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Time Series Analysis for Anomaly Detection of Water Consumption: A Case Study

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Innovations in Industrial Engineering (icieng 2021)

Part of the book series: Lecture Notes in Mechanical Engineering ((LNME))

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Abstract

Water loss is one of the factors that most affect a concessionaire’s financial sustainability. Early detection of any anomaly in water consumption is very valuable. This article aims to carry out a preliminary study to detect change points in consumption associated with water meter malfunction. The dataset is composed of water consumption measurements of two different companies (a hotel and a hospital) located in the north of Portugal, obtained during a complete year. Different methods were implemented in order to study its effectiveness in the detection of change points in the time series related to a sharp decrease in water consumption. Results suggest that the Seasonal Decomposition of Time Series by Loess method (STL) and the combination of several breakpoint detection methods is a suitable approach to be implemented in a software system, in order to help the company in anomaly detection and in the decision-making process of substituting the water meters.

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Acknowledgement

This work has received funding from FEDER Funds through P2020 program and from National Funds through FCT - Fundação para a Ciência e a Tecnologia (Portuguese Foundation for Science and Technology) under the projects UID/GES/04728/2017, UIDB/00013/2020 and UIDP/00013/2020.

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Authors and Affiliations

  1. CIICESI, ESTG, Politécnico do Porto, Rua do Curral, Casa do Curral, Margaride, 4610-156, Felgueiras, Portugal

    Marta Santos, Ana Borges & Davide Carneiro

  2. Center of Mathematics, University of Minho, Campus de Azurém, 4800-058, Guimarães, Portugal

    Flora Ferreira

Authors
  1. Marta Santos
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  2. Ana Borges
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  3. Davide Carneiro
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  4. Flora Ferreira
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Corresponding author

Correspondence to Flora Ferreira .

Editor information

Editors and Affiliations

  1. Department of Mechanical Engineering, University of Minho, Guimarães, Portugal

    José Machado

  2. Department of Industrial Electronics, University of Minho, Guimarães, Portugal

    Filomena Soares

  3. Poznan University of Technology, Poznan, Poland

    Justyna Trojanowska

  4. Department of Manufacturing Engineering, Machines and Tools, Sumy State University, Sumy, Ukraine

    Vitalii Ivanov

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Santos, M., Borges, A., Carneiro, D., Ferreira, F. (2022). Time Series Analysis for Anomaly Detection of Water Consumption: A Case Study. In: Machado, J., Soares, F., Trojanowska, J., Ivanov, V. (eds) Innovations in Industrial Engineering. icieng 2021. Lecture Notes in Mechanical Engineering. Springer, Cham. https://doi.org/10.1007/978-3-030-78170-5_21

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  • DOI: https://doi.org/10.1007/978-3-030-78170-5_21

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-78169-9

  • Online ISBN: 978-3-030-78170-5

  • eBook Packages: EngineeringEngineering (R0)

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