Fuzzy irrigation model in protected crop based on expert knowledge

Detalhes bibliográficos
Autor(a) principal: Godo Alonso, Alain
Data de Publicação: 2025
Outros Autores: Villavicencio Quintero, Dennis, abrera Hernández, Emilio C, Santana Ching, Ivan
Tipo de documento: Artigo
Idioma: eng
Título da fonte: ITEGAM-JETIA
Texto Completo: https://itegam-jetia.org/journal/index.php/jetia/article/view/1926
Resumo: Fuzzy logic is a subfield of Artificial Intelligence that allows human knowledge to be expressed naturally, through linguistic variables and values, and an inference process very similar to the one it uses daily. The present research uses expert criteria to design and evaluate a model based on a fuzzy system to predict the irrigation time of the protected crop of cucumber (Cucumis sativus L.). The variables temperature, soil moisture and lighting are used for the model construction, which is coupled to an existing IoT technology in the various crops company "Valle del Yabú", serving as a support system for decision making. The prototype is created and simulated in MATLAB, then transferred to a Raspberry Pi 4 Model B, using the Python programming language. Tests using a database collected during one crop cycle show a 10.07% reduction in water usage compared to the standard irrigation currently implemented by the company.
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spelling Fuzzy irrigation model in protected crop based on expert knowledgeFuzzy logic is a subfield of Artificial Intelligence that allows human knowledge to be expressed naturally, through linguistic variables and values, and an inference process very similar to the one it uses daily. The present research uses expert criteria to design and evaluate a model based on a fuzzy system to predict the irrigation time of the protected crop of cucumber (Cucumis sativus L.). The variables temperature, soil moisture and lighting are used for the model construction, which is coupled to an existing IoT technology in the various crops company "Valle del Yabú", serving as a support system for decision making. The prototype is created and simulated in MATLAB, then transferred to a Raspberry Pi 4 Model B, using the Python programming language. Tests using a database collected during one crop cycle show a 10.07% reduction in water usage compared to the standard irrigation currently implemented by the company.A lógica difusa é um subcampo da Inteligência Artificial que permite que o conhecimento humano seja expresso de forma natural, através de variáveis e valores linguísticos, e de um processo de inferência muito semelhante ao que utiliza diariamente. A presente investigação utiliza critérios especializados para conceber e avaliar um modelo baseado num sistema fuzzy para prever o tempo de rega da cultura protegida de pepino (Cucumis sativus L.). As variáveis temperatura, humidade do solo e iluminação são utilizadas para a construção do modelo, que é acoplado a uma tecnologia IoT existente na empresa de várias culturas “Valle del Yabú”, servindo como um sistema de apoio à tomada de decisões. O protótipo é criado e simulado em MATLAB, sendo depois transferido para um Raspberry Pi 4 Modelo B, utilizando a linguagem de programação Python. Os testes realizados com uma base de dados recolhida durante um ciclo de cultivo mostram uma redução de 10,07% no consumo de água em comparação com a rega padrão atualmente implementada pela empresa.La lógica difusa es un subcampo de la Inteligencia Artificial que permite expresar el conocimiento humano de forma natural, mediante variables y valores lingüísticos, y un proceso de inferencia muy similar al que utiliza cotidianamente. La presente investigación utiliza criterios expertos para diseñar y evaluar un modelo basado en un sistema difuso para predecir el momento de riego del cultivo protegido de pepino (Cucumis sativus L.). Se utilizan las variables temperatura, humedad del suelo e iluminación para la construcción del modelo, el cual se acopla a una tecnología IoT existente en la empresa de cultivos varios «Valle del Yabú», sirviendo como sistema de apoyo para la toma de decisiones. El prototipo es creado y simulado en MATLAB, luego transferido a una Raspberry Pi 4 Modelo B, utilizando el lenguaje de programación Python. Las pruebas realizadas con una base de datos recopilada durante un ciclo de cultivo muestran una reducción del 10,07% en el uso de agua en comparación con el riego estándar implementado actualmente por la empresa.ITEGAM - Instituto de Tecnologia e Educação Galileo da Amazônia2025-04-25info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionPeer-reviewed Articleapplication/pdfhttps://itegam-jetia.org/journal/index.php/jetia/article/view/192610.5935/jetia.v11i52.1926ITEGAM-JETIA; v.11 n.52 2025; 266-275ITEGAM-JETIA; v.11 n.52 2025; 266-275ITEGAM-JETIA; v.11 n.52 2025; 266-2752447-022810.5935/jetia.v11i52reponame:ITEGAM-JETIAinstname:Instituto de Tecnologia e Educação Galileo da Amazônia (ITEGAM)instacron:ITEGAMenghttps://itegam-jetia.org/journal/index.php/jetia/article/view/1926/1007Copyright (c) 2025 ITEGAM-JETIAinfo:eu-repo/semantics/openAccessGodo Alonso, AlainVillavicencio Quintero, Dennisabrera Hernández, Emilio CSantana Ching, Ivan2025-05-06T14:20:53Zoai:ojs.itegam-jetia.org:article/1926Revistahttps://itegam-jetia.org/journal/index.php/jetiaPRIhttps://itegam-jetia.org/journal/index.php/jetia/oaieditor@itegam-jetia.orgopendoar:2025-05-06T14:20:53ITEGAM-JETIA - Instituto de Tecnologia e Educação Galileo da Amazônia (ITEGAM)false
dc.title.none.fl_str_mv Fuzzy irrigation model in protected crop based on expert knowledge
title Fuzzy irrigation model in protected crop based on expert knowledge
spellingShingle Fuzzy irrigation model in protected crop based on expert knowledge
Godo Alonso, Alain
title_short Fuzzy irrigation model in protected crop based on expert knowledge
title_full Fuzzy irrigation model in protected crop based on expert knowledge
title_fullStr Fuzzy irrigation model in protected crop based on expert knowledge
title_full_unstemmed Fuzzy irrigation model in protected crop based on expert knowledge
title_sort Fuzzy irrigation model in protected crop based on expert knowledge
author Godo Alonso, Alain
author_facet Godo Alonso, Alain
Villavicencio Quintero, Dennis
abrera Hernández, Emilio C
Santana Ching, Ivan
author_role author
author2 Villavicencio Quintero, Dennis
abrera Hernández, Emilio C
Santana Ching, Ivan
author2_role author
author
author
dc.contributor.author.fl_str_mv Godo Alonso, Alain
Villavicencio Quintero, Dennis
abrera Hernández, Emilio C
Santana Ching, Ivan
description Fuzzy logic is a subfield of Artificial Intelligence that allows human knowledge to be expressed naturally, through linguistic variables and values, and an inference process very similar to the one it uses daily. The present research uses expert criteria to design and evaluate a model based on a fuzzy system to predict the irrigation time of the protected crop of cucumber (Cucumis sativus L.). The variables temperature, soil moisture and lighting are used for the model construction, which is coupled to an existing IoT technology in the various crops company "Valle del Yabú", serving as a support system for decision making. The prototype is created and simulated in MATLAB, then transferred to a Raspberry Pi 4 Model B, using the Python programming language. Tests using a database collected during one crop cycle show a 10.07% reduction in water usage compared to the standard irrigation currently implemented by the company.
publishDate 2025
dc.date.none.fl_str_mv 2025-04-25
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer-reviewed Article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://itegam-jetia.org/journal/index.php/jetia/article/view/1926
10.5935/jetia.v11i52.1926
url https://itegam-jetia.org/journal/index.php/jetia/article/view/1926
identifier_str_mv 10.5935/jetia.v11i52.1926
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://itegam-jetia.org/journal/index.php/jetia/article/view/1926/1007
dc.rights.driver.fl_str_mv Copyright (c) 2025 ITEGAM-JETIA
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2025 ITEGAM-JETIA
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv ITEGAM - Instituto de Tecnologia e Educação Galileo da Amazônia
publisher.none.fl_str_mv ITEGAM - Instituto de Tecnologia e Educação Galileo da Amazônia
dc.source.none.fl_str_mv ITEGAM-JETIA; v.11 n.52 2025; 266-275
ITEGAM-JETIA; v.11 n.52 2025; 266-275
ITEGAM-JETIA; v.11 n.52 2025; 266-275
2447-0228
10.5935/jetia.v11i52
reponame:ITEGAM-JETIA
instname:Instituto de Tecnologia e Educação Galileo da Amazônia (ITEGAM)
instacron:ITEGAM
instname_str Instituto de Tecnologia e Educação Galileo da Amazônia (ITEGAM)
instacron_str ITEGAM
institution ITEGAM
reponame_str ITEGAM-JETIA
collection ITEGAM-JETIA
repository.name.fl_str_mv ITEGAM-JETIA - Instituto de Tecnologia e Educação Galileo da Amazônia (ITEGAM)
repository.mail.fl_str_mv editor@itegam-jetia.org
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