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dc.contributor.advisorDe Farías, Claudio Miceli
dc.contributor.advisorTalavera Portocarrero, Jesús Martín
dc.contributor.advisorCabrera Cruz, José Daniel
dc.contributor.advisorBayona Rodríguez, Cristihian Jarri
dc.contributor.authorCulman Forero, María Alejandra
dc.date.accessioned2020-06-26T21:35:50Z
dc.date.available2020-06-26T21:35:50Z
dc.date.issued2018-03
dc.identifier.urihttp://hdl.handle.net/20.500.12749/3549
dc.description.abstractDado que la agricultura es la actividad humana más dependiente de las condiciones climáticas, es vital que los agricultores tomen decisiones bien informadas. Desafortunadamente en Colombia, los agricultores generalmente tienden a decidir sobre una base de conocimiento limitada y esto somete sus sistemas productivos a la incertidumbre generada por la variabilidad y el cambio climático. Las causas de este problema se pueden resumir en tres situaciones: los agricultores no tienen acceso a información agrometeorológica y a previsiones agroclimáticas a nivel local; los agricultores no tienen la competencia para tomar decisiones basadas en la información; y los agricultores no tienen el recurso económico para respaldar sus decisiones. Este Trabajo de investigación se centra en atender la segunda causa, respecto a llevar la información agrometeorológica a información accionable para apoyar la toma de decisiones en la gestión del cultivo de palma de aceite. Suponiendo un escenario agrícola donde está desplegada una Red Inalámbrica de Sensores para adquirir datos locales y representativos en el campo, se formuló un método de Fusión de Datos que apoya la gestión del riego al inferir el estado del cultivo y decidir sobre la necesidad de riego. El método compromete dos niveles, un primer nivel de decisión que combina datos de la humedad del suelo, la temperatura ambiente y la humedad relativa para decidir sí regar o no regar el lote de cultivo mediante la técnica de Inferencia Dempster–Shafer; y un segundo nivel de evaluación a la decisión que combina datos de la evapotranspiración de cultivo, la precipitación y la decisión de riego en el lote de cultivo para calificar el desempeño de la decisión en el contexto de la plantación mediante la técnica de Lógica Difusa. El impacto del método en la gestión del cultivo de palma de aceite fue establecido por medio de la simulación de dos escenarios: lote de cultivo con riego gestionado por el primer nivel del método, y lote de cultivo sin riego. Los resultados indican un impacto potencial de incrementar en un 27% el rendimiento del cultivo, gracias a las decisiones de riego tomadas por el método.spa
dc.description.tableofcontentsINTRODUCCIÓN 24 1. DESCRIPCIÓN DEL TRABAJO 28 1.1 PROBLEMA 28 1.2 PREGUNTA DE INVESTIGACIÓN 31 1.3 MOTIVACIÓN 31 1.4 HIPÓTESIS 32 1.5 JUSTIFICACIÓN 33 2. OBJETIVOS 36 2.1 GENERAL 36 2.2 ESPECÍFICOS 36 3. MARCO REFERENCIAL 37 3.1 MARCO CONCEPTUAL 37 3.1.1 Fusión de Datos 37 3.1.2 Método a partir de la Fusión de Datos basado en la Inferencia 39 3.1.3 Redes Inalámbricas de Sensores 40 3.1.4 Telemática 40 3.1.5 Agrometeorología 40 3.1.6 Naturaleza de los datos agrometeorológicos 41 3.1.7 Gestión del cultivo de palma de aceite 42 3.2 MARCO TEÓRICO 47 3.2.1 Fusión de datos aplicada a sensores 47 3.2.2 Técnicas de Fusión de Datos basadas en la Inferencia 49 3.2.3 Agrometeorología y Redes Inalámbricas de Sensores 54 3.2.4 Agricultura ante los cambios tecnológicos y climáticos 56 3.3 ESTADO DEL ARTE 59 3.3.1 Soluciones que integran Redes Inalámbricas de Sensores y Fusión de Datos para apoyar la toma de decisiones en la agricultura 60 3.3.2 Soluciones que integran Redes Inalámbricas de Sensores y otras áreas para apoyar la toma de decisiones en la agricultura 64 3.3.3 Síntesis sobre las soluciones reportadas y la toma de decisiones en la agricultura 68 3.4 MARCO CONTEXTUAL Y ANTECEDENTES 70 3.4.1 La palma de aceite en Colombia 70 3.4.2 Corporación Centro de Investigación en Palma de Aceite – CENIPALMA 71 3.4.3 Iniciativas en el territorio colombiano para una agricultura climáticamente inteligente 72 3.4.4 Red Temática CYTED RiegoNets 74 3.4.5 Centro de Excelencia y Apropiación en Internet de las Cosas – CEA–IoT 75 3.5 MARCO LEGAL Y NORMATIVO 77 4. ASPECTOS METODOLÓGICOS 78 4.1 ENFOQUE Y TIPO DE INVESTIGACIÓN 78 4.2 UNIVERSO Y MUESTRA 79 4.2.1 Universo y muestra para recolección de información 79 4.2.2 Universo con potencial de ser impacto por contribuciones 80 4.3 TÉCNICAS E INSTRUMENTOS DE RECOLECCIÓN DE DATOS 80 4.4 ACTIVIDADES REALIZADAS 80 4.4.1 Fase 1: análisis de técnicas de Fusión de Datos y oportunidades de investigación 81 4.4.2 Fase 2: propuesta de un método, utilizando una técnica de Fusión de Datos basada en la Inferencia 83 4.4.3 Fase 3: comparación del comportamiento agronómico de parcelas de palma de aceite 85 5. FUSIÓN DE DATOS APLICADA A REDES INALÁMBRICAS DE SENSORES PARA APOYAR LA TOMA DE DECISIONES EN AGRICULTURA: TÉCNICAS Y OPORTUNIDADES DE INVESTIGACIÓN 87 5.1 REVISIÓN DE LA LITERATURA 87 5.1.1 Preguntas de investigación 88 5.1.2 Proceso de búsqueda 89 5.1.3 Criterios de exclusión, inclusión y calidad 91 5.1.4 Extracción de datos 93 5.1.5 Resultados de la búsqueda 94 5.2 TÉCNICAS DE FUSIÓN DE DATOS APLICADAS A INFORMACIÓN RECOLECTADA POR REDES INALÁMBRICAS DE SENSORES PARA APOYAR LA TOMA DE DECISIONES EN AGRICULTURA 97 5.3 OPORTUNIDADES DE INVESTIGACIÓN EN REDES INALÁMBRICAS DE SENSORES Y FUSIÓN DE DATOS PARA APOYAR LA TOMA DE DECISIONES EN AGRICULTURA 112 5.3.1 Problemas abiertos en Redes Inalámbricas de Sensores y Fusión de Datos 112 5.3.2 Oportunidades de investigación en Redes Inalámbricas de Sensores y Fusión de Datos 114 6. MÉTODO DE FUSIÓN DE DATOS APLICADO A REDES INALÁMBRICAS DE SENSORES PARA APOYAR LA TOMA DE DECISIONES EN LA GESTIÓN DE CULTIVOS DE PALMA DE ACEITE 118 6.1 SOBRE LA PALMA DE ACEITE 118 6.1.1 Relación entre el suelo, el cultivo y el clima en la productividad de la palma de aceite 119 6.1.2 Información agrometeorológica disponible en palma de aceite en Colombia 125 6.1.3 Decisiones para apoyar la gestión del cultivo de palma de aceite 130 6.2 MÉTODO DE FUSIÓN DE DATOS AGROMETEOROLÓGICOS 148 6.2.1 Fusión de datos a nivel de lote 149 6.2.2 Fusión de datos a nivel de plantación 164 6.3 VALIDACIÓN DEL MÉTODO DE FUSIÓN DE DATOS AGROMETEOROLÓGICOS 180 6.3.1 Simulación de la fusión de datos a nivel de lote 180 6.3.2 Simulación de la fusión de datos a nivel de plantación 193 7. COMPORTAMIENTO AGRONÓMICO DE PARCELAS PARA MEDIR EL IMPACTO DEL MÉTODO DE FUSIÓN DE DATOS EN LA GESTIÓN DEL RIEGO EN CULTIVOS DE PALMA DE ACEITE 203 7.1 SIMULACIÓN DEL COMPORTAMIENTO AGRONÓMICO DEL LOTE DE ESTUDIO 203 7.2 COMPORTAMIENTO AGRONÓMICO DEL LOTE DE ESTUDIO BAJO DOS ESCENARIOS: CON RIEGO Y SIN RIEGO 212 7.2.1 Resultados de la simulación del comportamiento agronómico del lote de estudio 212 7.2.2 Impacto del método de inferencia en la productividad e ingresos del cultivo de palma de aceite 219 8. CONCLUSIONES 222 8.1 CONCLUSIONES 222 8.2 CONTRIBUCIONES 225 8.3 TRABAJO FUTURO 228 REFERENCIAS 231 ANEXOS 287spa
dc.format.mimetypeapplication/pdf
dc.language.isospa
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/2.5/co/*
dc.titleMétodo de fusión de datos aplicado a redes inalámbricas de sensores para apoyar la toma de decisiones en la gestión de cultivos de palma de aceitespa
dc.title.translatedData fusion method applied to wireless sensor networks to support decision-making in the management of oil palm cropseng
dc.degree.nameMagíster en Telemática
dc.coverageBucaramanga (Colombia)
dc.publisher.grantorUniversidad Autónoma de Bucaramanga UNAB
dc.rights.localAbierto (Texto Completo)spa
dc.publisher.facultyFacultad Ingenierías
dc.publisher.programMaestría en Telemática
dc.description.degreelevelMaestría
dc.type.driverinfo:eu-repo/semantics/masterThesis
dc.type.localTesisspa
dc.type.coarhttp://purl.org/coar/resource_type/c_bdcc
dc.subject.keywordsSystems Engineering
dc.subject.keywordsTelematics
dc.subject.keywordsWireless communication systems
dc.subject.keywordsWireless technology
dc.subject.keywordsElectronic data processing
dc.subject.keywordsInvestigations
dc.subject.keywordsAnalysis
dc.subject.keywordsDecision support
dc.subject.keywordsAgriculture
dc.subject.keywordsData fusion
dc.subject.keywordsOil palm
dc.subject.keywordsCrop management
dc.subject.keywordsWireless sensor networks
dc.identifier.instnameinstname:Universidad Autónoma de Bucaramanga - UNAB
dc.identifier.reponamereponame:Repositorio Institucional UNAB
dc.type.hasversioninfo:eu-repo/semantics/acceptedVersion
dc.rights.accessrightsinfo:eu-repo/semantics/openAccess
dc.rights.accessrightshttp://purl.org/coar/access_right/c_abf2
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dc.description.cvlachttps://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0000069035
dc.description.googlescholarhttps://scholar.google.es/citations?hl=es#user=hses_w0AAAAJ
dc.identifier.orcidhttps://orcid.org/0000-0002-1815-5057
dc.description.researchgatehttps://www.researchgate.net/profile/Jose_Cabrera_Cruz
dc.subject.lembIngeniería de sistemasspa
dc.subject.lembTelemáticaspa
dc.subject.lembSistemas de comunicación inalámbricaspa
dc.subject.lembTecnología inalámbricaspa
dc.subject.lembProcesamiento electrónico de datosspa
dc.subject.lembInvestigacionesspa
dc.subject.lembAnálisisspa
dc.description.abstractenglishSince agriculture is the human activity most dependent on climatic conditions, it is vital that farmers make informed decisions. Unfortunately, in Colombia, farmers tend to decide on a limited knowledge base, and this subjects their production systems to the uncertainty generated by climate variability and change. The causes of this problem can be summarized in three situations: farmers do not have access to agrometeorological information and agroclimatic forecasts at the local level, farmers do not have the competence to make decisions based on the information, and farmers do not have the economic resource to back their decisions. This research work focuses on addressing the second cause, about bringing the agrometeorological information to actionable information to support decision making in the management of oil palm cultivation. Assuming an agricultural scenario where a Wireless Sensor Network is deployed to acquire local and representative data in the field, a Data Fusion method was formulated that supports irrigation management by inferring the state of the crop and deciding on the need for irrigation. The method involves two levels, the first level of decision that combines data on soil moisture, ambient temperature, and relative humidity to decide whether to water or not irrigate the crop plot using the Dempster-Shafer Inference technique. And the second level of evaluation to the decision, which combines data of the crop evapotranspiration, precipitation and the decision of irrigation in the crop plot to qualify the performance of the decision in the context of the plantation using the Fuzzy Logic technique. The impact of the method in the management of oil palm cultivation was established through the simulation of two scenarios: crop plot with irrigation managed by the first level of the method, and crop plot without irrigation. The results indicate a potential impact of increasing crop yield by 27%, thanks to the irrigation decisions made by the method.eng
dc.subject.proposalSoporte a la decisiónspa
dc.subject.proposalFusión de datosspa
dc.subject.proposalAgrometeorologíaspa
dc.subject.proposalPalma de aceitespa
dc.subject.proposalGestión del cultivospa
dc.subject.proposalRedes Inalámbricas de sensoresspa
dc.rights.creativecommonsAtribución-NoComercial-SinDerivadas 2.5 Colombia*


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