Hydrometer Recommendation System and Predictive Analysis of Losses in Telemetry Networks
Autor(a) principal: | |
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Data de Publicação: | 2023 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo |
Idioma: | por |
Título da fonte: | Revista de Engenharia e Pesquisa Aplicada |
Texto Completo: | http://revistas.poli.br/index.php/repa/article/view/2784 |
Resumo: | Recommendation systems are essential tools that can assist in evaluating telemetric data by identifying patterns and trends within the telemetry data. In this study, we present an analysis conducted on the water network data of a municipality in the southern region of Brazil to detect patterns and develop a hydrometer recommendation system based on user profiles. We performed a correlational study between consumption characteristics and properties of measurement devices, aiming to identify the attributes with the most significant influence on water usage. Fromthe descriptive exploration of the data, we observed that both the type and model of the hydrometer and the age of the device could impact user measurement results and consumption behavior. Consequently, the analysis results were utilized to create a system capable of identifying and visually confirming the intersections between the desired characteristics. |
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Hydrometer Recommendation System and Predictive Analysis of Losses in Telemetry NetworksSistema de Recomendação de Hidrômetro e Análise Preditiva de Perdas em Redes de TelemetriaRecommendation systems are essential tools that can assist in evaluating telemetric data by identifying patterns and trends within the telemetry data. In this study, we present an analysis conducted on the water network data of a municipality in the southern region of Brazil to detect patterns and develop a hydrometer recommendation system based on user profiles. We performed a correlational study between consumption characteristics and properties of measurement devices, aiming to identify the attributes with the most significant influence on water usage. Fromthe descriptive exploration of the data, we observed that both the type and model of the hydrometer and the age of the device could impact user measurement results and consumption behavior. Consequently, the analysis results were utilized to create a system capable of identifying and visually confirming the intersections between the desired characteristics.Os sistemas de recomendação são importantes ferramentas que ajudamna avaliação de dados telemétricos a partir da identificação de padrões e tendências. Neste trabalho, os autores apresentam a análise realizada nos dados da rede hídrica de um município da região sul brasileira para a detecção de padrões e criação de um sistema de recomendação de hidrômetros, baseado no perfil do usuário. Para tanto, houve de ser estruturado um estudo correlacional entre características de consumo epropriedades dos aparelhos de medição, de modo a traçar quais atributos de maior influência no gasto de água. Após a exploração descritiva dos dados foi verificado que tanto o tipo, quanto o modelo do hidrômetro e idade do aparelho poderiam interferir nos resultados de medição do usuário e comportamento do consumo. Dessa forma, foi possível utilizar os resultados da análise para a criação de um sistema capaz de identificar e gerar comprovações visuais dos cruzamentos entre as características desejadas.Escola Politécnica de Pernambuco2023-12-28info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdftext/htmlhttp://revistas.poli.br/index.php/repa/article/view/278410.25286/repa.v9i1.2784Journal of Engineering and Applied Research; Vol 9 No 1 (2024): Edição Especial em Ciência de Dados e Analytics; 86-96Revista de Engenharia e Pesquisa Aplicada; v. 9 n. 1 (2024): Edição Especial em Ciência de Dados e Analytics; 86-962525-425110.25286/repa.v9i1reponame:Revista de Engenharia e Pesquisa Aplicadainstname:Universidade Federal de Pernambuco (UFPE)instacron:UFPEporhttp://revistas.poli.br/index.php/repa/article/view/2784/907http://revistas.poli.br/index.php/repa/article/view/2784/908Copyright (c) 2024 Mário Stela Guerra, Gabriel Correia de Albuquerque, Antônio Victor Alencar Lundgren, Bruno José Torres Fernandes, Alexandre Magno Andrade Maciel, Carmelo José Albanez Bastos Filhohttp://creativecommons.org/licenses/by-nc/4.0info:eu-repo/semantics/openAccessGuerra, Mário Stelade Albuquerque, Gabriel CorreiaLundgren, Antônio Victor AlencarFernandes, Bruno José TorresMaciel, Alexandre Magno AndradeBastos Filho, Carmelo José Albanez2023-12-30T10:15:41Zoai:ojs.poli.br:article/2784Revistahttp://revistas.poli.br/index.php/repaONGhttp://revistas.poli.br/index.php/repa/oai||repa@poli.br2525-42512525-4251opendoar:2023-12-30T10:15:41Revista de Engenharia e Pesquisa Aplicada - Universidade Federal de Pernambuco (UFPE)false |
dc.title.none.fl_str_mv |
Hydrometer Recommendation System and Predictive Analysis of Losses in Telemetry Networks Sistema de Recomendação de Hidrômetro e Análise Preditiva de Perdas em Redes de Telemetria |
title |
Hydrometer Recommendation System and Predictive Analysis of Losses in Telemetry Networks |
spellingShingle |
Hydrometer Recommendation System and Predictive Analysis of Losses in Telemetry Networks Guerra, Mário Stela |
title_short |
Hydrometer Recommendation System and Predictive Analysis of Losses in Telemetry Networks |
title_full |
Hydrometer Recommendation System and Predictive Analysis of Losses in Telemetry Networks |
title_fullStr |
Hydrometer Recommendation System and Predictive Analysis of Losses in Telemetry Networks |
title_full_unstemmed |
Hydrometer Recommendation System and Predictive Analysis of Losses in Telemetry Networks |
title_sort |
Hydrometer Recommendation System and Predictive Analysis of Losses in Telemetry Networks |
author |
Guerra, Mário Stela |
author_facet |
Guerra, Mário Stela de Albuquerque, Gabriel Correia Lundgren, Antônio Victor Alencar Fernandes, Bruno José Torres Maciel, Alexandre Magno Andrade Bastos Filho, Carmelo José Albanez |
author_role |
author |
author2 |
de Albuquerque, Gabriel Correia Lundgren, Antônio Victor Alencar Fernandes, Bruno José Torres Maciel, Alexandre Magno Andrade Bastos Filho, Carmelo José Albanez |
author2_role |
author author author author author |
dc.contributor.author.fl_str_mv |
Guerra, Mário Stela de Albuquerque, Gabriel Correia Lundgren, Antônio Victor Alencar Fernandes, Bruno José Torres Maciel, Alexandre Magno Andrade Bastos Filho, Carmelo José Albanez |
description |
Recommendation systems are essential tools that can assist in evaluating telemetric data by identifying patterns and trends within the telemetry data. In this study, we present an analysis conducted on the water network data of a municipality in the southern region of Brazil to detect patterns and develop a hydrometer recommendation system based on user profiles. We performed a correlational study between consumption characteristics and properties of measurement devices, aiming to identify the attributes with the most significant influence on water usage. Fromthe descriptive exploration of the data, we observed that both the type and model of the hydrometer and the age of the device could impact user measurement results and consumption behavior. Consequently, the analysis results were utilized to create a system capable of identifying and visually confirming the intersections between the desired characteristics. |
publishDate |
2023 |
dc.date.none.fl_str_mv |
2023-12-28 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://revistas.poli.br/index.php/repa/article/view/2784 10.25286/repa.v9i1.2784 |
url |
http://revistas.poli.br/index.php/repa/article/view/2784 |
identifier_str_mv |
10.25286/repa.v9i1.2784 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.relation.none.fl_str_mv |
http://revistas.poli.br/index.php/repa/article/view/2784/907 http://revistas.poli.br/index.php/repa/article/view/2784/908 |
dc.rights.driver.fl_str_mv |
http://creativecommons.org/licenses/by-nc/4.0 info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
http://creativecommons.org/licenses/by-nc/4.0 |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf text/html |
dc.publisher.none.fl_str_mv |
Escola Politécnica de Pernambuco |
publisher.none.fl_str_mv |
Escola Politécnica de Pernambuco |
dc.source.none.fl_str_mv |
Journal of Engineering and Applied Research; Vol 9 No 1 (2024): Edição Especial em Ciência de Dados e Analytics; 86-96 Revista de Engenharia e Pesquisa Aplicada; v. 9 n. 1 (2024): Edição Especial em Ciência de Dados e Analytics; 86-96 2525-4251 10.25286/repa.v9i1 reponame:Revista de Engenharia e Pesquisa Aplicada instname:Universidade Federal de Pernambuco (UFPE) instacron:UFPE |
instname_str |
Universidade Federal de Pernambuco (UFPE) |
instacron_str |
UFPE |
institution |
UFPE |
reponame_str |
Revista de Engenharia e Pesquisa Aplicada |
collection |
Revista de Engenharia e Pesquisa Aplicada |
repository.name.fl_str_mv |
Revista de Engenharia e Pesquisa Aplicada - Universidade Federal de Pernambuco (UFPE) |
repository.mail.fl_str_mv |
||repa@poli.br |
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1798036000572702720 |