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China Conference on Wireless Sensor Networks

CWSN 2022: Wireless Sensor Networks pp 1–18Cite as

MmLiquid: Liquid Identification Using mmWave

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1715))

Abstract

Liquid identification is an essential technology for water safety monitoring. This paper shows the feasibility of identifying liquid using millimeter wave (mmWave) signals. The inherent principle comes from that the fine-grained mmWave signals can capture signal attenuation, phase shift, and propagation delay when penetrating the liquid. We have conducted a preliminary experiment to prove the effectiveness of using mmWave for liquid identification. However, after moving the container, the identification accuracy will drop significantly. To address this challenge, we propose a robust mmWave-based liquid identification approach MmLiquid, which uses a container position information filtering (CPIF) scheme to eliminate the influence of different container positions. MmLiquid will extract container position-independent information from the original mmWave signals and train a deep complex model (DCN) for accurate liquid identification. To further improve the identification performance, we set up an identification environment with two reflective surfaces to capture effective mmWave signals that contain more liquids information. We implement MmLiquid using commercial mmWave devices. Experimental results on 16 kinds of liquids at 24 different container positions show that MmLiquid can achieve an average liquid identification accuracy of 97.6%.

This work is supported by NSFC under grant no. 62072396, Zhejiang Provincial Natural Science Foundation for Distinguished Young Scholars under grant no. LR19F020001, the Fundamental Research Funds for the Central Universities (no. 226-2022-00087), and Alibaba-Zhejiang University Joint Institute of Frontier Technologies.

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Author information

Authors and Affiliations

  1. College of Computer Science, Zhejiang University, Hangzhou, China

    Dingyue Cao, Yuxiang Lin, Yi Gao & Wei Dong

  2. Alibaba Group, Hangzhou, China

    Geng Ren

  3. Alibaba-Zhejiang University Joint Institute of Frontier Technologies, Hangzhou, China

    Yi Gao & Wei Dong

Authors
  1. Dingyue Cao
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  2. Yuxiang Lin
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  3. Geng Ren
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  4. Yi Gao
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  5. Wei Dong
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Corresponding author

Correspondence to Wei Dong .

Editor information

Editors and Affiliations

  1. Beijing University of Posts and Telecommunications, Beijing, China

    Huadong Ma

  2. Tsinghua University, Beijing, China

    Xue Wang

  3. Guangdong University of Technology, Guangzhou, China

    Lianglun Cheng

  4. Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China

    Li Cui

  5. Beijing University of Posts and Telecommunications, Beijing, China

    Liang Liu

  6. Guangdong University of Technology, Guangzhou, China

    An Zeng

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Cao, D., Lin, Y., Ren, G., Gao, Y., Dong, W. (2022). MmLiquid: Liquid Identification Using mmWave. In: Ma, H., Wang, X., Cheng, L., Cui, L., Liu, L., Zeng, A. (eds) Wireless Sensor Networks. CWSN 2022. Communications in Computer and Information Science, vol 1715. Springer, Singapore. https://doi.org/10.1007/978-981-19-8350-4_1

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  • DOI: https://doi.org/10.1007/978-981-19-8350-4_1

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-19-8349-8

  • Online ISBN: 978-981-19-8350-4

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