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Intelligent Electromagnetic Sensing with Learnable Data Acquisition and Processing.


ABSTRACT: Electromagnetic (EM) sensing is a widespread contactless examination technique with applications in areas such as health care and the internet of things. Most conventional sensing systems lack intelligence, which not only results in expensive hardware and complicated computational algorithms but also poses important challenges for real-time in situ sensing. To address this shortcoming, we propose the concept of intelligent sensing by designing a programmable metasurface for data-driven learnable data acquisition and integrating it into a data-driven learnable data-processing pipeline. Thereby, a measurement strategy can be learned jointly with a matching data post-processing scheme, optimally tailored to the specific sensing hardware, task, and scene, allowing us to perform high-quality imaging and high-accuracy recognition with a remarkably reduced number of measurements. We report the first experimental demonstration of "learned sensing" applied to microwave imaging and gesture recognition. Our results pave the way for learned EM sensing with low latency and computational burden.

SUBMITTER: Li HY 

PROVIDER: S-EPMC7660445 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature

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Intelligent Electromagnetic Sensing with Learnable Data Acquisition and Processing.

Li Hao-Yang HY   Zhao Han-Ting HT   Wei Meng-Lin ML   Ruan Heng-Xin HX   Shuang Ya Y   Cui Tie Jun TJ   Del Hougne Philipp P   Li Lianlin L  

Patterns (New York, N.Y.) 20200410 1


Electromagnetic (EM) sensing is a widespread contactless examination technique with applications in areas such as health care and the internet of things. Most conventional sensing systems lack intelligence, which not only results in expensive hardware and complicated computational algorithms but also poses important challenges for real-time <i>in situ</i> sensing. To address this shortcoming, we propose the concept of intelligent sensing by designing a programmable metasurface for data-driven le  ...[more]

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