Article

The design and implementation of a self-calibrating distributed acoustic sensing platform

Authors:

Deborah EstrinAuthors Info & Claims

SenSys '06: Proceedings of the 4th international conference on Embedded networked sensor systems

Pages 71 - 84

https://doi.org/10.1145/1182807.1182815

Published: 31 October 2006 Publication History

Abstract

We present the design, implementation, and evaluation of the Acoustic Embedded Networked Sensing Box (ENSBox), a platform for prototyping rapid-deployable distributed acoustic sensing systems, particularly distributed source localization. Each ENSBox integrates an ARM processor running Linux and supports key facilities required for source localization: a sensor array, wireless network services, time synchronization, and precise self-calibration of array position and orientation. The ENSBox's integrated, high precision self-calibration facility sets it apart from other platforms. This self-calibration is precise enough to support acoustic source localization applications in complex, realistic environments: e.g., 5 cm average 2D position error and 1.5 degree average orientation error over a partially obstructed 80x50 m outdoor area. Further, our integration of array orientation into the position estimation algorithm is a novel extension of traditional multilateration techniques. We present the result of several different test deployments, measuring the performance of the system in urban settings, as well as forested, hilly environments with obstructing foliage and 20-30 m distances between neighboring nodes.

References

[1]

A. Arora et al. A line in the sand: A wireless sensor network for target detection, classification and tracking. Computer Networks, 46(5):605--634, Dec. 2004.]]

Digital Library

[2]

A. Arora et al. Exscal: Elements of an extreme scale wireless sensor network. In IEEE RTCSA. IEEE, 2005.]]

Digital Library

[3]

S. Azou, C. Pistre, and G. Burel. A chaotic direct sequence spread-spectrum system for underwater communication. In Proceedings of the IEEE Oceans Conf., Biloxi, Mississippi, Oct. 2002.]]

[4]

P. Bergamo et al. Collaborative sensor networking towards real-time acoustical beamforming in free-space and limited reverberence. IEEE Transactions on Mobile Computing, 3(3):211--224, July-September 2004.]]

Digital Library

[5]

J. Bicket, D. Aguayo, S. Biswas, and R. Morris. Architecture and evaluation of an unplanned 802.11b mesh network. In MobiCom '05), August 2005.]]

Digital Library

[6]

K. Chintalapudi, R. Govindan, G. Sukhatme, and A. Dhariwal. Ad-hoc localization using ranging and sectoring. In IEEE INFOCOM, 2004.]]

[7]

I.L. Dryden and K.V. Mardia. Statistical Shape Analysis. John Wiley and Sons, 1998.]]

[8]

J. Elson, L. Girod, and D. Estrin. Fine-grained network time synchronization using reference broadcasts. In OSDI, pages 147--163, Boston, MA, December 2002.]]

Digital Library

[9]

J. Elson and K. Romer. Wireless sensor networks: A new regime for time synchronization. In First Workshop on Hot Topics in Networks (HotNets-I), 2002.]]

[10]

L. Girod. A Self-Calibrating System of Distributed Acoustic Arrays. PhD thesis, Univerity of Caliornia at Los Angeles, 2005.]]

Digital Library

[11]

L. Girod, V. Bychkovskiy, J. Elson, and D. Estrin. Locating tiny sensors in time and space: A case study. In in Proceedings of ICCD 2002 (invited paper), Freiburg, Germany, September 2002.]]

Digital Library

[12]

L. Girod., J. Elson, A. Cerpa, T. Stathopoulos, N. Ramanathan, and D. Estrin. Emstar: a software environment for developing and deploying wireless sensor networks. In USENIX, 2004.]]

Digital Library

[13]

L. Girod and D. Estrin. Robust range estimation using acoustic and multimodal sensing. In IROS, Oct. 2001.]]

[14]

L. Girod et al. A reliable multicast mechanism for sensor network applications. in CENS Technical Report 48, 2005.]]

[15]

B. Greenstein et al. Collecting high-rate data over low-rate sensor network radios. Technical Report 05-55, CENS, 2005.]]

[16]

J. Hill and D. Culler. Mica: A wireless platform for deeply embedded networks. IEEE Micro, 22(6):12--24, Nov/Dec 2002.]]

Digital Library

[17]

X. Ji and H. Zha. Sensor positioning in wireless ad-hoc networks with multidimensional scaling. In IEEE INFOCOM, 2004.]]

[18]

M. Kushwaha, K. Molnár, J. Sallai, P. Völgyesi, M. Maróti, and A. Lédeczi. Sensor node localization using mobile acoustic beacons. In The 2nd IEEE International Conference on Mobile Ad-hoc and Sensor Systems (MASS 2005), 2005.]]

[19]

B. Kusy, P. Dutta, P. Levis, M. Mar, A. Ledeczi, and D. Culler. Elapsed time on arrival: A simple and versatile primitive for canonical time synchronization services, in press, 2006.]]

[20]

Y. Kwon, K. Mechitov, S. Sundresh, W. Kim, and G. Agha. Resilient localization for sensor networks in outdoor environments. In IEEE ICDCS, 2005.]]

Digital Library

[21]

K. Langendoen and N. Reijers. Distributed localization in wireless sensor networks: a quantitative comparison. Computer Networks, special issue on Wireless Sensor Networks, 2003.]]

Digital Library

[22]

A. Ledeczi et al. Countersniper system for urban warfare. ACM Transactions on Sensor Networks, (2):153--177, Nov. 2005.]]

Digital Library

[23]

M. Maroti, P. Volgyesi, S. Dora, B. Kusy, A. Nadas, A. Ledeczi, G. Balogh, and K. Molnar. Radio interfermetric geolocation. In ACM SenSys. ACM, Nov. 2005.]]

Digital Library

[24]

W. Merrill, L. Girod, J. Elson, K. Sohrabi, F. Newberg, and W. Kaiser. Autonomous position location in distributed, embedded, wireless systems. In the IEEE CAS Workshop on Wireless Comm. and Networking, Pasadena, CA, 2002.]]

[25]

W. Merrill, L. Girod, B. Schiffer, D. McIntire, G. Rava, K. Sohrabi, F. Newberg, J. Elson, and W. Kaiser. Dynamic networking and smart sensing enable next-generation landmines. IEEE Pervasive Computing Magazine, Oct-Dec 2004.]]

Digital Library

[26]

W.M. Merrill, K. Sohrabi, L. Girod, J. Elson, F. Newberg, and W. Kaiser. Open standard development platforms for distributed sensor networks. In SPIE Unattended Ground Sensor Technologies and Applications IV, pages 327--337, 2002.]]

[27]

D.L. Mills. Internet Time Synchronization: The Network Time Protocol. In Z. Yang and T.A. Marsland, editors, Global States and Time in Distributed Systems. IEEE Computer Society Press, 1994.]]

[28]

J. Polastre, C. Sharp, and R. Szewczyk. http://www.moteiv.com.]]

[29]

N. Priyantha, A. Chakraborty, and H. Balakrishnan. The cricket location support system. In ACM MobiCom. ACM, Aug. 2000.]]

Digital Library

[30]

N.B. Priyantha, A.K.L. Miu, H. Balakrishnan, and S. Teller. The cricket compass for context-aware mobile applicaitons. In ACM MobiCom, 2001.]]

Digital Library

[31]

V.C. Raykar and R. Duraiswami. Automatic position calibration of multiple microphones. In IEEE ICASSP04. IEEE, 2004.]]

[32]

J. Sallai, G. Balogh, M. Maroti, A. Ledeczi, and B. Kusy. Acoustic ranging in resource-constrained sensor networks. In ICWN '04, June 2004.]]

[33]

A. Savvides, L. Girod, M. Srivastava, and D. Estrin. Localization in sensor networks. In C.S. Raghavendra, K.M. Sivalingam, and T. Znati, editors, Wireless Sensor Networks. Kluwer, 2004.]]

Digital Library

[34]

A. Savvides, C.-C. Han, and M.B. Strivastava. Dynamic fine-grained localization in ad-hoc networks of sensors. In ACM MobiCom, pages 166--179, New York, NY, USA, 2001. ACM.]]

Digital Library

[35]

A. Savvides, H. Park, and M.B. Srivastava. The n-hop multilateration primitive for node localization problems. MONET Special Issue on Sensor Networks and Applications, 2003.]]

Digital Library

[36]

W. Torgerson. Multidimensional scaling: I. theory and method. Psychometrika, 17:401--419, 1952.]]

[37]

H. Wang et al. Acoustic sensor networks for woodpecker localization. In SPIE Conference on Advanced Signal Processing Algorithms, Architectures and Implementations, Aug. 2005.]]

[38]

H. Wang, L. Yip, D. Maniezzo, J. Chen, R. Hudson, J. Elson, and K. Yao. A wireless time-synchronized cots sensor platform, part ii: Applications to beam-forming. In IEEE CAS Workshop on Wireless Communications and Networking, 2002.]]

[39]

A. Ward, A. Jones, and A. Hopper. A new location technique for the active office. IEEE Personal Communications, 4(5), Oct. 1997.]]

[40]

K. Yao, R. Hudson, C. Reed, D. Chen, and F. Lorenzelli. Blind beamforming on a randomly distributed sensor array system. IEEE JSAC, 16(8), Oct. 1998.]]

Cited By

Sakagami YIkeda TTsuji T(2024)Seismic reflection profile derived from the natural earthquakes recorded with seafloor DAS data海底DASデータに含まれる自然地震記録を用いた反射面図の構築BUTSURI-TANSA(Geophysical Exploration)10.3124/segj.77.4077(40-48)Online publication date: 2024
https://doi.org/10.3124/segj.77.40
Bahle GFortes Rey VBian SBello HLukowicz P(2021)Using Privacy Respecting Sound Analysis to Improve Bluetooth Based Proximity Detection for COVID-19 Exposure Tracing and Social DistancingSensors10.3390/s2116560421:16(5604)Online publication date: 20-Aug-2021
https://doi.org/10.3390/s21165604
Ji CChen MSun PShu HWang Z(2020)An encoding and decoding scheme for long-distance ultrasonic localization2020 39th Chinese Control Conference (CCC)10.23919/CCC50068.2020.9188875(5247-5252)Online publication date: Jul-2020
https://doi.org/10.23919/CCC50068.2020.9188875
Show More Cited By

Index Terms

The design and implementation of a self-calibrating distributed acoustic sensing platform
1. Hardware
  1. Communication hardware, interfaces and storage
    1. Signal processing systems

Recommendations

A self-calibrating distributed acoustic sensing platform
SenSys '06: Proceedings of the 4th international conference on Embedded networked sensor systems

We will demonstrate the operation of the Acoustic Embedded Networked Sensing Box (ENSBox), a platform for prototyping rapid-deployable distributed acoustic sensing systems. The ENSBox is a Linux-based acoustic sensing system with and integrated, high ...
Research on the Self-localization of Wireless Sensor Networks
ICESS '08: Proceedings of the 2008 International Conference on Embedded Software and Systems

Self-localization is a key function in Wireless Sensor Networks (WSNs). Many applications and internal mechanisms require nodes to know their location. Based on two different application environments and from the view of anchor nodes density, this paper ...
Self-Localization of IoT Devices Using Noisy Anchor Positions and RSSI Measurements
Abstract
Location-enabled Internet of things (IoT) has attracted much attention from the scientific and industrial communities given its high relevance in application domains such as agriculture, wildlife management, and infectious disease control. The ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Conferences

SenSys '06: Proceedings of the 4th international conference on Embedded networked sensor systems

October 2006

444 pages

ISBN:1595933433

DOI:10.1145/1182807

General Chair:
Andrew Campbell
Dartmouth University
,
Program Chairs:
Philippe Bonnet
University of Copenhagen (DIKU), Denmark
,
John Heidemann
University of Southern California/ISI, USA

Copyright © 2006 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]

Sponsors

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 31 October 2006

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Article

Conference

SenSys06

Sponsor:

SenSys06: ACM Conference on Embedded Network Sensor Systems

October 31 - November 3, 2006

Colorado, Boulder, USA

Acceptance Rates

Overall Acceptance Rate 174 of 867 submissions, 20%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

127
Total Citations
View Citations
1,490
Total Downloads

Downloads (Last 12 months)81
Downloads (Last 6 weeks)15

Reflects downloads up to 13 Nov 2024

Other Metrics

View Author Metrics

Citations

Cited By

Sakagami YIkeda TTsuji T(2024)Seismic reflection profile derived from the natural earthquakes recorded with seafloor DAS data海底DASデータに含まれる自然地震記録を用いた反射面図の構築BUTSURI-TANSA(Geophysical Exploration)10.3124/segj.77.4077(40-48)Online publication date: 2024
https://doi.org/10.3124/segj.77.40
Bahle GFortes Rey VBian SBello HLukowicz P(2021)Using Privacy Respecting Sound Analysis to Improve Bluetooth Based Proximity Detection for COVID-19 Exposure Tracing and Social DistancingSensors10.3390/s2116560421:16(5604)Online publication date: 20-Aug-2021
https://doi.org/10.3390/s21165604
Ji CChen MSun PShu HWang Z(2020)An encoding and decoding scheme for long-distance ultrasonic localization2020 39th Chinese Control Conference (CCC)10.23919/CCC50068.2020.9188875(5247-5252)Online publication date: Jul-2020
https://doi.org/10.23919/CCC50068.2020.9188875
Liu MCheng LQian KWang JWang JLiu Y(2020)Indoor acoustic localization: a surveyHuman-centric Computing and Information Sciences10.1186/s13673-019-0207-410:1Online publication date: 6-Jan-2020
https://doi.org/10.1186/s13673-019-0207-4
Ceolini EKiselev ILiu S(2020)Evaluating Multi-Channel Multi-Device Speech Separation Algorithms in the Wild: A Hardware-Software SolutionIEEE/ACM Transactions on Audio, Speech and Language Processing10.1109/TASLP.2020.298954528(1428-1439)Online publication date: 21-May-2020
https://dl.acm.org/doi/10.1109/TASLP.2020.2989545
Sharma NGupta V(2020)Meta-heuristic based optimization of WSNs Localisation Problem- a SurveyProcedia Computer Science10.1016/j.procs.2020.06.006173(36-45)Online publication date: 2020
https://doi.org/10.1016/j.procs.2020.06.006
Bai YLu LCheng JLiu JChen YYu J(2020)Acoustic-based sensing and applications: A surveyComputer Networks10.1016/j.comnet.2020.107447181(107447)Online publication date: Nov-2020
https://doi.org/10.1016/j.comnet.2020.107447
Rhinehart TChronister LDevlin TKitzes J(2020)Acoustic localization of terrestrial wildlife: Current practices and future opportunitiesEcology and Evolution10.1002/ece3.621610:13(6794-6818)Online publication date: 13-Jun-2020
https://doi.org/10.1002/ece3.6216
Galangque CGuirnaldo S(2019)Gunshot Classification and Localization System using Artificial Neural Network (ANN)2019 12th International Conference on Information & Communication Technology and System (ICTS)10.1109/ICTS.2019.8850937(1-5)Online publication date: Jul-2019
https://doi.org/10.1109/ICTS.2019.8850937
Adkins JGhena BJackson NPannuto PRohrer SCampbell BDutta PMottola LGao JZhang P(2018)The signpost platform for city-scale sensingProceedings of the 17th ACM/IEEE International Conference on Information Processing in Sensor Networks10.1109/IPSN.2018.00047(188-199)Online publication date: 11-Apr-2018
https://dl.acm.org/doi/10.1109/IPSN.2018.00047
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 Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Media

Figures

Other

Tables

View Table of Contents