Agriculture faces significant challenges, such as the excessive use of insecticides that affects product quality and optimizes production. Precision agriculture, driven by artificial intelligence (AI), is an alternative to improve efficiency, reduce environmental impact, and increase productivity. This technology allows the precise measurement of variables, facilitating real‑time decision‑making. Pest monitoring is crucial, as their presence can reduce crop yield. Early detection through automated monitoring systems is an essential alternative to prevent damage. AI and machine learning (ML) are fundamental for data analysis and the precise identification of pests in real-time, optimizing decision-making. Automated monitoring systems, such as image‑based ones, offer advantages over traditional manual methods, enabling pest detection with high precision. These technologies improve agricultural production efficiency and promote more sustainable practices by reducing human intervention.

Rodríguez‑Vázquez E., Hernández‑Rodríguez M., Aguirre‑Uribe L.A., Castro‑del Ángel E., Lara‑Viveros F.M., Hernández‑Juárez A. (2025). Sistemas automáticos de monitoreo, nueva herramienta para la detección temprana de insectos plaga. Revisión bibliográfica. ITEA‑Información Técnica Económica Agraria 121(4): 331-353. https://doi.org/10.12706/itea.2025.011

Consejo Nacional de Humanidades Ciencias y Tecnologías (CONAHCYT), Universidad Autónoma Agraria Antonio Narro (proyecto 436) y Centro de Investigación en Química Aplicada (proyecto interno 6706)