Tesis Telecomunicaciones

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Start date: 2024Subject: search.filters.subject.DETECCIÓN DE PLAGAS

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    Identificación temprana de presencia de plagas en cultivos de ambiente controlado empleando visión artificial y deep learning
    (Universidad Técnica de Ambato. Facultad de Ingeniería en Sistemas, Electrónica e Industrial. Carrera de Telecomunicaciones, 2025-02) Lascano Villafuerte Erick Fernando; Córdova Córdova Edgar Patricio
    The cultivation of crops in controlled environments offers optimal conditions for their growth. However, the presence of pests can adversely impact both the quantity and the quality of the produce. This phenomenon exerts a deleterious effect on the economic viability of farmers. To address these challenges, farmers have adopted technological solutions, such as Agriculture 5.0, to enhance their productivity and quality of produce. A study was conducted with the objective of implementing a system for pest detection, utilizing Computer Vision and Deep Learning technologies. It is imperative to detect pests in crops at an early stage to avert production losses. Consequently, the system is predicated on a neural network capable of accurately detecting various pests. The system is comprised of four distinct stages: acquisition, training, processing, and visualization. In the initial acquisition stage, four cameras were utilized to capture images and video. The training stage entailed the utilization of collected data in conjunction with a model adept at functioning with constrained resources while maintaining optimal detection accuracy. The image processing stage entailed the utilization of a microcomputer that had been optimized to operate in conjunction with artificial intelligence. The visualization and information management stage involved the development of a graphic interface capable of displaying the data obtained. The trained model demonstrated an accuracy of 95.7% in the detection of pests, and subsequent system tests yielded a reliability of 93.7%, thus confirming the system's reliability.
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    Sistema de detección temprana de plagas en cultivos de mora mediante visión artificial
    (Universidad Técnica de Ambato. Facultad de Ingeniería en Sistemas, Electrónica e Industrial. Carrera de Telecomunicaciones, 2024-08) Arequipa Tipantuña, Jonathan Marcelo; Castro Martin, Ana Pamela
    The blackberry production in Ecuador has experienced significant growth in recent years, becoming one of the most in-demand fruits. However, several factors, such as pests and diseases, affect the production and quality of this fruit, directly impacting the farmers' economy. Based on this context, the present research project focuses on the implementation of a pest and disease detection system using an artificial vision model, which serves as a tool to help farmers identify diseases in their crops quickly and efficiently. The system consists of a mobile application that integrates the artificial vision model. This model is designed to detect four types of pests with the highest incidence in the area. The application offers two detection modes: the first one through real-time video via the device's camera and the second one through image analysis, thus allowing the integration of multimedia resources for transmitting information to the model for analysis. The system has demonstrated an accuracy of 90.34% in pest detection, according to tests conducted in various environments where crops are located. The implementation of this system has significantly reduced pest identification errors by avoiding human errors and reducing economic losses by identifying pests and diseases at early stages of infection.