Browsing by Author "Lascano Villafuerte Erick Fernando"

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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.