Intelligent metasurface imager and recognizer

Lianlin Li; Ya Shuang; Qian Ma; Haoyang Li; Hanting Zhao; Menglin Wei; Che Liu; Chenglong Hao; Cheng-Wei Qiu; Tie Jun Cui

doi:10.1038/s41377-019-0209-z

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Intelligent metasurface imager and recognizer

Articles

- Intelligent metasurface imager and recognizer
- Light: Science & Applications Vol. 8, Issue 5, Pages: 893-901(2019)
- Affiliations：
  
  1.State Key Laboratory of Advanced Optical Communication Systems and Networks, Department of Electronics, Peking University, Beijing 100871, China
  2.State Key Laboratory of Millimeter Waves, Southeast University, Nanjing 210096, China
  3.Department of Electrical and Computer Engineering, National University of Singapore, 4 Engineering Drive 3, 117583 Singapore, Singapore
- Author bio：
  
  Lianlin Li (lianlin.li@pku.edu.cn)
  Tie Jun Cui (tjcui@seu.edu.cn)
- Funds：
- DOI：10.1038/s41377-019-0209-z
  CLC：
- Published：2019，
  
  Published Online：21 October 2019，
  
  Received：06 September 2019，
  
  Revised：12 October 2019，
  
  Accepted：09 October 2019
- Accepted：
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Li, L. L. et al. Intelligent metasurface imager and recognizer. Light: Science & Applications, 8, 893-901 (2019).
DOI：

Li, L. L. et al. Intelligent metasurface imager and recognizer. Light: Science & Applications, 8, 893-901 (2019). DOI： 10.1038/s41377-019-0209-z.

摘要

Abstract

There is an increasing need to remotely monitor people in daily life using radio-frequency probe signals. However

conventional systems can hardly be deployed in real-world settings since they typically require objects to either deliberately cooperate or carry a wireless active device or identification tag. To accomplish complicated successive tasks using a single device in real time

we propose the simultaneous use of a smart metasurface imager and recognizer

empowered by a network of artificial neural networks (ANNs) for adaptively controlling data flow. Here

three ANNs are employed in an integrated hierarchy

transforming measured microwave data into images of the whole human body

classifying specifically designated spots (hand and chest) within the whole image

and recognizing human hand signs instantly at a Wi-Fi frequency of 2.4 GHz. Instantaneous in situ full-scene imaging and adaptive recognition of hand signs and vital signs of multiple non-cooperative people were experimentally demonstrated. We also show that the proposed intelligent metasurface system works well even when it is passively excited by stray Wi-Fi signals that ubiquitously exist in our daily lives. The reported strategy could open up a new avenue for future smart cities

smart homes

human-device interaction interfaces

health monitoring

and safety screening free of visual privacy issues.

关键词

Keywords

references

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