research-article

VECTOR: Velocity Based Temperature-field Monitoring with Distributed Acoustic Devices

Authors:

Wei WangAuthors Info & Claims

Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, Volume 6, Issue 3

Article No.: 144, Pages 1 - 28

https://doi.org/10.1145/3550336

Published: 07 September 2022 Publication History

Abstract

Ambient temperature distribution monitoring is desired in a variety of real-life applications including indoors temperature control and building energy management. Traditional temperature sensors have their limitations in the aspects of single point/item based measurements, slow response time and huge cost for distribution estimation. In this paper, we introduce VECTOR, a temperature-field monitoring system that achieves high temperature sensing accuracy and fast response time using commercial sound playing/recording devices. First, our system uses a distributed ranging algorithm to measure the time-of-flight of multiple sound paths with microsecond resolution. We then propose a dRadon transform algorithm that reconstructs the temperature distribution from the measured speed of sound along different paths. Our experimental results show that we can measure the temperature with an error of 0.25°C from single sound path and reconstruct the temperature distribution at a decimeter-level spatial resolution.

Supplementary Material

wan (wan.zip)

Supplemental movie, appendix, image and software files for, VECTOR: Velocity Based Temperature-field Monitoring with Distributed Acoustic Devices

Download
876.15 KB

References

[1]

Yanghui Ou, Xifu Wang, and Jingyun Liu. Warehouse multipoint temperature and humidity monitoring system design based on kingview. AIP Conference Proceedings, 1834(1):040009, 2017.

[2]

A. Pedrini, F.S. Westphal, and R. Lamberts. A methodology for building energy modelling and calibration in warm climates. Building and Environment, 37(8):903--912, 2002.

[3]

Doaa M. Atia and Hanaa T. El-madany. Analysis and design of greenhouse temperature control using adaptive neuro-fuzzy inference system. Journal of Electrical Systems and Information Technology, 4(1):34--48, 2017.

[4]

Proper storage temperatures for usda commodities. https://www.cde.ca.gov/ls/nu/fd/mb00404.asp, 2021.

[5]

CK Chau, EY Tu, D W T Chan, and J Burnett. Estimating the total exposure to air pollutants for different population age groups in hong kong. Environment international, 27(8):617--630, March 2002.

[6]

Klepeis NE, Nelson WC, Ott WR, Robinson JP, Tsang AM, Switzer P, Behar JV, Hern SC, and Engelmann WH. National Human Activity Pattern Survey (NHAPS): A resource for assessing exposure to environmental pollutants. J Expo Anal Environ Epidemiol, 11(3):231--252, 2001.

[7]

Catalin Teodosiu, Raluca Hohota, Gilles Rusaouën, and Monika Woloszyn. Numerical prediction of indoor air humidity and its effect on indoor environment. Building and Environment, 38(5):655--664, 2003.

[8]

Air conditioning use emerges as one of the key drivers of global electricity-demand growth. https://www.iea.org/news/air-conditioning-use-emerges-as-one-of-the-key-drivers-of-global-electricity-demand-growth, 2018.

[9]

Roberto Z. Freire, Gustavo H.C. Oliveira, and Nathan Mendes. Predictive controllers for thermal comfort optimization and energy savings. Energy and Buildings, 40(7):1353--1365, 2008.

[10]

Siyu Wu and Jian-Qiao Sun. A physics-based linear parametric model of room temperature in office buildings. Building and Environment, 50:1--9, 2012.

[11]

FLIR E5-XT infraed camera. https://www.flir.com/products/e5-xt/, 2015.

[12]

Chao Cai, Zhe Chen, Henglin Pu, Liyuan Ye, Menglan Hu, and Jun Luo. AcuTe: Acoustic thermometer empowered by a single smartphone. In Proceedings of ACM SenSys, 2020.

[13]

Xingyu Chen, Jia Liu, Fu Xiao, Shigang Chen, and Lijun Chen. Thermotag: Item-level temperature sensing with a passive rfid tag. In Proceedings of ACM MobiSys, 2021.

[14]

Swadhin Pradhan and Lili Qiu. Rtsense: Passive rfid based temperature sensing. In Proceedings of ACM SenSys, 2020.

[15]

Baicheng Chen, Huining Li, Zhengxiong Li, Xingyu Chen, Chenhan Xu, and Wenyao Xu. Thermowave: A new paradigm of wireless passive temperature monitoring via mmwave sensing. In Proceedings of ACM MobiCom, 2020.

[16]

Gengsheng Lawrence Zeng. Medical image reconstruction: a conceptual tutorial. Springer, 2010.

[17]

Grand View Research. Automotive Electronics Market Size, Share & Trends Analysis Report By Component (Electronic Control Unit, Sensors, Current Carrying Devices), By Application, By Sales Channel, By Region, And Segment Forecasts, 2021 - 2028. Grand View Research, San Francisco, CA, 2021.

[18]

Mordor Intelligence. Automotive Wiring Harness Market - Growth, Trends, COVID-19 Impact, and Forecasts (2022 - 2027). Mordor Intelligence, Hyderabad, Telangana, India, 2021.

[19]

Arman Shehabi, Dale Sartor Sarah Smith, Richard Brown, Magnus Herrlin, Jonathan Koomey, Eric Masanet, Nathaniel Horner, Inês Azevedo, and William Lintner. United States Data Center Energy Usage Report. Lawrence Berkeley National Lab (LBNL), Berkeley, CA, 2016.

[20]

Infocomm Media Development Authority. Singapore announces a proof-of-concept for the world's first Tropical Data Centre (TDC). https://www.imda.gov.sg/news-and-events/impact-news/2016/06/tropical-revolution-for-data-centres, 2013.

[21]

Rongrong Wang, Duc Van Le, Rui Tan, Yew-Wah Wong, and Yonggang Wen. Real-time cooling power attribution for co-located data center rooms with distinct temperatures. In Proceedings of ACM BuildSys, 2020.

Digital Library

[22]

Victor-Alexandru Pădurean, Andrei-Alexandru Cristea, and Marcel Antal. Heat reuse models for liquid cooled data centers integrated with district heating. In Proceedings of ACM BuildSys, 2021.

Digital Library

[23]

Marcel Antal, Tudor Cioara, Ionut Anghel, Claudia Antal, and loan Salomie. Flexibility management of data centers to provide energy services in the smart grid. In Proceedings of ACM e-Energy, 2021.

Digital Library

[24]

Optimize airflow and hvac for data center. https://www.energystar.gov/products/data_centers/optimize_airflow_hvac, 2022.

[25]

Eronini I. Umez-Eronini. System Dynamics and Control. CL-Engineering, first edition edition, 1998.

[26]

Joe Brown, Jonathan Chambers, Alessandro Abate, and Alex Rogers. Smite: Using smart meters to infer the thermal efficiency of residential homes. In Proceedings of ACM BuildSys, 2020.

Digital Library

[27]

Jonathan D. Chambers and Tadj Oreszczyn. Deconstruct: A scalable method of as-built heat power loss coefficient inference for uk dwellings using smart meter data. Energy and Buildings, 183:443--453, 2019.

[28]

Google nest thermostat. https://www.nest-thermostat.com/, 2022.

[29]

Nadine von Frankenberg, Vivian Loftness, and Bernd Bruegge. I want it that way: Thermal desirability in shared spaces. In Proceedings of ACM BuildSys, 2021.

Digital Library

[30]

Elvin Vindel, Mario Bergés, Burcu Akinci, and Olga Kavvada. Demand flexibility potential model for multi-zone commercial buildings using internal hvac system states. In Proceedings of ACM BuildSys, 2021.

Digital Library

[31]

Srinarayana Nagarathinam, Arunchandar Vasan, Venkatesh Sarangan, Rajesh Jayaprakash, and Anand Sivasubramaniam. Good set-points make good neighbors: User seating and temperature control in uberized workspaces. In Proceedings of ACM BuildSys, 2018.

Digital Library

[32]

Lawrence E Kinsler, Austin R Frey, Alan B Coppens, and James V Sanders. Fundamentals of Acoustics. Wiley, fourth edition edition, 2000.

[33]

Anran Wang and Shyamnath Gollakota. MilliSonic: Pushing the limits of acoustic motion tracking. In Proceedings of ACM CHI, 2019.

[34]

International Electrotechnical Commission. Digital audio interface - part1: General. IEC 60958-1, 2014.

[35]

Wenguang Mao, Jian He, and Lili Qiu. CAT: High-precision acoustic motion tracking. In Proceedings of ACM MobiCom, 2016.

Digital Library

[36]

Sangki Yun, Yi-Chao Chen, and Lili Qiu. Turning a mobile device into a mouse in the air. In Proceedings of ACM MobiSys, 2015.

Digital Library

[37]

Branislav M Popovic. Generalized chirp-like polyphase sequences with optimum correlation properties. IEEE Transactions on Information Theory, 38(4):1406--1409, 1992.

Digital Library

[38]

Ke Sun, Ting Zhao, Wei Wang, and Lei Xie. VSkin: Sensing touch gestures on surfaces of mobile devices using acoustic signals. In Proceedings of ACM MobiCom, 2018.

[39]

Chunyi Peng, Guobin Shen, Yongguang Zhang, Yanlin Li, and Kun Tan. BeepBeep: A high accuracy acoustic ranging system using COTS mobile devices. In Proceedings of ACM SenSys, 2007.

Digital Library

[40]

Wenguang Mao, Mei Wang, Wei Sun, Lili Qiu, Swadhin Pradhan, and Yi-Chao Chen. Rnn-based room scale hand motion tracking. In Proceedings of ACM MobiCom, 2019.

Digital Library

[41]

Wenguang Mao, Wei Sun, Mei Wang, and Lili Qiu. Deeprange: Acoustic ranging via deep learning. Proceedings of ACM IMWUT, 2020.

[42]

Bosch. BME280 combined humidity, pressure and temperature sensor, 2018.

[43]

Noah Klugman, Meghan Clark, Pat Pannuto, and Prabal Dutta. Android resists liberation from its primary use case. In Proceedings of ACM MobiCom, 2018.

Digital Library

[44]

Dario Camuffo and Chiara Bertolin. The earliest spirit-in-glass thermometer and a comparison between the earliest cet and italian observations. Weather, 67(8):206--209, 2012.

[45]

Xun Gong, Xiaohe Tang, Yanjie Li, Minmin You Zude Lin, and Jingquan Liu. Investigation the minimum measurement points for calibration a high precision ntc thermistors in cryogenic field. In Proceedings of IEEE NEMS, pages 1088-1091, 2021.

[46]

R. Walker. Recent advances in resistance thermometry readouts. In NCSL International Workshop and Symposium, 2010.

[47]

R. Denos and C. H Sieverding. Assessment of the Cold-Wire Resistance Thermometer for High-Speed Turbomachinery Applications. Journal of Turbomachinery, 119(1):140--148, 01 1997.

[48]

Tetsuya Jitsufuchi. Thermal infrared surveys for mapping surface temperature and sulfur dioxide plumes at sakurajima volcano (minamidake a-crater, showa crater) using the airborne hyperspectral scanner. In Proceedings of IEEE IGARSS, pages 715-718, 2013.

[49]

Jingshuo Yang. Flexible temperature sensor based on pdms/cnt/ti3c2tx for physiological temperature monitoring. In Proceedings of ACM ISAIMS, 2021.

Digital Library

[50]

Michele Caselli, Marco Ronchi, and Andrea Boni. An integrated low power temperature sensor for food monitoring applications. In Proceedings of IEEE ISCAS, 2021.

[51]

Joseph Breda, Amee Trivedi, Chulabhaya Wijesundara, Phuthipong Bovornkeeratiroj, David Irwin, Prashant Shenoy, and Jay Taneja. Hot or not: Leveraging mobile devices for ubiquitous temperature sensing. In Proceedings of ACM BuildSys, 2019.

Digital Library

[52]

Ning Wang and Jia-Yang Li. Efficient multi-channel thermal monitoring and temperature prediction based on improved linear regression. IEEE Transactions on Instrumentation and Measurement, 71:1--9, 2022.

[53]

Sibo Xia, Xinyuan Nan, Xin Cai, and Xumeng Lu. Data fusion based wireless temperature monitoring system applied to intelligent greenhouse. Computers and Electronics in Agriculture, 192:106576, 2022.

Digital Library

[54]

Desenclos JC Bitar D, Goubar A. International travels and fever screening during epidemics: a literature review on the effectiveness and potential use of non-contact infrared thermometers. Euro Surveill, 1(1):21, 02 2009.

[55]

Shelley N Facente, Lauren A Hunter, Laura J Packel, Yi Li, Anna Harte, Guy Nicolette, Shana McDevitt, Maya Petersen, and Arthur L Reingold. Feasibility and effectiveness of daily temperature screening to detect COVID-19 in a prospective cohort at a large public university. BMC Public Health, 1(1):21, 09 2021.

[56]

Racha Benarrait, Frederic Lamarque, Jeremy Terrien, Hani Al Hajjar, Muneeb Ullah Khan, and Andreas Dietzel. Optical power supply of a wireless temperature sensor for rotating machines monitoring purpose. In Proceedings of IEEE I2MTC, pages 1-6, 2021.

Digital Library

[57]

Ashrant Aryal and Burcin Becerik-Gerber. Skin temperature extraction using facial landmark detection and thermal imaging for comfort assessment. In Proceedings of ACM BuildSys, 2019.

Digital Library

[58]

Pandarasamy Arjunan, Gregory Dobler, Kyungmin Lee, Clayton Miller, Filip Biljecki, and Kameshwar Poolla. Operational characteristics of residential air conditioners with temporally granular remote thermographic imaging. In Proceedings of ACM BuildSys, 2021.

Digital Library

[59]

A. Vaz, A. Ubarretxena, I. Zalbide, D. Pardo, H. Solar, A. Garcia-Alonso, and R. Berenguer. Full passive uhf tag with a temperature sensor suitable for human body temperature monitoring. IEEE Transactions on Circuits and Systems II: Express Briefs, 57(2):95--99, 2010.

Digital Library

[60]

Jun Yin, Jun Yi, Man Kay Law, Yunxiao Ling, Man Chiu Lee, Kwok Ping Ng, Bo Gao, Howard Cam Luong, Amine Bermak, Mansun Chan, Wing-Hung Ki, Chi-Ying Tsui, and Matthew Ming-Fai Yuen. A system-on-chip epc gen-2 passive uhf rfid tag with embedded temperature sensor. In Proceedings of IEEE ISSCC, pages 308-309, 2010.

[61]

Vincent Ha and Ani Nahapetian. Received wifi signal strength monitoring for contactless body temperature classification. In Body Area Networks. Smart IoT and Big Data for Intelligent Health Management, pages 112-125. Springer International Publishing, 2022.

[62]

Chao Cai, Henglin Pu, Menglan Hu, Rong Zheng, and Jun Luo. SST: Software sonic thermometer on acoustic-enabled IoT devices. IEEE Transactions on Mobile Computing, 2020.

[63]

Lawrence Yule, Bahareh Zaghari, Nicholas Harris, and Martyn Hill. Modelling and validation of a guided acoustic wave temperature monitoring system. Sensors, 21(21), 2021.

[64]

Fusang Zhang, Kai Niu, Xiaolai Fu, and Beihong Jin. Acousticthermo: Temperature monitoring using acoustic pulse signal. In Proceedings of IEEE MSN, 2020.

[65]

Wen-Yuan Tsai, Hsin-Chieh Chen, and Teh-Lu Liao. High accuracy ultrasonic air temperature measurement using multi-frequency continuous wave. Sensors and Actuators A: Physical, 132(2):526--532, 2006.

[66]

YS Huang and Ming-Shing Young. An accurate ultrasonic distance measurement system with self temperature compensation. Instrumentation Science and Technology, 37(1):124--133, 2009.

[67]

Xuehua Shen, Qingyu Xiong, Xin Shi, Kai Wang, Shan Liang, and Min Gao. Ultrasonic temperature distribution reconstruction for circular area based on markov radial basis approximation and singular value decomposition. Ultrasonics, 62:174--185, 2015.

[68]

Ruixi Jia, Qingyu Xiong, Guangyu Xu, Kai Wang, and Shan Liang. A method for two-dimensional temperature field distribution reconstruction. Applied Thermal Engineering, 111:961--967, 2017.

[69]

Rajalakshmi Nandakumar, Vikram Iyer, Desney Tan, and Shyamnath Gollakota. FingerIO: Using active sonar for fine-grained finger tracking. In Proceedings of ACM CHI, 2016.

[70]

Wenjie Ruan, Quan Z Sheng, Lei Yang, Tao Gu, Peipei Xu, and Longfei Shangguan. AudioGest: Enabling fine-grained hand gesture detection by decoding echo signal. In Proceedings of ACM Ubicomp, 2016.

[71]

Ke Sun, Wei Wang, Alex X. Liu, and Haipeng Dai. Depth aware finger tapping on virutal displays. In Proceedings of ACM MobiSys, 2018.

Digital Library

[72]

Rajalakshmi Nandakumar, Shyamnath Gollakota, and Nathaniel Watson. Contactless sleep apnea detection on smartphones. In Proceedings of ACM MobiSys, 2015.

Digital Library

[73]

Tianben Wang, Daqing Zhang, Yuanqing Zheng, Tao Gu, Xingshe Zhou, and Bernadette Dorizzi. C-FMCW based contactless respiration detection using acoustic signal. In Proceedings of ACM UbiComp, 2018.

Digital Library

[74]

Anran Wang, Jacob E Sunshine, and Shyamnath Gollakota. Contactless infant monitoring using white noise. In Proceedings of ACM MobiCom, 2019.

Digital Library

[75]

Bing Zhou, Mohammed Elbadry, Ruipeng Gao, and Fan Ye. BatMapper: Acoustic sensing based indoor floor plan construction using smartphones. In Proceedings of ACM MobiSys, 2017.

[76]

Yu-Chih Tung and Kang G Shin. Echotag: Accurate infrastructure-free indoor location tagging with smartphones. In Proceedings of ACM MobiCom, 2015.

[77]

Cheng Zhang, Qiuyue Xue, Anandghan Waghmare, Sumeet Jain, Yiming Pu, Sinan Hersek, Kent Lyons, Kenneth A Cunefare, Omer T Inan, and Gregory D Abowd. Soundtrak: Continuous 3D tracking of a finger using active acoustics. In Proceedings of ACM UbiComp, 2017.

[78]

Zengbin Zhang, David Chu, Xiaomeng Chen, and Thomas Moscibroda. Swordfight: Enabling a new class of phone-to-phone action games on commodity phones. In Proceedings of ACM MobiSys, 2012.

[79]

Yunting Zhang, Jiliang Wang, Weiyi Wang, Zhao Wang, and Yunhao Liu. Vernier: Accurate and fast acoustic motion tracking using mobile devices. In Proceedings of IEEE INFOCOM, 2018.

Digital Library

[80]

Gaoshuai Cao, Kuang Yuan, Jie Xiong, Panlong Yang, Yubo Yan, Hao Zhou, and Xiang-Yang Li. Earphonetrack: Involving earphones into the ecosystem of acoustic motion tracking. In Proceedings of ACM SenSys, 2020.

Cited By

Pang MLi KWang XWang WCheng WLiu DYin YChen P(2024)DEWS: A Distributed Measurement Scheme for Efficient Wireless SensingProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36997288:4(1-34)Online publication date: 21-Nov-2024
https://dl.acm.org/doi/10.1145/3699728
Wang SWang XJiang WMiao CCao QWang HSun KXue HSu L(2024)Towards Smartphone-based 3D Hand Pose Reconstruction Using Acoustic SignalsACM Transactions on Sensor Networks10.1145/367712220:5(1-32)Online publication date: 26-Aug-2024
https://dl.acm.org/doi/10.1145/3677122
Dai CZhou WGui LCao HGarg SXiao F(2024)Acoustic Sensing for Fitness Activities Recognition: A Deep Learning ApproachIEEE INFOCOM 2024 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)10.1109/INFOCOMWKSHPS61880.2024.10620762(1-6)Online publication date: 20-May-2024
https://doi.org/10.1109/INFOCOMWKSHPS61880.2024.10620762
Show More Cited By

Index Terms

VECTOR: Velocity Based Temperature-field Monitoring with Distributed Acoustic Devices
1. Human-centered computing
  1. Ubiquitous and mobile computing
    1. Ubiquitous and mobile computing systems and tools

Recommendations

Industrial IoT Enabled Fuzzy Logic Based Flame Image Processing for Rotary Kiln Control
Abstract
In the cement industry, a rotary kiln is a pyro-processing device that is used to measure temperature. Measuring and maintaining a certain range of temperature in the rotary kiln is important to ensure the production of quality clinker granules. ...
In-ear thermometer: wearable real-time core body temperature monitoring: poster abstract
SenSys '20: Proceedings of the 18th Conference on Embedded Networked Sensor Systems

Core body temperature is an important indicator of medical treatment. Sudden changes in core body temperature can be a precursor to neurodegenerative diseases such as Parkinson's disease. These diseases have the potential to strike at any time, ...
Temperature Monitoring System Based on Hadoop and VLC

This paper presents a temperature monitoring system based on Hadoop and visible light communication (VLC). The system includes two parts: temperature acquisition and temperature monitoring. Temperature acquisition section uses visible light ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

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 6, Issue 3

September 2022

1612 pages

EISSN:2474-9567

DOI:10.1145/3563014

Issue’s Table of Contents

Copyright © 2022 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: 07 September 2022

Published in IMWUT Volume 6, Issue 3

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article
Research
Refereed

Funding Sources

National Natural Science Foundation of China
Natural Science Foundation of Jiangsu Province of China

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

10
Total Citations
View Citations
501
Total Downloads

Downloads (Last 12 months)182
Downloads (Last 6 weeks)34

Reflects downloads up to 23 Nov 2024

Other Metrics

View Author Metrics

Citations

Cited By

Pang MLi KWang XWang WCheng WLiu DYin YChen P(2024)DEWS: A Distributed Measurement Scheme for Efficient Wireless SensingProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36997288:4(1-34)Online publication date: 21-Nov-2024
https://dl.acm.org/doi/10.1145/3699728
Wang SWang XJiang WMiao CCao QWang HSun KXue HSu L(2024)Towards Smartphone-based 3D Hand Pose Reconstruction Using Acoustic SignalsACM Transactions on Sensor Networks10.1145/367712220:5(1-32)Online publication date: 26-Aug-2024
https://dl.acm.org/doi/10.1145/3677122
Dai CZhou WGui LCao HGarg SXiao F(2024)Acoustic Sensing for Fitness Activities Recognition: A Deep Learning ApproachIEEE INFOCOM 2024 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)10.1109/INFOCOMWKSHPS61880.2024.10620762(1-6)Online publication date: 20-May-2024
https://doi.org/10.1109/INFOCOMWKSHPS61880.2024.10620762
Wei ZChen WZhang YLian BZhao J(2024)CIU-LPervasive and Mobile Computing10.1016/j.pmcj.2024.101947103:COnline publication date: 1-Oct-2024
https://dl.acm.org/doi/10.1016/j.pmcj.2024.101947
Wei ZChen WTao WNing SLian BSun XZhao J(2024)CATFSIDComputer Communications10.1016/j.comcom.2024.06.014224:C(275-284)Online publication date: 1-Aug-2024
https://dl.acm.org/doi/10.1016/j.comcom.2024.06.014
Wan HShi SCao WWang WChen G(2023)Multi-User Room-Scale Respiration Tracking Using COTS Acoustic DevicesACM Transactions on Sensor Networks10.1145/359422019:4(1-28)Online publication date: 9-Jun-2023
https://dl.acm.org/doi/10.1145/3594220
Wang LWang WDai HLiu S(2023)MagSoundProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/35808897:1(1-32)Online publication date: 28-Mar-2023
https://dl.acm.org/doi/10.1145/3580889
Chhaglani BAcer UJang SKawsar FMin C(2023)CocoonProceedings of the 24th International Workshop on Mobile Computing Systems and Applications10.1145/3572864.3580340(89-95)Online publication date: 22-Feb-2023
https://dl.acm.org/doi/10.1145/3572864.3580340
Cao SLi DLee SXiong JCosta XAl Hassanieh HAsadi ACox LPerino DWidmer JGiustiniano D(2023)PowerPhone: Unleashing the Acoustic Sensing Capability of SmartphonesProceedings of the 29th Annual International Conference on Mobile Computing and Networking10.1145/3570361.3613270(1-16)Online publication date: 2-Oct-2023
https://dl.acm.org/doi/10.1145/3570361.3613270
Chen XLi DChen YXiong J(2022)Boosting the sensing granularity of acoustic signals by exploiting hardware non-linearityProceedings of the 21st ACM Workshop on Hot Topics in Networks10.1145/3563766.3564091(53-59)Online publication date: 14-Nov-2022
https://dl.acm.org/doi/10.1145/3563766.3564091

View Options

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