Modelling and Clustering Patterns from Smart Meter Data in Water Distribution Systems

Mariaelena Berlotti, Sarah Di Grande, Salvatore Cavalieri, Roberto Gueli

2025

Abstract

In recent years, water utilities have increasingly required a deeper understanding of users’ water demand across their distribution networks to optimize resource management and meet customers' needs. With the adoption of smart metering solutions, it has become possible to investigate water usage at a finer resolution, enabling the collection of more detailed consumption data. In the present study, the authors present an innovative methodology for identifying water usage using data from smart meters. First, a Multiple Seasonal-Trend Decomposition algorithm is applied to extract seasonality from the raw time-series data. Next, the Bootstrap sampling technique is used to train an optimized Time Series K-means algorithm on multiple data configurations. Finally, the clustering results are interpreted graphically and validated, providing valuable insights into consumption habits and a comprehensive assessment of the methodology's effectiveness and stability.

Paper Citation

in Harvard Style

Berlotti M., Di Grande S., Cavalieri S. and Gueli R. (2025). Modelling and Clustering Patterns from Smart Meter Data in Water Distribution Systems. In Proceedings of the 27th International Conference on Enterprise Information Systems - Volume 1: ICEIS; ISBN 978-989-758-749-8, SciTePress, pages 691-698. DOI: 10.5220/0013200500003929

in Bibtex Style

@conference{iceis25,
author={Mariaelena Berlotti and Sarah Di Grande and Salvatore Cavalieri and Roberto Gueli},
title={Modelling and Clustering Patterns from Smart Meter Data in Water Distribution Systems},
booktitle={Proceedings of the 27th International Conference on Enterprise Information Systems - Volume 1: ICEIS},
year={2025},
pages={691-698},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013200500003929},
isbn={978-989-758-749-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 27th International Conference on Enterprise Information Systems - Volume 1: ICEIS
TI - Modelling and Clustering Patterns from Smart Meter Data in Water Distribution Systems
SN - 978-989-758-749-8
AU - Berlotti M.
AU - Di Grande S.
AU - Cavalieri S.
AU - Gueli R.
PY - 2025
SP - 691
EP - 698
DO - 10.5220/0013200500003929
PB - SciTePress