research-article

Liquid Level Sensing Using Commodity WiFi in a Smart Home Environment

Authors:

Jie YangAuthors Info & Claims

Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, Volume 4, Issue 1

Article No.: 24, Pages 1 - 30

https://doi.org/10.1145/3380996

Published: 18 March 2020 Publication History

Abstract

The popularity of Internet-of-Things (IoT) has provided us with unprecedented opportunities to enable a variety of emerging services in a smart home environment. Among those services, sensing the liquid level in a container is critical to building many smart home and mobile healthcare applications that improve the quality of life. This paper presents LiquidSense, a liquid level sensing system that is low-cost, high accuracy, widely applicable to different daily liquids and containers, and can be easily integrated with existing smart home networks. LiquidSense uses existing home WiFi network and a low-cost transducer that attached to the container to sense the resonance of the container for liquid level detection. In particular, our system mounts a low-cost transducer on the surface of the container and emits a well-designed chirp signal to make the container resonant, which introduces subtle changes to the home WiFi signals. By analyzing the subtle phase changes of the WiFi signals, LiquidSense extracts the resonance frequency as a feature for liquid level detection. Our system constructs prediction models for both continuous and discrete predictions using curve fitting and SVM respectively. We evaluate LiquidSense in home environments with containers of three different materials and six types of liquids. Results show that LiquidSense achieves an overall accuracy of 97% for continuous prediction and an overall F-score of 0.968 for discrete predication. Results also show that our system has a large coverage in a home environment and works well under non-line-of-sight (NLOS) scenarios.

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Cited By

Li BRen YWang YYang J(2024)SpaceBeat: Identity-aware Multi-person Vital Signs Monitoring Using Commodity WiFiProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36785908:3(1-23)Online publication date: 9-Sep-2024
https://dl.acm.org/doi/10.1145/3678590
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Fujii AMurao KKostakos VKay JHoang T(2024)Water Level Recognition by Analyzing the Sound when Pouring WaterCompanion of the 2024 on ACM International Joint Conference on Pervasive and Ubiquitous Computing10.1145/3675094.3678440(464-469)Online publication date: 5-Oct-2024
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Index Terms

Liquid Level Sensing Using Commodity WiFi in a Smart Home Environment
1. Human-centered computing
  1. Ubiquitous and mobile computing
    1. Ubiquitous and mobile computing systems and tools

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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 4, Issue 1

March 2020

1006 pages

EISSN:2474-9567

DOI:10.1145/3388993

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Copyright © 2020 ACM.

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Publication History

Published: 18 March 2020

Published in IMWUT Volume 4, Issue 1

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Cited By

Li BRen YWang YYang J(2024)SpaceBeat: Identity-aware Multi-person Vital Signs Monitoring Using Commodity WiFiProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36785908:3(1-23)Online publication date: 9-Sep-2024
https://dl.acm.org/doi/10.1145/3678590
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
https://dl.acm.org/doi/10.1145/3678589
Fujii AMurao KKostakos VKay JHoang T(2024)Water Level Recognition by Analyzing the Sound when Pouring WaterCompanion of the 2024 on ACM International Joint Conference on Pervasive and Ubiquitous Computing10.1145/3675094.3678440(464-469)Online publication date: 5-Oct-2024
https://dl.acm.org/doi/10.1145/3675094.3678440
Wang YRen YYang J(2024)Multi-Subject 3D Human Mesh Construction Using Commodity WiFiProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36435048:1(1-25)Online publication date: 6-Mar-2024
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Ismail IKamavuako E(2024)Differentiating Fluid-intake-related Swallowing Events from Saliva and Solid Food Intake Using Swallowing Sounds and Conventional Machine Learning2024 IEEE 22nd Mediterranean Electrotechnical Conference (MELECON)10.1109/MELECON56669.2024.10608589(491-496)Online publication date: 25-Jun-2024
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