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Detection of unauthorized consumption in water supply systems: A case study using logistic regression

Author

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  • Pereira Teodoro da Silva, Kairo
  • Kalbusch, Andreza
  • Henning, Elisa

Abstract

This study proposes characterizing unauthorized water consumption and fitting multiple logistic regression models for detecting illegal connections. The research used monthly water consumption data from 42,131 single-family homes in Joinville, southern Brazil. The obtained models achieved accuracies ranging from 83% to 100% for detecting three types of fraud (unauthorized reconnection of a disconnected water service line, bypass, and direct connection). The results showed previous minor violations, tampering with water meters and stands, and non-compliance of meter installation with utility standards are related to illegal connections.

Suggested Citation

  • Pereira Teodoro da Silva, Kairo & Kalbusch, Andreza & Henning, Elisa, 2023. "Detection of unauthorized consumption in water supply systems: A case study using logistic regression," Utilities Policy, Elsevier, vol. 84(C).
    • Handle: RePEc:eee:juipol:v:84:y:2023:i:c:s0957178723001595
    DOI: 10.1016/j.jup.2023.101647
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    References listed on IDEAS

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    1. J. G. Liao & Joseph E. Cavanaugh & Timothy L. McMurry, 2018. "Extending AIC to best subset regression," Computational Statistics, Springer, vol. 33(2), pages 787-806, June.
    2. Aditya Dinesh Gupta & Prerna Pandey & Andrés Feijóo & Zaher Mundher Yaseen & Neeraj Dhanraj Bokde, 2020. "Smart Water Technology for Efficient Water Resource Management: A Review," Energies, MDPI, vol. 13(23), pages 1-23, November.
    3. Taha AL-Washali & Saroj Sharma & Maria Kennedy, 2016. "Methods of Assessment of Water Losses in Water Supply Systems: a Review," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(14), pages 4985-5001, November.
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