Skip to main content

Design and Evaluation of a Sound Based Water Flow Measurement System

  • Conference paper
Smart Sensing and Context (EuroSSC 2008)

Part of the book series: Lecture Notes in Computer Science ((LNCCN,volume 5279))

Included in the following conference series:

Abstract

This paper presents a low-cost, easy to install sound-based system for water usage monitoring in a household environment. It extends the state of the art but not only detecting that water is flowing in a pipe, but also quantifying the flow thus allowing us to compute the amount of water used. We describe the system architecture including hardware, software and the signal processing and pattern recognition algorithms used. We present an extensive evaluation in a real life noisy kitchen environment. We show an accuracy of over 90 percent on classifying six different water flow levels. We also demonstrate good performance measuring water consumption when compared with the home’s water meter.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Bauer, G., Lukowicz, P.: Developing a Sub Room Level Indoor Location System for Wide Scale Deployment in Assisted Living Systems. In: Miesenberger, K., Klaus, J., Fagler, W.L., Karshmer, A.I. (eds.) ICCHP 2008. LNCS, vol. 5105, pp. 1057–1064. Springer, Heidelberg (2008)

    Google Scholar 

  2. Stäger, M., Lukowicz, P., Tröster, G.: Power and accuracy trade-offs in sound-based context recognition systems. Pervasive and Mobile Computing, vol. 3, pp. 300–327. Elsevier, Amsterdam (2007)

    Google Scholar 

  3. Fogarty, J., Au, C., Hudson, S.E.: Sensing from the Basement: A Feasibility Study of Unobtrusive and Low-Cost Home Activity Recognition. In: Proceedings of the ACM Symposium on User Interface Software and Technology (UIST 2006), pp. 91–100 (2006)

    Google Scholar 

  4. Chen, J., Zhang, J., Kam, A.H., Shue, L.: An automatic acoustic bathroom monitoring system. In: IEEE International Symposium on Circuits and Systems, 2005. ISCAS 2005, May 23-26, 2005, vol. 2, pp. 1750–1753 (2005)

    Google Scholar 

  5. Kraft, F., Schaaf, T., Waibel, A., Malkin, R.: Temporal ICA for Classification of Acoustic Events in a Kitchen Environment. In: 9th European Conference on Speech Communication and Technology 2005, Interspeech 2005, Lisboa, Portugal, September 13, 2005, pp. 2689–2692 (2005)

    Google Scholar 

  6. Stager, M., Lukowicz, P., Troster, G.: Implementation and evaluation of a low-power sound-based user activity recognition system. In: Eighth International Symposium on Wearable Computers. ISWC 2004, 31 October-3 November 2004, vol. 1, pp. 138–141 (2004)

    Google Scholar 

  7. Bannach, D., Amft, O., Lukowicz, P.: Rapid Prototyping of Activity Recognition Applications. Pervasive Computing 7(2), 22–31 (2008)

    Article  Google Scholar 

  8. Mierswa, I., Wurst, M., Klinkenberg, R., Scholz, M., Euler, T.: YALE: Rapid Prototyping for Complex Data Mining Tasks. In: Proceedings of the 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2006), pp. 935–940 (2006)

    Google Scholar 

  9. Bluetooth Special Interest Group, https://www.bluetooth.org/apps/content/

  10. Stevens, S., Volkman, J., Newman, E.: A scale for the measurement of the psychological magnitude of pitch. Journal of the Acoustical Society of America 8(3), 185–190 (1937)

    Article  Google Scholar 

  11. Liu, H., Motoda, H.: Feature Extraction, Construction and Selection. Kluwer Academic Publisher Group, Boston (1998)

    Book  MATH  Google Scholar 

  12. Liu, H., Motoda, H.: Feature Selection for Knowledge Discovery and Data Mining. Kluwer Academic Publisher Group, Boston (1998)

    Book  MATH  Google Scholar 

  13. Bishop, C.: Pattern Recognition and Machine Learning, 1st edn. Springer, Heidelberg (2007)

    MATH  Google Scholar 

  14. Cristianini, N., Shawe-Taylor, J.: An Introduction to Support Vector Machines and Other Kernel-Based Learning Methods. Cambridge University Press, New York (2000)

    Book  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2008 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Ibarz, A., Bauer, G., Casas, R., Marco, A., Lukowicz, P. (2008). Design and Evaluation of a Sound Based Water Flow Measurement System. In: Roggen, D., Lombriser, C., Tröster, G., Kortuem, G., Havinga, P. (eds) Smart Sensing and Context. EuroSSC 2008. Lecture Notes in Computer Science, vol 5279. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88793-5_4

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-88793-5_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-88792-8

  • Online ISBN: 978-3-540-88793-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics