Sistema de detección temprana de plagas en cultivos de mora mediante visión artificial

Abstract

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.