Browsing by Author "Hidalgo Segovia Oscar Gustavo"

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    Sistema para la caracterización de enfermedades de cultivos de cebolla mediante el uso de procesamiento digital de imágenes
    (Universidad Técnica de Ambato. Facultad de Ingeniería en Sistemas, Electrónica e Industrial. Carrera de Telecomunicaciones, 2025-02) Hidalgo Segovia Oscar Gustavo; Guamán Molina Jesús Israel
    Modern agriculture faces critical challenges related to disease detection and management in high-value crops such as onion, an essential commodity with an annual global production of approximately 300 million tons. This project proposes an innovative system for disease characterization in onion crops using digital image processing, IoT and artificial intelligence. The system integrates sensors to collect key environmental data, such as temperature, humidity and UV radiation, which are stored in a MongoDB database. This data is visualized with Chart.js, complementing digital image analysis to detect diseases such as Botrytis squamosa and powdery mildew. Through advanced deep learning algorithms, such as YOLOv8, the system identifies visual patterns associated with diseases, enabling early disease detection. The implementation of the system comprises four stages: data acquisition through sensors and cameras, preprocessing using OpenCV, training of models based on neural networks, and visualization of results through graphical interfaces. This integrated approach not only optimizes disease detection and management, but also improves efficiency in agricultural decision making, reducing losses and maximizing productivity. Thus, it contributes significantly to the sustainability of the agricultural sector, especially in regions with low technification such as Tungurahua, Ecuador