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

• Type: Article in International Conference Proceedings Book
• Date: 2022

Authors

Santos, M (Author) Other; Borges, A (Author) Other; Carneiro, D (Author) Other; Ferreira, F (Author) Other

Conference proceedings International

Title: INNOVATIONS IN INDUSTRIAL ENGINEERING

Pages: 234-245

1st International Conference on Innovation in Engineering (ICIE)

Guimaraes, PORTUGAL, JUN 28-30, 2021

Indexing

ISI Web of Knowledge - 0 Citations

Scopus - 1 Citation

Other information

Authenticus ID: P-00V-377

DOI: 10.1007/978-3-030-78170-5_21

Abstract (EN): 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.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 12