Top > JDR > Water Leakage Detection System for Underground Pipes by Using ...

single-dr.php

JDR Vol.12 No.3 pp. 557-568
(2017)
doi: 10.20965/jdr.2017.p0557

Paper:

Views over last 60 days: 1,486

Water Leakage Detection System for Underground Pipes by Using Wireless Sensors and Machine Learning

Shigeru Teruhi*, Yo Yamaguchi*, and Junichi Akahani**

*NTT Network Innovation Laboratories, NTT Corporation
Hikarinooka, Yokosuka 239-0847, Japan

**NTT Advanced Technology Corporation, Kawasaki, Japan

Received:
September 21, 2016
Accepted:
January 28, 2017
Online released:
May 29, 2017
Published:
June 1, 2017
Creative Commons License
Keywords:
water leakage, underground structure, wireless sensor, machine learning
Abstract
Expectations have been raised for a social infrastructure maintenance system that utilizes IoT/M2M technology. We are working to develop a water leakage detection system using wireless sensors set into the water pipes. However, radio propagation is restricted in the constrained underground environment of water pipes so how to collect the data and identify leaks is an issue. We propose a system that combines drive-by data collection and static data collection, in order to collect acoustic sensor data from a wide area effectively [1]. We also propose a random noise removal method by focusing on the constancy of the leak sound, in order to identify leaks accurately. We show the results of evaluating the effectiveness of the proposed system in tests and real fields.
Cite this article as:
S. Teruhi, Y. Yamaguchi, and J. Akahani, “Water Leakage Detection System for Underground Pipes by Using Wireless Sensors and Machine Learning,” J. Disaster Res., Vol.12 No.3, pp. 557-568, 2017.
Data files:
References
  1. [1] K. Akabane, N. Mochizuki, S. Teruhi, M. Kobayashi, S. Yoshino, M. Shimizu, and K. Uehara, “High-Capacity Wireless Access Networks Using 920 MHz Band for Wide-Area IoT/M2M Services,” IEICE Trans. on Comm., Vol.E99.B, No.9, pp. 1920-1929, 2016.
  2. [2] “Water Statistics,” No.97, Japan Water Works Association, 2014.
  3. [3] “Water Resources in Japan,” Ministry of Land, Infrastructure, Transport and Tourism, 2014.
  4. [4] Y. Kuwata and T. Okamoto, “Analysis of the Impact of Water-Supply Outages Due to Multiple Factors Caused by the 2011 Tohoku Earthquake,” J. of Disaster Research, Vol.7, No.6, pp. 701-710, 2012.
  5. [5] K. Matsui, “Japan’s approach to water problems in the world,” Lawmaking and Research, No.332, House of Councillors, 2012.
  6. [6] http://www.jwrc-net.or.jp/hotnews/pdf/HotNews109.pdf [accessed Sep. 21, 2016]
  7. [7] K. Fukushima, Y. Murata, K. Izumi, Y. Ito, A. Yoshizawa, and T. Tanaka, “A Water Leak Detection Service Based on Sensors and ICT Solutions,” NEC Technical Journal, Vol.9, No.1, pp. 107-110, 2015.
  8. [8] Z. Sun and I. F. Akyildiz, “Magnetic Induction Communications for Wireless Underground Sensor Networks,” IEEE Trans. on Ant. and Prop., Vol.58, No.7, 2010.
  9. [9] H. Yoshioka, H. Shibayama, J. Iwatani, T. Ito, H. Tsuboi, A. Ando, and H. Nakamura, “Study on communication that uses RF-ID set in a manhole,” IEICE Society Conference 2009, B-5-94, 2009 (in Japanese).
  10. [10] T. Mizuno, H. Miyakawa, S. Meguro, and J. Akahani, “Study of water pipe leak detection using machine learning,” IEICE General Conference 2016, B-18-55, 2016 (in Japanese).
  11. [11] A. Ando, T. Ito, H. Yoshioka, H. Tsuboi, and H. Nakamura, “Effects of receiver antenna height and polarization on received signal levels at road level from transmitter antennas set in manhole,” IEEE AP-S, pp. 2399-2402, 2011.
  12. [12] H. Tsuboi, H. Yoshioka, A. Ando, and H. Nakamura, “Study of a radio system that can amass information about manholes from a moving vehicle,” IEICE General Conference 2012, B-5-39, 2012 (in Japanese).
  13. [13] http://www.arib.or.jp/english/html/overview/doc/1-STD-T108v1_0.pdf [accessed Sep. 21, 2016]
  14. [14] IEEE Std 802.15.4gTM-2012, Part15.4-Low-Rate Wireless Personal Area Networks (LR-WPANs), April 2012.
  15. [15] http://www.tepco.co.jp/smartmeter/index-j.html [accessed Sep. 21, 2016]
  16. [16] COST 231 Final Report, Chapter 4.6.2, Penetration loss at non line of sight conditions, 1996.
  17. [17] M. Hata, “Empirical formula for propagation loss in land mobile radio services,” IEEE Trans. Veh. Tech., Vol.VT-29, No.3, pp. 317-325, 1980.
  18. [18] http://www.silabs.com/support%20documents/technicaldocs/an647.pdf [accessed Sep. 21, 2016]
  19. [19] K. Tanaka, K. Hoshino, H. Maruyama, H. Imura, Y. Katahara, and T. Hamaya, “Study on an Antenna of Radio wave for Frequency and Time standard,” Report of the Industrial Research Institute of Niigata Prefecture, No.31, 2002.
  20. [20] Public Notice that sets Details set by safety standard Article 3 about Road Trucking Vehicle, (1002nd Public Notice of Ministry of Land, Infrastructure, Transport and Tourism, July 7, 2003), 2003.
  21. [21] Y. Chiba, “Introductory of Acoustics,” http://abcpedia.acoustics.jp/acoustic_feature_2.pdf [accessed Sep. 21, 2016]
  22. [22] C. Kondo and A. Mita, “PCA Based Water Leakage Detection Method Using Complex Fourier Components,” J. of Environmental Engineering, Architectural Institute of Japan, Vol.74, No.642, pp. 965-972, 2009.
  23. [23] S. Koshimura, “Special Issue on Disaster and Big Data,” J. of Disaster Research, Vol.11, No.2, p. 163, 2016.
  24. [24] T. Kurita, “Introduction to Support Vector Machines,” National Institute of Advanced Industrial Science and Technology, http://home.hiroshima-u.ac.jp/tkurita/lecture/svm.pdf [accessed Sep. 21, 2016]
  25. [25] https://cran.r-project.org/web/packages/e1071/index.html [accessed Sep. 21, 2016]

Creative Commons License  This article is published under a Creative Commons Attribution-NoDerivatives 4.0 Internationa License.

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, Opera.

Last updated on Apr. 19, 2024