Detection of Water Meter Under-Registration Using Statistical Algorithms
Publication: Journal of Water Resources Planning and Management
Volume 142, Issue 1
Abstract
Meter tampering is an important problem for utilities (both power and water distribution) to address because they represent an important loss of income. The authors’ group at the Electronic Technology Department of the University of Seville worked with the Empresa Metropolitana de Abastecimiento y Saneamiento de Aguas de Sevilla (EMASESA Company, a water distribution company in Seville and one of the most important of the country) to develop a methodology consisting of three algorithms that makes it possible to jointly detect this type of manipulations among its customers. The algorithms were generated and programmed after a data mining process using the database of the company. In addition, these algorithms were supplemented with a study of the geographical information of the customer supply points to improve the results. To test the results, the Emasesa Company performed in situ inspections of the customers selected by the algorithms for several areas in the province of Seville. The success rate of the algorithms was approximately 9%, which is considered satisfactory owing to the nature of the problem, in which fraud is easy to hide and infrequently detected.
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Acknowledgments
The authors thank the Corporación Tecnológica de Andalucía (CTA) for providing the funds for this project. The authors are also indebted to the following colleagues of EMASESA Company for their valuable assistance in the project: Victor Pallares, Alfonso Cardenas, Carmelo Santana, and Alejandro Alfaro.
References
American Water Works Association (AWWA). (2012). Water meters—Selection, installation, testing, and maintenance, manual of water supply practices M6, 5th Ed., Denver.
Arregui, F., Cobacho, R., Cabrera, E., Jr., and Espert, V. (2011). “Graphical method to calculate the optimum replacement period for water meters.” J. Water Resour. Plann. Manage., 143–146.
Arreguín-Cortés, F., and Ochoa-Alejo, L. (1997). “Evaluation of water losses in distribution networks.” J. Water Resour. Plann. Manage., 284–291.
Bayliss, C. R., and Hardy, B. J. (2012). “Smart grids.” Chapter 27, Transmission and distribution electrical engineering, 4th Ed., Newnes, Oxford, 1059–1074.
Begovich, O., and Valdovinos-Villalobos, G. (2010). “DSP application of a water-leak detection and isolation algorithm.” 7th Int. Conf. on Electrical Engineering Computing Science and Automatic Control (CCE), IEEE, Piscataway, NJ, 93–98.
Bolton, R. J., and Hand, D. J. (2001). “Unsupervised profiling methods for fraud detection.” Proc., Credit Scoring and Credit Control VII, Credit Research Centre, Edinburgh, U.K., 5–7.
Bolton, R. J., and Hand, D. J. (2002). “Statistical fraud detection: A review.” Stat. Sci., 17(3), 235–255.
Bonchi, F., Giannotti, F., Mainetto, G., and Pedreschi, D. (1999). “Using data mining techniques in fiscal fraud detection.” DataWarehousing and knowledge discovery, M. Mohania and A. M. Tjoa, eds., Springer, Berlin, 369–376.
Cabrera, E., Espert, V., Cabrera, E., Jr., and Soriano, J. (2014). “Discussion of ‘Losses reduction and energy production in water-distribution networks.’” J. Water Resour. Plann. Manage., 269–271.
Convey, H. J., and Booth, M. J. (2002). “Development of a water leak detection system.” Comput. Contr. Eng. J., 13(1), 33–38.
Creaco, E., and Pezzinga, G. (2015). “Multiobjective optimization of pipe replacements and control valve installations for leakage attenuation in water distribution networks.” J. Water Resour. Plann. Manage., 04014059.
Depuru, S. S. S. R., Wang, L., and Devabhaktuni, V. (2011). “Smart meters for power grid: Challenges, issues, advantages and status.” Renewable Sustainable Energy Rev., 15(6), 2736–2742.
Gestion de Aquas del Levante Almeriense (GALASA). (1991). “Reglamento de Suministro Domiciliario de Agua de la Junta de Andalucía [Regulation on home water supply in Andalusia].” Decreto 120/91, Almería, Spain.
Giugni, M., Fontana, N., and Ranucci, A. (2014). “Optimal location of PRVs and turbines in water distribution systems.” J. Water Resour. Plann. Manage., 06014004.
Google Earth [Computer software]. Mountain View, CA, Google.
Gouthaman, J., Bharathwajanprabhu, R., and Srikanth, A. (2011). “Automated urban drinking water supply control and water theft identification system.” 2011 IEEE Students’ Technology Symp. (TechSym), Indian Institute of Technology Kharagpur, Kharagpur, India, 87–91.
ISO. (2014). “Water meters count on ISO standards, parts 1 to 5.” ISO 4064:2014, Geneva.
Jankovic-Nišic, B., Maksimovic, C., Butler, D., and Graham, N. (2004). “Use of flow meters for managing water supply networks.” J. Water Resour. Plann. Manage., 171–179.
Kang, D., and Lansey, K. (2010). “Optimal meter placement for water distribution system state estimation.” J. Water Resour. Plann. Manage., 337–347.
León, C., Biscarri, F., Monedero, I., Guerrero, J. I., and Biscarri, J. (2011). “Variability and trend-based generalized rule induction model to NTL detection in power companies.” IEEE Trans. Power Syst., 26(4), 1798–1807.
Lin, J., Sedigh, S., and Hurson, A. R. (2012). “Ontologies and decision support for failure mitigation in intelligent water distribution networks.” 45th Hawaii Int. Conf. on System Science (HICSS), Shidler College of Business, Univ. of Hawai’i at Manoa, Honolulu, 1187–1196.
Monedero, I., Biscarri, F., León, C., Guerrero, J. I., Biscarri, J., and Millán, R. (2012). “Detection of frauds and other non-technical losses in a power utility using Pearson coefficient, Bayesian networks and decision trees.” Int. J. Electr. Power Energy Syst., 34(1), 90–98.
Mutikanga, H., Sharma, S., and Vairavamoorthy, K. (2013). “Methods and tools for managing losses in water distribution systems.” J. Water Resour. Plann. Manage., 166–174.
Niu, K., Huang, C., Zhang, S., and Chen, J. (2007). “ODDC: Outlier detection using distance distribution clustering.” Emerging technologies in knowledge discovery and data mining, T. Washio, et al., eds., Springer, Berlin, 332–343.
Noss, R., Newman, G., and Male, J. (1987). “Optimal testing frequency for domestic water meters.” J. Water Resour. Plann. Manage., 1–14.
Obradović, D. (2000). “Modelling of demand and losses in real-life water distribution systems.” Urban Water, 2(2), 131–139.
Pettersson, A., Nordlander, J., and Gong, S. (2009). “ZigBee-ready wireless water leak detector.” 3rd Int. Conf. on Sensor Technologies and Applications, SENSORCOMM’09, IEEE, Washington, DC, 105–108.
Popa, M., Ciocarlie, H., Popa, A. S., and Racz, M. B. (2010). “Smart metering for monitoring domestic utilities.” 14th Int. Conf. on Intelligent Engineering Systems (INES), IEEE, 55–60.
Ratnayaka, D. D., Brandt, M. J., and Johnson, K. M. (2009). “Chapter 1—The demand for public water supplies.” Water supply, 6th Ed., Butterworth-Heinemann, Boston, 1–35.
Ríos, J. C., Santos-Tellez, R. U., Rodríguez, P. H., Leyva, E. A., and Martínez, V. N. (2014). “Methodology for the identification of apparent losses in water distribution networks.” Procedia Eng., 70, 238–247.
Singhal, A. (2007). “Data modeling and data warehousing techniques to improve intrusion detection.” Data warehousing and data mining techniques for cyber security, Springer, New York, 69–82.
Vítkovský, J., Simpson, A., and Lambert, M. (2000). “Leak detection and calibration using transients and genetic algorithms.” J. Water Resour. Plann. Manage., 262–265.
Wang, R., Wang, Z., Wang, X., Yang, H., and Sun, J. (2014). “Pipe burst risk state assessment and classification based on water hammer analysis for water supply networks.” J. Water Resour. Plann. Manage., 04014005.
Wang, S. (2010). “A comprehensive survey of data mining-based accounting-fraud detection research.” Int. Conf. on Intelligent Computation Technology and Automation (ICICTA), Vol. 1, IEEE, New York, 50–53.
Xu, T., and Qin, X. (2013). “Integrating decision analysis with fuzzy programming: Application in urban water distribution system operation.” J. Water Resour. Plann. Manage., 638–648.
Yang, J., Wen, Y., and Li, P. (2008). “Leak acoustic detection in water distribution pipelines.” 7th World Congress on Intelligent Control and Automation, 2008, Chongqing Univ., Hong Kong, China, 3057–3061.
Information & Authors
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Published In
Journal of Water Resources Planning and Management
Volume 142 • Issue 1 • January 2016
Copyright
© 2015 American Society of Civil Engineers.
History
Received: Dec 10, 2014
Accepted: Apr 28, 2015
Published online: Jun 16, 2015
Discussion open until: Nov 16, 2015
Published in print: Jan 1, 2016
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