Detection and Prediction of Leakages in Water Distribution Networks

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

2023

Abstract

Leakages are one of the main causes of water loss in a water distribution system (WDS). In recent years, the increasing of streaming data coming from sensors installed in the water network, allows the monitoring the health status of each asset of the WDS. In this paper, a preliminary data-driven approach for leakages detection and prediction is proposed. Starting from the characteristics of a real water distribution network, a realistic leakages dataset has been achieved. Using this dataset, unsupervised rule-based time series algorithms has been trained for the detection and prediction of leakages.

Paper Citation

in Harvard Style

Berlotti M., Di Grande S., Cavalieri S. and Gueli R. (2023). Detection and Prediction of Leakages in Water Distribution Networks. In Proceedings of the 12th International Conference on Data Science, Technology and Applications - Volume 1: DATA; ISBN 978-989-758-664-4, SciTePress, pages 436-443. DOI: 10.5220/0012122000003541

in Bibtex Style

@conference{data23,
author={Mariaelena Berlotti and Sarah Di Grande and Salvatore Cavalieri and Roberto Gueli},
title={Detection and Prediction of Leakages in Water Distribution Networks},
booktitle={Proceedings of the 12th International Conference on Data Science, Technology and Applications - Volume 1: DATA},
year={2023},
pages={436-443},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012122000003541},
isbn={978-989-758-664-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 12th International Conference on Data Science, Technology and Applications - Volume 1: DATA
TI - Detection and Prediction of Leakages in Water Distribution Networks
SN - 978-989-758-664-4
AU - Berlotti M.
AU - Di Grande S.
AU - Cavalieri S.
AU - Gueli R.
PY - 2023
SP - 436
EP - 443
DO - 10.5220/0012122000003541
PB - SciTePress