Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.12394/18429
Title: Improvement Of The Hass Avocado Selection Process For Export By Means Of Artificial Intelligence And An Automated Mechanical System
Other Titles: Mejora del proceso de selección de aguacate Hass para exportación mediante inteligencia artificial y un sistema mecánico automatizado
Authors: Escalante Talavera, Jhuliza Jhunely
Osores Huisa, Sandra Lesli
Gabriel Vilcahuaman, Cesar
Chávez Castillo, Rodolfo Antonio
metadata.dc.contributor.advisor: Chávez Castillo, Rodolfo Antonio
Keywords: Automatización
Automation
Inteligencia artificial
Artificial intelligence
Ingeniería industrial
Industrial engineering
Publisher: Universidad Continental.
Issue Date: 2025
metadata.dc.date.available: 18-Nov-2025
Citation: Escalante, J., Osores, S., Gabriel, C., et al. (2025). Improvement Of The Hass Avocado Selection Process For Export By Means Of Artificial Intelligence And An Automated Mechanical System [Tesis de licenciatura, Universidad Continental]. Repositorio Institucional Continental. https://repositorio.continental.edu.pe/handle/20.500.12394/18429
metadata.dc.identifier.doi: https://doi.org/10.1109/ICAACE65325.2025.11019237
Abstract: The research comprehensively addresses the challenges and opportunities in the production and grading of Hass avocado, a product of vital importance in the agricultural industry [1], analyzing key aspects such as the production and demand of Hass avocado, highlighting its relevance both nationally and globally. The research identifies the inherent limitations of manual avocado sorting, which leads to errors and long processing times, impacting the efficiency and quality of the final product. To address these challenges, the application of industrial engineering tools such as the Process Operations Diagram (POD), the Process Analysis Diagram (PAD), the Pareto Diagram and the Flow Diagram are proposed to identify critical areas for improvement and optimize the sorting processes. In addition, the use of advanced technologies such as YOLOv8, a computer vision tool, is used to automate and improve the accuracy of avocado grading. The implementation of these tools and technologies aims to improve efficiency, accuracy and profitability in the grading of quality Hass avocados. By using the PDO and PAD, existing processes can be identified and analyzed, highlighting areas of opportunity for optimization and automation. The Pareto Diagram allows prioritization of the most critical issues, while the Flow Chart provides a visual representation of the current and proposed workflow. Finally, the integration of YOLOv8 in the monitoring and classification system of Hass avocados has transformed the agricultural processes, obtaining a predictive model based on its products in the identification of fruit suitable for export. This system integrates a drone with vision sensors and an automated sorting machine, completing the entire process in just 56 seconds, which represents an improvement of 47.98% compared to the manual method. With a total implementation cost of $6,156.72, this solution not only ensures high efficiency and quality in avocado handling, but also presents itself as a technologically viable and sustainable alternative to increase productivity and competitiveness in the agricultural industry.
metadata.dc.relation: https://www.researchgate.net/publication/392533560_Improvement_of_the_Hass_Avocado_Selection_Process_for_Export_by_Means_of_Artificial_Intelligence_and_an_Automated_Mechanical_System
Extension: [4] páginas.
metadata.dc.rights.accessRights: Acceso restringido
metadata.dc.source: Universidad Continental
Repositorio Institucional - Continental
Appears in Collections:Tesis

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IV_FIN_108_TE_Escalante_Osores_Gabriel_Chávez_2025.pdfEscalante Talavera, Jhuliza Jhunely; Osores Huisa, Sandra Lesli; Gabriel Vilcahuaman, Cesar; Chávez Castillo, Rodolfo Antonio656.94 kBAdobe PDFView/Open
IV_FIN_108_Autorización_2025.pdf
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