayesian Intelligent Measurement Networks,Regularizing Bayesian Approach,Bayesian convolution,Measurement Theory,Artificial Intelligence

In the context of the Fourth International Conference on Sensing, Measurement & Data Analytics in the era of Artificial Intelligence, specifically within the section dedicated to "Measurement Theory and Methodology," this article addresses a fundamental aspect of Industry 4.0 — the advancement of intelligent sensor systems. Emphasizing the critical nature of real measurement processes in complex systems operating under significant uncertainty, the article explores the challenges posed by inherent incompleteness, inaccuracy, and vagueness of information concerning measurement objects and their operational environments.



The article presents an innovative approach to intelligent measurement systems, harnessing Bayesian intelligent technologies (BIT) and their associated tools. It delves into the core modules of such networks, encompassing integrated sensor arrays and intelligent systems designed for advanced measurement data processing.



These sensor arrays encompass both physical measuring instruments and virtual sensors tailored to assess non-quantitative or integral characteristics. The resultant network operations yield comprehensive insights into the states of complex objects, accompanied by recommendations for ensuring their stable performance. Integral to these systems is a robust means of achieving complete metrological justification for all derived solutions.



Leveraging a hierarchical architecture, these systems align with the control structures of complex objects and possess the capacity for autonomous development through dynamic constraints and information scaling. The article supplements these concepts with real-world examples showcasing the utility of intelligent sensor networks for monitoring and managing complex technical and socio-economic systems.