Herramienta de analítica de datos para el mantenimiento de cultivos de cacao bajo escenarios de variabilidad climatológica

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dc.contributor.advisorTalero Sarmiento, Leonardo Hernán
dc.contributor.advisorMoreno Corzo, Feisar Enrique
dc.contributor.advisorCárdenas Fontecha, Mauren Slendy
dc.contributor.apolounabTalero Sarmiento, Leonardo Hernán [leonardo-talero]spa
dc.contributor.apolounabMoreno Corzo, Feisar Enrique [feisar-enrique-moreno-corzo]spa
dc.contributor.apolounabCárdenas Fontecha, Mauren Slendy [mauren-slendy-cárdenas-fontecha]spa
dc.contributor.authorSanabria Romero, Lizeth Johanna
dc.contributor.cvlacTalero Sarmiento, Leonardo Hernán [31387]spa
dc.contributor.cvlacMoreno Corzo, Feisar Enrique [1499008]spa
dc.contributor.cvlacCárdenas Fontecha, Mauren Slendy [0001950200]spa
dc.contributor.googlescholarMoreno Corzo, Feisar Enrique [jz75nEcAAAAJ]spa
dc.contributor.linkedinTalero Sarmiento, Leonardo Hernán [leonardo-talero-sarmiento]spa
dc.contributor.linkedinMoreno Corzo, Feisar Enrique [feisar-moreno]spa
dc.contributor.orcidTalero Sarmiento, Leonardo Hernán [0000-0002-4129-9163]spa
dc.contributor.orcidMoreno Corzo, Feisar Enrique [0000-0002-5007-3422]spa
dc.contributor.researchgateTalero Sarmiento, Leonardo Hernán [Leonardo_Talero]spa
dc.coverage.campusUNAB Campus Bucaramangaspa
dc.coverage.spatialSan Vicente de Chucurí (Santander, Colombia)spa
dc.date.accessioned2024-06-14T14:27:36Z
dc.date.available2024-06-14T14:27:36Z
dc.date.issued2024-06-04
dc.degree.nameMagíster en Gestión, Aplicación y Desarrollo de Softwarespa
dc.description.abstractEl proyecto "Herramienta de Analítica de Datos para el Mantenimiento de Cultivos de Cacao bajo Escenarios de Variabilidad Climatológica" aborda los desafíos que enfrenta la producción de cacao debido a la variabilidad climática. Esta herramienta surge como una respuesta a problemas como sequías, inundaciones y extremos térmicos que amenazan la calidad y cantidad de la cosecha de cacao. La herramienta creada utiliza análisis avanzados para comprender los fenómenos ecológicos que afectan la producción de cacao. Se conecta directamente con el API de la NASA para obtener datos climatológicos precisos. Además, implementa Redes Neuronales Recurrentes (RNN) con el modelo LSTM para realizar pronósticos confiables. La herramienta desarrollada con Python y Power BI permite no solo calcular y modelar la biomasa, sino también evaluar la sensibilidad del cacao al estrés hídrico y los índices de cosecha lo cual le confiere al tomador de decisiones una herramienta para afrontar la incertidumbre en el horizonte de planeación. La herramienta se caracteriza por su capacidad de integrar datos climatológicos, datos agrícolas y datos de rendimiento del cultivo, facilitando una visión holística de las interacciones entre estos factores. También incluye funcionalidades de visualización de datos y generación de informes, lo que facilita la interpretación de los resultados y la toma de decisiones informadas. La validación del modelo en un entorno controlado ha demostrado su eficacia y precisión, posicionando esta herramienta como un recurso esencial para mejorar la sostenibilidad y productividad de los cultivos de cacao en condiciones climáticas variables.spa
dc.description.abstractenglishThe project "Data Analytics Tool for the Maintenance of Cocoa Crops under Scenarios of Climatic Variability" is a significant step in addressing the challenges cocoa production faces due to climatic variability. This tool is a direct response to issues such as droughts, floods, and extreme temperatures that pose a threat to the quality and quantity of the cocoa harvest. It utilizes advanced analysis to comprehend the ecological phenomena affecting cocoa production. By connecting directly with the NASA API, it acquires precise climatological data. Moreover, it implements Recurrent Neural Networks (RNN) with the Long Short-Term Memory (LSTM) model to provide reliable forecasts. The tool, developed with Python and Power BI, not only allows for the calculation and modeling of biomass but also for assessing the sensitivity of cocoa to water stress and harvest indices. This equips decision-makers with a powerful tool to navigate uncertainty in the planning horizon. The tool's standout feature is its ability to seamlessly integrate climatological data, agricultural data, and crop yield data, offering a comprehensive view of the intricate interactions between these factors. It also includes functionalities for data visualization and report generation, which greatly aids in the interpretation of results and informed decision-making. The model's validation in a controlled environment has demonstrated its effectiveness and accuracy, positioning this tool as an indispensable resource for enhancing the sustainability and productivity of cocoa crops under variable climatic conditions.spa
dc.description.degreelevelMaestríaspa
dc.description.learningmodalityModalidad Presencialspa
dc.description.tableofcontentsINTRODUCCIÓN...................................................................................................11 1. MARCO TEÓRICO............................................................................................14 1.1. Mantenimiento de cultivos de cacao bajo escenarios de variabilidad climatológica ..........................................................................................................14 1.2. Redes neuronales recurrentes........................................................................15 1.3. Metodología KDD............................................................................................16 1.4. Herramienta de analítica de datos ..................................................................18 1.5. Tecnologías y arquitecturas............................................................................20 1.5.2. Lenguaje de programación, Python .............................................................21 1.5.3. Herramientas de visualización, Power BI.....................................................22 1.5.4. Sistemas de información geográfica (SIG)...................................................23 1.5.5. Metodología de desarrollo, modelo V ..........................................................24 1.5.6. Fuentes de datos .........................................................................................25 2. MARCO METODOLÓGICO...............................................................................26 3. REVISIÓN BIBLIOGRÁFICA Y RECOPILACIÓN DE DATOS...........................27 3.1. Impacto de la Variabilidad Climática en los Cultivos de Cacao.......................27 3.2. Respuestas Fisiológicas del Cacao al Ambiente Climático.............................28 3.3. Tratamientos Agrícolas y Buenas Prácticas para Mitigar los Efectos de la Variabilidad Climática ............................................................................................28 3.4. Recopilación de datos climatológicos .............................................................28 4. DESARROLLO DEL MODELO PARA LA TOMA DE DECISIONES..................30 4.1. Conexión a la API de la NASA Power:............................................................33 4.2. Imputación de datos........................................................................................34 4.3. Modelo de predicción......................................................................................40 4.4. Funciones .......................................................................................................50 4.5. Sensibilidades.................................................................................................59 5. DISEÑO E IMPLEMENTACIÓN DE LA INTERFAZ...........................................65 5.1. Diseño de Arquitectura ...................................................................................65 5.2. Diseño de Interfaz de Usuario.........................................................................66 5.3. Dashboard ......................................................................................................73 6. VERIFICACIÓN, PRUEBAS Y DESPLIEGUE ...................................................82 7. CONCLUSIONES ..............................................................................................99 8. TRABAJOS FUTUROS....................................................................................101 BIBLIOGRAFÍA....................................................................................................102 ANEXOS..............................................................................................................107 ANEXO A.............................................................................................................107spa
dc.format.mimetypeapplication/pdfspa
dc.identifier.instnameinstname:Universidad Autónoma de Bucaramanga - UNABspa
dc.identifier.reponamereponame:Repositorio Institucional UNABspa
dc.identifier.repourlrepourl:https://repository.unab.edu.cospa
dc.identifier.urihttp://hdl.handle.net/20.500.12749/25165
dc.language.isospaspa
dc.publisher.facultyFacultad Ingenieríaspa
dc.publisher.grantorUniversidad Autónoma de Bucaramanga UNABspa
dc.publisher.programMaestría en Gestión, Aplicación y Desarrollo de Softwarespa
dc.publisher.programidMGAS-1809
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dc.relation.uriapolohttps://apolo.unab.edu.co/en/persons/leonardo-talerospa
dc.rights.accessrightsinfo:eu-repo/semantics/restrictedAccessspa
dc.rights.creativecommonsAtribución-NoComercial-SinDerivadas 2.5 Colombia*
dc.rights.localAbierto (Texto Completo)spa
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/2.5/co/*
dc.subject.keywordsSystems engineerspa
dc.subject.keywordsSoftware developmentspa
dc.subject.keywordsCocoa cultivationspa
dc.subject.keywordsClimatic variabilityspa
dc.subject.keywordsForecasting algorithmsspa
dc.subject.keywordsData analytics toolspa
dc.subject.keywordsNeural networkspa
dc.subject.keywordsBusiness intelligencespa
dc.subject.keywordsClimatologyspa
dc.subject.keywordsSoils and climatespa
dc.subject.keywordsVegetation and climatespa
dc.subject.keywordsCrops and soilsspa
dc.subject.keywordsNeural networks (Computer science)spa
dc.subject.keywordsArtificial intelligencespa
dc.subject.lembDesarrollo de Softwarespa
dc.subject.lembIngeniería de sistemasspa
dc.subject.lembClimatologíaspa
dc.subject.lembSuelos y climaspa
dc.subject.lembVegetación y climaspa
dc.subject.lembCultivos y suelosspa
dc.subject.lembRedes neuronales (Computadores)spa
dc.subject.lembInteligencia artificialspa
dc.subject.proposalCultivo de cacaospa
dc.subject.proposalHerramienta de analítica de datosspa
dc.subject.proposalAalgoritmos de predicciónspa
dc.subject.proposalRed neuronalspa
dc.subject.proposalVariabilidad climatológicaspa
dc.titleHerramienta de analítica de datos para el mantenimiento de cultivos de cacao bajo escenarios de variabilidad climatológicaspa
dc.title.translatedData analytics tool for the maintenance of cocoa crops under scenarios of climatic variabilityspa
dc.type.coarhttp://purl.org/coar/resource_type/c_bdcc
dc.type.coarversionhttp://purl.org/coar/version/c_ab4af688f83e57aaspa
dc.type.driverinfo:eu-repo/semantics/masterThesis
dc.type.hasversioninfo:eu-repo/semantics/acceptedVersion
dc.type.localTesisspa
dc.type.redcolhttp://purl.org/redcol/resource_type/TM

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