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.

References

[1]

Amazon. 2019. Amazon Dash Replenishment Service. https://developer.amazon.com/zh/dash-replenishment-service

[2]

Maher Arebey, MA Hannan, Rawshan Ara Begum, and Hassan Basri. 2012. Solid waste bin level detection using gray level co-occurrence matrix feature extraction approach. Journal of environmental management 104 (2012), 9--18.

[3]

Satish Chandra Bera, Hiranmoy Mandal, Sirshendu Saha, and Abhinaba Dutta. 2013. Study of a modified capacitance-type level transducer for any type of liquid. IEEE Transactions on Instrumentation and Measurement 63, 3 (2013), 641--649.

[4]

Joseph W Caldwell. 2008. Fluid level measuring system. US Patent 7,421,895.

[5]

Hüseyin Canbolat. 2009. A novel level measurement technique using three capacitive sensors for liquids. IEEE transactions on Instrumentation and Measurement 58, 10 (2009), 3762--3768.

[6]

P Castellini, M Martarelli, and EP Tomasini. 2006. Laser Doppler Vibrometry: Development of advanced solutions answering to technology's needs. Mechanical systems and signal processing 20, 6 (2006), 1265--1285.

[7]

Chih-Chung Chang and Chih-Jen Lin. 2011. LIBSVM: A library for support vector machines. ACM transactions on intelligent systems and technology (TIST) 2, 3 (2011), 27.

Digital Library

[8]

Meng-Chieh Chiu, Shih-Ping Chang, Yu-Chen Chang, Hao-Hua Chu, Cheryl Chia-Hui Chen, Fei-Hsiu Hsiao, and Ju-Chun Ko. 2009. Playful bottle: a mobile social persuasion system to motivate healthy water intake. In Proceedings of the 11th international conference on Ubiquitous computing. ACM, 185--194.

Digital Library

[9]

Naim Dam and Howard Paul Austerlitz. 2003. System and method of non-invasive discreet, continuous and multi-point level liquid sensing using flexural waves. US Patent 6,631,639.

[10]

Ashutosh Dhekne, Mahanth Gowda, Yixuan Zhao, Haitham Hassanieh, and Romit Roy Choudhury. 2018. Liquid: A wireless liquid identifier. In Proceedings of the 16th Annual International Conference on Mobile Systems, Applications, and Services. ACM, 442--454.

Digital Library

[11]

Paul H Dietz, Darren Leigh, and William S Yerazunis. 2002. Wireless liquid level sensing for restaurant applications. In SENSORS, 2002 IEEE, Vol. 1. IEEE, 715--720.

[12]

Parisa Esmaili, Federico Cavedo, and Michele Norgia. 2018. Differential pressure based liquid level measurement in sloshing condition. In 2018 IEEE International Instrumentation and Measurement Technology Conference (I2MTC). IEEE, 1--6.

[13]

Mingming Fan and Khai N Truong. 2015. SoQr: sonically quantifying the content level inside containers. In Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing. ACM, 3--14.

Digital Library

[14]

Zhi-Fang Fu and Jimin He. 2001. Modal analysis. Elsevier.

[15]

Chuhan Gao, Yilong Li, and Xinyu Zhang. 2018. LiveTag: Sensing human-object interaction through passive chipless WiFi tags. In 15th {USENIX} Symposium on Networked Systems Design and Implementation ({NSDI} 18). 533--546.

[16]

R Geethamani, Rani Gnanamalar, S Sheeba, N Ramyarani, and C Pavithra. 2018. Non-Contact Continuous Capacitive Liquid Level Sensing. International Journal of Pure and Applied Mathematics 119, 12 (2018), 1921--1930.

[17]

Cihun-Siyong Alex Gong, Huan Ke Chiu, Li Ren Huang, Cheng Hsun Lin, Zen Dar Hsu, and Po-Hsun Tu. 2016. Low-cost comb-electrode capacitive sensing device for liquid-level measurement. IEEE Sensors Journal 16, 9 (2016), 2896--2897.

[18]

Unsoo Ha, Yunfei Ma, Zexuan Zhong, Tzu-Ming Hsu, and Fadel Adib. 2018. Learning Food Quality and Safety from Wireless Stickers. In HotNets. 106--112.

[19]

Daniel Halperin, Wenjun Hu, Anmol Sheth, and David Wetherall. 2011. Tool release: Gathering 802.11 n traces with channel state information. ACM SIGCOMM Computer Communication Review 41, 1 (2011), 53--53.

Digital Library

[20]

MA Hannan, Maher Arebey, Rawshan Ara Begum, and Hassan Basri. 2012. An automated solid waste bin level detection system using a gray level aura matrix. Waste management 32, 12 (2012), 2229--2238.

[21]

Md Shafiqul Islam, MA Hannan, Hassan Basri, Aini Hussain, and Maher Arebey. 2014. Solid waste bin detection and classification using Dynamic Time Warping and MLP classifier. Waste management 34, 2 (2014), 281--290.

[22]

Yijun Jiang, Elim Schenck, Spencer Kranz, Sean Banerjee, and Natasha Kholgade Banerjee. 2019. CNN-Based Non-contact Detection of Food Level in Bottles from RGB Images. In International Conference on Multimedia Modeling. Springer, 202--213.

[23]

Gregor Jundt, Adrian Radu, Emmanuel Fort, Jan Duda, Holger Vach, and Neville Fletcher. 2006. Vibrational modes of partly filled wine glasses. The Journal of the Acoustical Society of America 119, 6 (2006), 3793--3798.

[24]

Jong-Yun Kim, Jin-Hong Lee, Sang-Eun Bae, Seungwoo Paek, Si Hyung Kim, Tack-Jin Kim, and Tae-Hong Park. 2017. Automated high-temperature liquid level measurement system using a dynamic tube pressure technique. Journal of Industrial and Engineering Chemistry 49 (2017), 30--35.

[25]

Dennis M Kotz and William R Hinz. 2010. Ultrasonic liquid level detector. US Patent 7,802,470.

[26]

Peng Li, Yulei Cai, Xiaolong Shen, Sharon Nabuzaale, Jie Yin, and Jiaqiang Li. 2014. An accurate detection for dynamic liquid level based on MIMO ultrasonic transducer array. IEEE Transactions on Instrumentation and Measurement 64, 3 (2014), 582--595.

[27]

Xiang Li, Daqing Zhang, Qin Lv, Jie Xiong, Shengjie Li, Yue Zhang, and Hong Mei. 2017. IndoTrack: Device-free indoor human tracking with commodity Wi-Fi. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 1, 3 (2017), 72.

Digital Library

[28]

Jian Liu, Yan Wang, Yingying Chen, Jie Yang, Xu Chen, and Jerry Cheng. 2015. Tracking vital signs during sleep leveraging off-the-shelf wifi. In Proceedings of the 16th ACM International Symposium on Mobile Ad Hoc Networking and Computing. ACM, 267--276.

Digital Library

[29]

Konstantinos Loizou, Eftichios Koutroulis, Dimitrios Zalikas, and Georgios Liontas. 2015. A low-cost capacitive sensor for water level monitoring in large-scale storage tanks. In 2015 IEEE International Conference on Industrial Technology (ICIT). IEEE, 1416--1421.

[30]

Ion Cornel Mituletu, Gilbert-Rainer Gillich, and Nuno MM Maia. 2019. A method for an accurate estimation of natural frequencies using swept-sine acoustic excitation. Mechanical Systems and Signal Processing 116 (2019), 693--709.

[31]

Saleem Latteef Mohammed, Ali Al-Naji, Mashael M Farjo, and Javaan Chahl. 2019. Highly Accurate Water Level Measurement System Using a Microcontroller and an Ultrasonic Sensor. In IOP Conference Series: Materials Science and Engineering, Vol. 518. IOP Publishing, 042025.

[32]

Somnath Mukherjee. 2010. Non-invasive measurement of liquid content inside a small vial. In 2010 IEEE Radio and Wireless Symposium (RWS). IEEE, 527--530.

[33]

Tatsuo Nakagawa, Akihiko Hyodo, Kenichi Osada, Hideaki Kurata, and Shigeru Oho. 2011. Contactless liquid-level measurement through opaque container using millimeter-wave sensor. In SENSORS, 2011 IEEE. IEEE, 1421--1424.

[34]

Ozmo. 2017. Ozmo Smart Bottle. https://www.ozmo.io/ozmo-smart-bottle/

[35]

Ki-Woong Park and Hyeon Cheol Kim. 2015. High accuracy pressure type liquid level measurement system capable of measuring density. In TENCON 2015--2015 IEEE Region 10 Conference. IEEE, 1--5.

[36]

Harvard Health Publishing. 2019. Calorie counting made easy. https://www.health.harvard.edu/staying-healthy/calorie-counting-made- easy

[37]

Shyam Purkayastha. 2016. IoT application that monitors your food pantry. https://www.ibm.com/cloud/blog/iot-inventory-monitor-part1

[38]

Kun Qian, Chenshu Wu, Zheng Yang, Yunhao Liu, and Kyle Jamieson. 2017. Widar: Decimeter-level passive tracking via velocity monitoring with commodity Wi-Fi. In Proceedings of the 18th ACM International Symposium on Mobile Ad Hoc Networking and Computing. ACM, 6.

Digital Library

[39]

Kun Qian, Chenshu Wu, Yi Zhang, Guidong Zhang, Zheng Yang, and Yunhao Liu. 2018. Widar2. 0: Passive human tracking with a single wi-fi link. In Proceedings of the 16th Annual International Conference on Mobile Systems, Applications, and Services. ACM, 350--361.

Digital Library

[40]

Kun Qian, Chenshu Wu, Zimu Zhou, Yue Zheng, Zheng Yang, and Yunhao Liu. 2017. Inferring motion direction using commodity wi-fi for interactive exergames. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems. ACM, 1961--1972.

Digital Library

[41]

Tauhidur Rahman, Alexander T Adams, Perry Schein, Aadhar Jain, David Erickson, and Tanzeem Choudhury. 2016. Nutrilyzer: A mobile system for characterizing liquid food with photoacoustic effect. In Proceedings of the 14th ACM Conference on Embedded Network Sensor Systems CD-ROM. ACM, 123--136.

Digital Library

[42]

Ferran Reverter, Xiujun Li, and Gerard CM Meijer. 2007. Liquid-level measurement system based on a remote grounded capacitive sensor. Sensors and Actuators A: Physical 138, 1 (2007), 1--8.

[43]

Thomas D Rossing. 1990. Wine glasses, bell modes, and Lord Rayleigh. The Physics Teacher 28, 9 (1990), 582--585.

[44]

Thomas D Rossing. 1994. Acoustics of the glass harmonica. The Journal of the Acoustical Society of America 95, 2 (1994), 1106--1111.

[45]

Jeongjae Ryu, Hanbert Jeong, Yugang Chen, Chungik Oh, Jaegyu Kim, Hongjun Kim, Seongwoo Cho, Kwangsoo No, Yong-Hwa Park, Steve Park, et al. 2018. Flexible piezoelectric liquid volume sensor. Sensors and Actuators A: Physical 276 (2018), 219--225.

[46]

Shelly K. Schwartz. 2012. How to Help Your Patients Manage Their Medications. https://www.physicianspractice.com/patient-relations/how-help-your-patients-manage-their-medications

[47]

CE Shannon. 1949. Communication in the Presence of Noise. Proceedings of the IRE 37, 1 (1949), 10--21.

[48]

Jonathon Shlens. 2014. A tutorial on principal component analysis. arXiv preprint arXiv:1404.1100 (2014).

[49]

Emily Slawek. 2017. I Stayed Hydrated for Two Weeks and It Changed My Life. https://www.nbcnews.com/better/diet-fitness/i-stayed-hydrated-two-weeks-it-changed-my-life-n731131

[50]

Hidrate Spark. 2019. Hidrate Spark Smart Water Bottle. https://hidratespark.com/

[51]

Sheng Tan and Jie Yang. 2016. WiFinger: leveraging commodity WiFi for fine-grained finger gesture recognition. In Proceedings of the 17th ACM international symposium on mobile ad hoc networking and computing. ACM, 201--210.

Digital Library

[52]

Sheng Tan, Linghan Zhang, and Jie Yang. 2018. Sensing Fruit Ripeness Using Wireless Signals. In 2018 27th International Conference on Computer Communication and Networks (ICCCN). IEEE, 1--9.

[53]

Denis Terwagne and John WM Bush. 2011. Tibetan singing bowls. Nonlinearity 24, 8 (2011), R51.

[54]

Edin Terzic, CR Nagarajah, and Muhammad Alamgir. 2010. Capacitive sensor-based fluid level measurement in a dynamic environment using neural network. Engineering Applications of Artificial Intelligence 23, 4 (2010), 614--619.

Digital Library

[55]

Guanhua Wang, Yongpan Zou, Zimu Zhou, Kaishun Wu, and Lionel M Ni. 2016. We can hear you with wi-fi! IEEE Transactions on Mobile Computing 15, 11 (2016), 2907--2920.

[56]

Ju Wang, Jie Xiong, Xiaojiang Chen, Hongbo Jiang, Rajesh Krishna Balan, and Dingyi Fang. 2017. TagScan: Simultaneous target imaging and material identification with commodity RFID devices. In Proceedings of the 23rd Annual International Conference on Mobile Computing and Networking. ACM, 288--300.

Digital Library

[57]

Sheng-Wei Wang, Chen-Chia Chen, Chieh-Ming Wu, and Chun-Ming Huang. 2018. A continuous water-level sensor based on load cell and floating pipe. In 2018 IEEE International Conference on Applied System Invention (ICASI). IEEE, 151--154.

[58]

Wei Wang, Alex X Liu, Muhammad Shahzad, Kang Ling, and Sanglu Lu. 2015. Understanding and modeling of wifi signal based human activity recognition. In Proceedings of the 21st annual international conference on mobile computing and networking. ACM, 65--76.

Digital Library

[59]

Yan Wang, Jian Liu, Yingying Chen, Marco Gruteser, Jie Yang, and Hongbo Liu. 2014. E-eyes: device-free location-oriented activity identification using fine-grained wifi signatures. In Proceedings of the 20th annual international conference on Mobile computing and networking. ACM, 617--628.

Digital Library

[60]

Yuxi Wang, Kaishun Wu, and Lionel M Ni. 2016. Wifall: Device-free fall detection by wireless networks. IEEE Transactions on Mobile Computing 16, 2 (2016), 581--594.

Digital Library

[61]

Yan Wang, Jie Yang, Yingying Chen, Hongbo Liu, Marco Gruteser, and Richard P Martin. 2014. Tracking human queues using single-point signal monitoring. In Proceedings of the 12th annual international conference on Mobile systems, applications, and services. 42--54.

Digital Library

[62]

Teng Wei, Shu Wang, Anfu Zhou, and Xinyu Zhang. 2015. Acoustic eavesdropping through wireless vibrometry. In Proceedings of the 21st Annual International Conference on Mobile Computing and Networking. ACM, 130--141.

Digital Library

[63]

Wikipedia contributors. 2019. Resonance --- Wikipedia, The Free Encyclopedia. https://en.wikipedia.org/w/index.php?title=Resonance&oldid=908795753

[64]

Chenshu Wu, Zheng Yang, Zimu Zhou, Kun Qian, Yunhao Liu, and Mingyan Liu. 2015. PhaseU: Real-time LOS identification with WiFi. In 2015 IEEE conference on computer communications (INFOCOM). IEEE, 2038--2046.

[65]

Zhuoling Xiao, Hongkai Wen, Andrew Markham, Niki Trigoni, Phil Blunsom, and Jeff Frolik. 2014. Non-line-of-sight identification and mitigation using received signal strength. IEEE Transactions on Wireless Communications 14, 3 (2014), 1689--1702.

[66]

Shichao Yue and Dina Katabi. 2019. Liquid Testing with Your Smartphone. In Proceedings of the 17th Annual International Conference on Mobile Systems, Applications, and Services (MobiSys '19). ACM, New York, NY, USA, 275--286.

Digital Library

[67]

Yiran Zhao, Shuochao Yao, Shen Li, Shaohan Hu, Huajie Shao, and Tarek F Abdelzaher. 2017. VibeBin: A vibration-based waste bin level detection system. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 1, 3 (2017), 122.

Digital Library

Cited By

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
https://dl.acm.org/doi/10.1145/3643504
Kianpisheh MMariakakis ATruong K(2024)exHARProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36435008:1(1-30)Online publication date: 6-Mar-2024
https://dl.acm.org/doi/10.1145/3643500
Yan DYang PShang FJiang WLi X(2024)Wi-PainterProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36338097:4(1-25)Online publication date: 12-Jan-2024
https://dl.acm.org/doi/10.1145/3633809
Show More Cited By

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

Recommendations

Intelligent Oven in Smart Home Environment
ICRCCS '09: Proceedings of the 2009 International Conference on Research Challenges in Computer Science

Smart homes are gradually becoming one of the main applications in the high technology area. The intelligent appliance is a fundamental component of a smart home environment. People tend to invest in the kitchen appliances as they will be used ...
Read More
Delivering home healthcare through a Cloud-based Smart Home Environment (CoSHE)

The dramatic increase of senior population worldwide is challenging the existing healthcare and support systems. Recently, smart home environments are utilized for ubiquitous health monitoring, allowing patients to stay at the comfort of their homes. In ...
Read More
Smart home – digitally engineered domestic life

The purpose of the Smart Home Project is to devise a set of intelligent home appliances that can provide an awareness of the users' needs, providing them with a better home life experience without overpowering them with complex technologies and ...
Read More

Comments

Information & Contributors

Information

Published In

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

Issue’s Table of Contents

Copyright © 2020 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 18 March 2020

Published in IMWUT Volume 4, Issue 1

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article
Research
Refereed

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

27
Total Citations
View Citations
952
Total Downloads

Downloads (Last 12 months)137
Downloads (Last 6 weeks)20

Other Metrics

View Author Metrics

Citations

Cited By

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
https://dl.acm.org/doi/10.1145/3643504
Kianpisheh MMariakakis ATruong K(2024)exHARProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36435008:1(1-30)Online publication date: 6-Mar-2024
https://dl.acm.org/doi/10.1145/3643500
Yan DYang PShang FJiang WLi X(2024)Wi-PainterProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36338097:4(1-25)Online publication date: 12-Jan-2024
https://dl.acm.org/doi/10.1145/3633809
Wang ZGuo YRen ZSong WSun ZChen CGuo BYu Z(2024)LiqDetectorProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36314437:4(1-24)Online publication date: 12-Jan-2024
https://dl.acm.org/doi/10.1145/3631443
Su YZhang TFeng JShi YYang XWu T(2024)Tagnoo: Enabling Smart Room-Scale Environments with RFID-Augmented PlywoodProceedings of the CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642356(1-18)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642356
Kim TPark SOh SKim H(2024)LiquidListener: Supporting Ubiquitous Liquid Volume Sensing via Singing SoundsIEEE Access10.1109/ACCESS.2024.337539212(39833-39846)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3375392
Shi YZhang XFu LZhang H(2024)An investigation of the private-attribute leakage in WiFi sensingHigh-Confidence Computing10.1016/j.hcc.2024.100209(100209)Online publication date: Feb-2024
https://doi.org/10.1016/j.hcc.2024.100209
Ren YWang YTan SChen YYang JCalandrino JTroncoso C(2023)Person re-identification in 3D spaceProceedings of the 32nd USENIX Conference on Security Symposium10.5555/3620237.3620529(5217-5234)Online publication date: 9-Aug-2023
https://dl.acm.org/doi/10.5555/3620237.3620529
Ismail INiazi IHaavik HKamavuako E(2023)A Cross-Day Analysis of EMG Features, Classifiers, and Regressors for Swallowing Events Detection and Fluid Intake Volume EstimationSensors10.3390/s2321878923:21(8789)Online publication date: 28-Oct-2023
https://doi.org/10.3390/s23218789
Afzal SKludze AKarmakar SChandra RGhasempour YCosta XHassanieh HAsadi ACox LPerino DWidmer JGiustiniano D(2023)AgriTera: Accurate Non-Invasive Fruit Ripeness Sensing via Sub-Terahertz Wireless SignalsProceedings of the 29th Annual International Conference on Mobile Computing and Networking10.1145/3570361.3613275(1-15)Online publication date: 2-Oct-2023
https://dl.acm.org/doi/10.1145/3570361.3613275
Show More Cited By

View Options

Get Access

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Article

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Media

Figures

Other

Tables

View Issue’s Table of Contents