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

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2022

Autores

Santos, M (Autor) Outra; Borges, A (Autor) Outra; Carneiro, D (Autor) Outra; Ferreira, F (Autor) Outra

Ata de Conferência Internacional

Título: INNOVATIONS IN INDUSTRIAL ENGINEERING

Páginas: 234-245

1st International Conference on Innovation in Engineering (ICIE)

Guimaraes, PORTUGAL, JUN 28-30, 2021

Indexação

ISI Web of Knowledge - 0 Citações

Scopus - 1 Citação

Outras Informações

ID Authenticus: 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.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 12