The internet of things enables the implementation of Cyber–Physical Systems (CPS) to control the physical processes and interactions between them through a range of sensors, controllers and communication systems. Images and videos in real–time over the internet for data analysis and data fusion applies machine learning algorithms to recognize people, objects, giant, context and situations automatically. The improvements in deep learning algorithms compounded with lower cost hardware make this research area emerging and practically realizable. The improvements in software, hardware technologies and storage is essential to improve the reliability of such systems. Video analytics also requires considerations of cyber security and privacy as essential ingredients to the scalability, and trust management issues in practical applications. To address these, the development of enabling vision devices, circuits and systems within the CPS framework is promoted. This special issue will present the state of the art research results on the topic of vision sensors, circuits, and systems on its application to the internet of things for industrial and exploratory applications. The areas of interests include, but are not limited to, the following CPS–relevant topics:<br>Data–driven approaches<br>Software/Hardware codesign approaches<br>Design and test for vision sensors<br>CPS security in vision systems<br>Complexity, reliability, and scalability<br>IoT vision system implementations<br>Bioinspired and Neuromorphic vision computing<br>Architecture design and analysis<br>Circuits and systems for video analytics<br>Deep learning vision circuits and systems<br>Systems approaches of CPS<br>CPS in real–time vision computing<br>
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IET CPS
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