Revisión sistemática de literatura sobre soluciones computacionales aplicadas a la agricultura: diagnóstico visual de enfermedades, clasificación poscosecha y monitoreo inteligente mediante IoT

La agricultura enfrenta desafíos crecientes en el diagnóstico de enfermedades, la evaluación de la calidad poscosecha y la gestión de fincas. Las soluciones computacionales basadas en inteligencia artificial, visión por computador e IoT apoyan la toma de decisiones. Este artículo presenta una revisión sistemática de literatura (RSL) que analiza y sintetiza la evidencia reciente sobre enfoques computacionales aplicados a (1) detección automática de enfermedades en hojas y frutos agrícolas, (2) clasificación superficial y evaluación de calidad poscosecha de granos y (3) monitoreo y gestión de fincas mediante plataformas web e IoT. La RSL siguió los lineamientos de Kitchenham y el protocolo PRISMA, aplicando criterios explícitos de búsqueda, selección, evaluación de calidad y síntesis. De 263 registros iniciales, se incluyeron 16 estudios primarios: 6 sobre diagnóstico visual de enfermedades (Eje A), 3 sobre clasificación poscosecha de granos (Eje B) y 7 sobre monitoreo agrícola mediante IoT y plataformas web (Eje C). Los resultados muestran que el aprendizaje profundo (redes neuronales convolucionales, mecanismos de atención y modelos preentrenados) domina el diagnóstico visual y la clasificación poscosecha. Se evidencia un énfasis en infraestructuras IoT para monitoreo, aunque con atención limitada a la usabilidad y a la aplicación sistemática de estándares como ISO 9241. A diferencia de revisiones previas, esta RSL estructura la evidencia por problemas concretos, integrando diagnóstico visual, clasificación y monitoreo en un análisis unificado. Finalmente, se identifican brechas en generalización de modelos, estandarización de los conjuntos de datos y validación en campo, orientando futuras investigaciones en computación aplicada a la agricultura.

https://doi.org/10.61854/rccedia.v1n1.007

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Derechos de autor 2026 Luis Chamba Eras, Sergio Jumbo-Gonza, Walter Yaguana-Alejandro, Geovanny Romero-Suquilanda, Gerardo Herrera-Campoverde