Sensores inteligentes y técnicas de machine learning para la detección del estrés en ganado bovino
DOI:
https://doi.org/10.63618/omd/isj/v3/n3/64Palabras clave:
Machine Learning; Ganado Bovino; Sensores Inteligentes; Stress.Resumen
Este artículo estudia el uso de la inteligencia artificial y el aprendizaje automático en la ganadería de precisión, en particular, el monitoreo del bienestar animal y la detección del estrés térmico en el ganado vacuno. Se presta especial atención a las tecnologías digitales, como los sensores inteligentes y el Internet de las cosas, que posibilitan el monitoreo continuo y no invasivo. La búsqueda se llevó a cabo con base en los artículos recientes a partir de 2020 con palabras clave relacionados con el estrés, y la ganadería de precisión. Los resultados del análisis permiten afirmar que varios algoritmos, por ejemplo, Bosque Aleatorio y XGBoost, permiten obtener una alta precisión de la predicción de la condiciones de salud. Uno de los estudios obtuvo hasta un 89,3% de precisión en la detección del estrés térmico. A pesar de los resultados prometedores, es necesario mejorar la precisión de los modelos, así como la integración de datos para una implementación efectiva.
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Derechos de autor 2025 Lascano-Rivera, Samuel Benjamín, Rivera-Escriba, Luis Antonio, Balarezo-Urresta, Luis Rodrigo, Castañeda-Albán, Jorge Eduardo (Autor/a)
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