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dc.contributor.advisorTalero Sarmiento, Leonardo Hernánspa
dc.contributor.advisorCoronado Silva, Roberto Antoniospa
dc.contributor.authorHeredia Gómez, Juan Felipespa
dc.contributor.authorRueda Gómez, Juan Pablospa
dc.contributor.authorRamírez Acuña, Juan Sebastiánspa
dc.coverage.spatialColombiaspa
dc.date.accessioned2021-01-28T16:29:07Z
dc.date.available2021-01-28T16:29:07Z
dc.date.issued2020
dc.identifier.urihttp://hdl.handle.net/20.500.12749/12070
dc.description.abstractEl presente proyecto presenta una solución para la etapa de madurez en el ciclo productivo del cacao, dado que una cosecha oportuna es uno de los factores que inciden en el rendimiento del producto (medido en “peso de granos recolectado/ unidad de área cosechada”). Teniendo en cuenta lo anterior, durante la etapa de revisión de antecedentes y estado del arte se identificó la oportunidad de generar una solución que permita reducir las imprecisiones generadas por la inspección visual (al ser un proceso completamente manual y no estandarizado), ya que ésta se ve afectada por distintas variaciones tales como problemas de visión, la cantidad de horas luz al que es expuesto un fruto de cacao, las características del suelo y sus respectivos nutrientes, y la altura de la plantación. La interacción de los factores mencionados previamente incide en que los colores que puede tomar una misma variedad de mazorca de cacao no sean uniformes a lo largo de la misma unidad productiva, y menos en otra ubicación. Así mismo, la ingente cantidad de variedades de cacao, hacen que la identificación del estado de madurez de la mazorca sea un proceso abstruso, por consiguiente, en este proyecto se seleccionó la variedad TCS-01 (Theobroma Corpoica La suiza 01), ya que esta posee un rendimiento mejor en comparación con otras variedades disponibles de AGROSAVIA, además, tiene un récord en tamaño de grano y, por último, es endémica de Santander. Esta variedad en específico presenta un inconveniente, ya que sus granos tienden a germinarse en un estado final de madurez, a causa de los factores anteriormente mencionados y la precoz germinación de esta variedad. Con miras en remediar la pérdida de producción por la presencia de granos maduros dentro de la mazorca, se propone el desarrollo de una herramienta fácilmente transferible que le ayude al cacaotero a identificar el estado de madurez de la mazorca cuando no tenga una plena certeza, además de sentar una base tecnológica para futuros desarrollos en esta área y, por último, promover el uso de variedades autóctonas en la región para aquellos agricultores que se encuentran incursionando, aportando así la información necesaria para su capacitación.spa
dc.description.tableofcontents1. RESUMEN 11 2. PLANTEAMIENTO DEL PROBLEMA 12 2.1. DEFINICIÓN DEL PROBLEMA 12 2.2. JUSTIFICACIÓN DEL PROYECTO 13 3. OBJETIVOS 17 3.1. OBJETIVO GENERAL 17 3.2. OBJETIVOS ESPECÍFICOS 17 4. RESULTADOS ESPERADOS 18 4.1. OBJETIVO ESPECÍFICO 1 18 4.2. OBJETIVO ESPECÍFICO 2 18 4.3. OBJETIVO ESPECÍFICO 3 18 4.4. OBJETIVO ESPECÍFICO 4 18 5. REVISIÓN DE LA LITERATURA 20 5.1. APARTADO UNO 20 5.1.1. Máquina de vectores de soporte (Support Vector Machine – SVM) 23 5.1.2. Red neuronal Artificial (Artificial Neural Network - ANN) 23 5.1.3. K- Vecino más cercano (K-Nearest Neighboor - KNN) 24 5.1.4. Múltiples técnicas 24 5.1.5. Tratamiento de las imágenes 24 5.2. APARTADO DOS 25 5.2.1. Tomates 26 5.2.2. Bananos 27 5.2.3. Papaya 28 5.2.4. Manzanas 29 5.2.5. Pimentón 29 5.2.6. Método de captura de datos 29 5.3. CONCLUSIONES DE LA REVISIÓN 29 6. MARCO TEÓRICO 32 6.1. AGRICULTURA Y CACAO 32 6.1.1. Agricultura 32 6.1.2. Etapas del ciclo agrícola 33 6.1.3. Cacao criollo 34 6.1.4. Cacao forastero 35 6.1.5. Cacao trinitario 36 6.1.6. Teobroma Corpoica La Suiza 01 (TCS-01) 37 6.1.7. Etapa de madurez 37 6.2. INTELIGENCIA ARTIFICIAL 38 6.2.1. ¿Cómo aprende una maquina? 39 6.2.2. Inteligencia artificial 39 6.2.3. Aprendizaje automático 40 6.2.4. Tipos de aprendizaje 41 6.2.5. Técnicas de aprendizaje: 41 6.2.6. WEKA 55 6.2.7. YOLO 55 6.2.8. Darkflow 55 6.2.9. TensorFlow 55 6.3. PROCESAMIENTO DE IMÁGENES 56 6.3.1. Procesamiento de imágenes digitales a color 56 6.3.2. Definición de imágenes digitales 56 6.3.3. Herramientas 57 6.3.4. Convolución 57 6.3.5. Propiedades 57 6.3.6. Transformada de Fourier 58 6.3.7. Conceptos fundamentales del color 59 6.3.8. Modelos de color 61 6.3.9. Segmentación de imágenes 63 6.4. HERRAMIENTAS DE SOPORTE 66 6.4.1. LabelImg: 67 6.4.2. Android Studio: 67 6.4.3. NDK: 68 7. DISEÑO METODOLÓGICO 69 7.1. METODOLOGÍA DE LA INVESTIGACIÓN 69 7.2. METODOLOGÍA DE LA CONSOLIDACIÓN DEL DATASET 73 7.3. METODOLOGÍA DE LA DESARROLLO DE SOFTWARE 74 7.3.1. El conjunto de datos 74 7.3.2. Aplicación de estimación del nivel de madurez “DELECO” 75 8. DISCUSIÓN DE RESULTADOS 80 8.1. ARTICULO CIENTÍFICO Y FUNDAMENTO TEÓRICO 80 8.2. DATASET 80 8.3. MODELO 83 8.4. APLICATIVO MÓVIL 85 9. CONCLUSIONES 87 10. BIBLIOGRAFÍA 88spa
dc.format.mimetypeapplication/pdfspa
dc.language.isospaspa
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/2.5/co/*
dc.titleAplicación para estimar el nivel de madurez en las mazorcas de cacao haciendo uso de visión por computador y aprendizaje de máquina “DELECO”spa
dc.title.translatedApplication to estimate the level of maturity in cocoa pods using computer vision and machine learning "DELECO"spa
dc.degree.nameIngeniero de Sistemasspa
dc.publisher.grantorUniversidad Autónoma de Bucaramanga UNABspa
dc.rights.localAbierto (Texto Completo)spa
dc.publisher.facultyFacultad Ingenieríaspa
dc.publisher.programPregrado Ingeniería de Sistemasspa
dc.description.degreelevelPregradospa
dc.type.driverinfo:eu-repo/semantics/bachelorThesis
dc.type.localTrabajo de Gradospa
dc.type.coarhttp://purl.org/coar/resource_type/c_7a1f
dc.subject.keywordsSystems engineereng
dc.subject.keywordsTechnological innovationseng
dc.subject.keywordsCacao production cycleeng
dc.subject.keywordsComputer visioneng
dc.subject.keywordsAgricultural administrationeng
dc.subject.keywordsCropseng
dc.subject.keywordsFarmingeng
dc.subject.keywordsMarket economyeng
dc.identifier.instnameinstname:Universidad Autónoma de Bucaramanga - UNABspa
dc.identifier.reponamereponame:Repositorio Institucional UNABspa
dc.type.hasversioninfo:eu-repo/semantics/acceptedVersion
dc.rights.accessrightsinfo:eu-repo/semantics/openAccessspa
dc.rights.accessrightshttp://purl.org/coar/access_right/c_abf2spa
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dc.contributor.cvlachttps://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0000031387*
dc.contributor.orcidhttps://orcid.org/0000-0002-4129-9163*
dc.contributor.researchgatehttps://www.researchgate.net/profile/Leonardo_Talero*
dc.subject.lembIngeniería de sistemasspa
dc.subject.lembInnovaciones tecnológicasspa
dc.subject.lembAdministración agrícolaspa
dc.subject.lembCultivosspa
dc.subject.lembAgriculturaspa
dc.subject.lembEconomía de mercadospa
dc.identifier.repourlrepourl:https://repository.unab.edu.cospa
dc.description.abstractenglishThis project presents a solution for the maturity stage in the cocoa production cycle, since a timely harvest is one of the factors that affect the yield of the product (measured in "weight of beans harvested / unit of harvested area") . Taking into account the above, during the background and state of the art review stage, the opportunity was identified to generate a solution that allows reducing the inaccuracies generated by visual inspection (as it is a completely manual and non-standardized process), since this It is affected by different variations such as vision problems, the amount of light hours to which a cocoa fruit is exposed, the characteristics of the soil and its respective nutrients, and the height of the plantation. The interaction of factors mentioned previously affects the fact that the colors that the same variety of cocoa pod can take are not uniform throughout the same production unit, and less so in another location. Likewise, the huge number of cocoa varieties make the identification of the pod's state of maturity an abstruse process, therefore, in this project the TCS-01 variety (Theobroma Corpoica La suiza 01) was selected, since it has a better yield compared to other varieties available from AGROSAVIA, in addition, it has a record in grain size and, finally, it is endemic to Santander. This specific variety has a drawback, since its grains tend to germinate in a final state of maturity, due to the aforementioned factors and the early germination of this variety. With a view to remedying the loss of production due to the presence of ripe grains inside the pod, the development of an easily transferable tool is proposed to help the cocoa farmer to identify the state of maturity of the pod when they are not fully certain, in addition to lay a technological base for future developments in this area and, finally, to promote the use of indigenous varieties in the region to those farmers who are making incursions, thus providing the necessary information for their training.eng
dc.subject.proposalCiclo productivo del cacaospa
dc.subject.proposalVisión por computadorspa
dc.subject.proposalDELECOspa
dc.type.redcolhttp://purl.org/redcol/resource_type/TP
dc.rights.creativecommonsAtribución-NoComercial-SinDerivadas 2.5 Colombia*
dc.coverage.campusUNAB Campus Bucaramangaspa
dc.description.learningmodalityModalidad Presencialspa


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