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The number of sensor nodes in the Internet of Things is growing rapidly, leading to a large volume of data generated at sensory terminals. Frequent data transfer between the sensors and computing units causes severe limitations on the system performance in terms of energy efficiency, speed, and security. To efficiently process a substantial amount of sensory data, a novel computation paradigm that can integrate computing functions into sensor networks should be developed. The in-sensor computing paradigm reduces data transfer and also decreases the high computing complexity by processing data locally. Here, the hardware implementation of the in-sensor computing paradigm at the device and array levels is discussed. The physical mechanisms that lead to unique sensory response characteristics and their corresponding computing functions are illustrated. In particular, bioinspired device characteristics enable the implementation of the functionalities of neuromorphic computation. The integration technology is also discussed and the perspective on the future development of in-sensor computing is provided.
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Tianqing Wan
Hong Kong Polytechnic University
Bangjie Shao
Hong Kong Polytechnic University
Sijie Ma
Hong Kong Polytechnic University
Advanced Materials
Hong Kong Polytechnic University
Shenzhen Polytechnic
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Wan et al. (Sat,) studied this question.
synapsesocial.com/papers/69d8f7976715230d10bedc02 — DOI: https://doi.org/10.1002/adma.202203830