Artificial Intelligence for Smart Sensing, Test and Measurement

Dear Colleagues,

The automated measurement tasks related to the monitoring of biomedical, environmental and industrial processes have become a reality in the context of the latest developments in the field of sensors, real-time processing systems and communication protocols. Nowadays, data acquired in an automated way can be stored in a database and analyzed in an on-line or off-line manner. Not only classical algorithms but also artificial intelligence algorithms can be employed to perform regression, clustering and classification tasks associated with monitored processes. Based on applied computational intelligence and machine learning techniques, useful information can be extracted. In the medical field, this could be information associated with disease diagnosis or the evolution of human health status according to applied treatment. Other examples of applications of computational intelligence and machine learning techniques include the extraction of information of anomalous functioning of an industrial system or the forecasting of the production of a photovoltaic system for a period of time. The acquired data are strongly dependent on the sensor characteristics, which can also be modeled using AI.

This Special Issue aims to highlight recent advances related to artificial intelligence algorithms, including machine learning and computational intelligence algorithms, applied in the field of sensors and automated measurement systems. Thus, we welcome contributions considering different fields of applications of the AMS (e.g., biomedical, environmental, industrial) where the implemented AI can assure higher accuracy, reliability and productivity of the systems.