Characterization of Water Consumers in Urban Areas Using Artificial Intelligence and Data Analysis

This work presents the first steps of the integration of AI techniques in the field of urban water management, more precisely in the line of urban consumption forecasting and user characterization. For this purpose, different data visualization and clustering techniques are applied and the results are compared, in order to study which ones are more suitable for pattern extraction and detection. The resulting user profiles are then contrasted to determine common characteristics among the same group members and differences among others. Average daily consumption and variability are proposed as the variables on which the characterization is based.

Authors

Institutions

Publication Details

Published
2024-11-01
DOI
https://doi.org/10.17979/spudc.9788497498913.22
Primary Topic
Smart Parking Systems Research
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Characterization of Water Consumers in Urban Areas Using Artificial Intelligence and Data Analysis

Francisco Zayas‐Gato, José Luis Calvo‐Rolle, Manuel Rubiños, Marta-María Álvarez-Crespo
Smart Parking Systems Research
article

Characterization of Water Consumers in Urban Areas Using Artificial Intelligence and Data Analysis

Francisco Zayas‐Gato, José Luis Calvo‐Rolle, Manuel Rubiños, Marta-María Álvarez-Crespo
article en

Abstract

This work presents the first steps of the integration of AI techniques in the field of urban water management, more precisely in the line of urban consumption forecasting and user characterization. For this purpose, different data visualization and clustering techniques are applied and the results are compared, in order to study which ones are more suitable for pattern extraction and detection. The resulting user profiles are then contrasted to determine common characteristics among the same group members and differences among others. Average daily consumption and variability are proposed as the variables on which the characterization is based.

CITIC Group (China) (CN)
European Commission, Xunta de Galicia, Instituto Nacional de Ciberseguridad, Agencia Estatal de Investigación
Openalex Percentile: Top 71%
Smart Parking Systems Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.