In-Sensor Computing: Materials, Devices, and Integration Technologies

Tianqing Wan, Bangjie Shao, Sijie Ma, Yue Zhou, Qiao Li, Yang Chai

Research output: Journal article publicationJournal articleAcademic researchpeer-review

66 Citations (Scopus)

Abstract

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.

Original languageEnglish
Article number2203830
JournalAdvanced Materials
DOIs
Publication statusAccepted/In press - 2022

Keywords

  • bioinspired devices
  • in-sensor computing
  • near-sensor computing
  • optoelectronic devices
  • vision sensors

ASJC Scopus subject areas

  • General Materials Science
  • Mechanics of Materials
  • Mechanical Engineering

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