OPERATIONAL FREQUENCIES OF MEASUREMENT SYSTEM COMPONENTS AS KEY DETERMINANTS OF APPLICATION POTENTIAL

This paper presents an investigation of an integrated measurement system combining sensors and data acquisition software, with a focus on how the operational frequencies of individual components determine overall system capabilities. The study explores the frequency-dependent application possibilities of such systems, demonstrating that their performance is not solely defined by hardware specifications but also by dynamic interactions between system elements. The analysis shows that these capabilities can extend beyond routine measurement tasks, enabling more advanced monitoring, diagnostics, and experimental applications. In addition, the potential integration of emerging artificial intelligence techniques is discussed as a means to further enhance system functionality, optimize signal processing, and expand the range of practical applications. Experimental validation and case studies illustrate how operational frequency characteristics influence measurement accuracy, responsiveness, and system adaptability. The results provide insights for the design and deployment of flexible, high-performance measurement systems in research and industrial environments, highlighting opportunities for AI-assisted enhancement of both system capabilities and application scope.