research-article

FG-LiquID: A Contact-less Fine-grained Liquid Identifier by Pushing the Limits of Millimeter-wave Sensing

Authors:

Huanhuan Zhang,

Huadong MaAuthors Info & Claims

Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, Volume 5, Issue 3

Article No.: 116, Pages 1 - 27

https://doi.org/10.1145/3478075

Published: 14 September 2021 Publication History

Abstract

Contact-less liquid identification via wireless sensing has diverse potential applications in our daily life, such as identifying alcohol content in liquids, distinguishing spoiled and fresh milk, and even detecting water contamination. Recent works have verified the feasibility of utilizing mmWave radar to perform coarse-grained material identification, e.g., discriminating liquid and carpet. However, they do not fully exploit the sensing limits of mmWave in terms of fine-grained material classification. In this paper, we propose FG-LiquID, an accurate and robust system for fine-grained liquid identification. To achieve the desired fine granularity, FG-LiquID first focuses on the small but informative region of the mmWave spectrum, so as to extract the most discriminative features of liquids. Then we design a novel neural network, which uncovers and leverages the hidden signal patterns across multiple antennas on mmWave sensors. In this way, FG-LiquID learns to calibrate signals and finally eliminate the adverse effect of location interference caused by minor displacement/rotation of the liquid container, which ensures robust identification towards daily usage scenarios. Extensive experimental results using a custom-build prototype demonstrate that FG-LiquID can accurately distinguish 30 different liquids with an average accuracy of 97%, under 5 different scenarios. More importantly, it can discriminate quite similar liquids, such as liquors with the difference of only 1% alcohol concentration by volume.

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Index Terms

FG-LiquID: A Contact-less Fine-grained Liquid Identifier by Pushing the Limits of Millimeter-wave Sensing
1. Human-centered computing
  1. Ubiquitous and mobile computing
    1. Ubiquitous and mobile computing design and evaluation methods

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cover image Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies

Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies Volume 5, Issue 3

Sept 2021

1443 pages

EISSN:2474-9567

DOI:10.1145/3486621

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Published: 14 September 2021

Published in IMWUT Volume 5, Issue 3

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Wang ZChen ZZhang YGeng CSong WSun ZGuo BYu ZChen L(2024)GrainSense: A Wireless Grain Moisture Sensing System Based on Wi-Fi SignalsProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36785898:3(1-25)Online publication date: 9-Sep-2024
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Zhang ZSong DZhou AMa H(2024)airTac: A Contactless Digital Tactile Receptor for Detecting Material and Roughness via Terahertz SensingProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36785868:3(1-37)Online publication date: 9-Sep-2024
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Shang FYang PYan DZhang SLi X(2024)LiquImagerProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36435098:1(1-29)Online publication date: 6-Mar-2024
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