Rapid advances in smart sensing technologies have provided new tools to collect signals for system health monitoring in different engineering sectors, such as mechanical, electrical, civil, and chemical engineering. Reliable monitoring information can be used in predictive maintenance to improve production quality, operation safety, and reliability, as well as to reduce maintenance costs. On the other hand, the application of smart sensor networks can provide a large amount of data with high variety and pose significant challenges on the signal processing side. Artificial intelligence provides a promising approach for effective learning and decision-making for complex and integrated systems. This Special Issue focuses on smart sensor technology and its applications in health condition monitoring across different domains and engineering sectors. We welcome original research contributions and state-of-the-art reviews from academia and industry. The Special Issue topics include but are not limited to the following:
Smart sensor technology (e.g., vibration, temperature, humidity, and electric current);
Sensor networks and internet of things (IOT);
Design, implementation, and testing of sensing systems;
Fault detection and diagnosis of different engineering systems using sensor data;
Prognostics and health management;
Artificial intelligence for health condition monitoring;
Machine learning and deep learning to improve decision-making efficiency;
Intelligent manufacturing and control;
Energy harvesting for sensor networks；
Applications in different engineering disciplines.
Prof. Dr. Wilson Wang
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