神经形态工程学
计算机科学
无线传感器网络
计算
过程(计算)
分布式计算
数据处理
人工神经网络
人工智能
计算机网络
操作系统
算法
作者
Tianqing Wan,Bangjie Shao,Sijie Ma,Yue Zhou,Qiao Li,Yang Chai
标识
DOI:10.1002/adma.202203830
摘要
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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