Andrzej Dzierwa – författare

In this book, the authors present a comprehensive study of the effects of operating parameters (load, amplitude, frequency) on dry gross fretting of rough surfaces. It helps the reader to efficient surface preparations in order to monitor and reduce damage caused by fretting. It exposes the effect of surface topography on fretting, which is often neglected.

This book presents an integrated overview of modern sensor technologies and intelligent measurement systems. It combines research on digital signal processing, distributed IIoT architectures, embedded systems, and cybersecurity for resource-limited nodes. Such integration enhances accuracy, interference resistance, scalability, and computational efficiency, improving monitoring and diagnostic performance. A key focus is the convergence of sensors with artificial intelligence and machine learning, enabling multichannel data analysis, anomaly detection, and predictive maintenance through digital twins and adaptive algorithms. This approach ensures high diagnostic sensitivity, reliability, and autonomous real-time decision-making in industrial and technical systems. The book also covers developments in microelectronics, MEMS, and robotics, from material design and metrological validation to embedded implementation. Advanced transducers and actuators increase energy efficiency and interface compatibility. Contributions on biomedical, optoelectronic, photonic, energy, and environmental sensors highlight improved precision and integration with IoT analytics, confirming the vital role of sensor technologies in medicine, energy, and sustainability. The book is of interest to experts in the field of automation, computer integrated technologies, robotics, and related spheres, as well as scientists, and Ph.D. students.

This book presents an integrated overview of modern sensor technologies and intelligent measurement systems. It combines research on digital signal processing, distributed IIoT architectures, embedded systems, and cybersecurity for resource-limited nodes. Such integration enhances accuracy, interference resistance, scalability, and computational efficiency, improving monitoring and diagnostic performance. A key focus is the convergence of sensors with artificial intelligence and machine learning, enabling multichannel data analysis, anomaly detection, and predictive maintenance through digital twins and adaptive algorithms. This approach ensures high diagnostic sensitivity, reliability, and autonomous real-time decision-making in industrial and technical systems. The book also covers developments in microelectronics, MEMS, and robotics, from material design and metrological validation to embedded implementation. Advanced transducers and actuators increase energy efficiency and interface compatibility. Contributions on biomedical, optoelectronic, photonic, energy, and environmental sensors highlight improved precision and integration with IoT analytics, confirming the vital role of sensor technologies in medicine, energy, and sustainability. The book is of interest to experts in the field of automation, computer integrated technologies, robotics, and related spheres, as well as scientists, and Ph.D. students.