Machine learning and computational intelligence methods, especially deep learning, can be used to create smart sensors that can perform testing, classification, or prediction. The whole menagerie of sensors, including inductive proximity sensors, photoelectric retro-reflective sensors, ultrasonic sensors, and others, can be beneficial to all areas—from Industry 4.0, through cars, to smart offices, homes, or hospitals. Synergistic hyperconnectivity brought by the emergence of the IoT will increase the applicability of such intelligent sensors. This Special Issue is addressed to all soft computing methods enabling in-sensor, edge, and similar computing for machine vision, data acquisition, or diagnostics. The methods covered will include deep learning, fuzzy logic, evolutionary methods, and various data mining techniques.
sensor technology and application
Internet of things
data fusion and deep learning in sensor systems
Special Issue Editor
Dr. Rafal Scherer
Częstochowa University Of Technology, Czestochowa, Poland
Interests: machine learning; neural networks; computer vision; artificial intelligence
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