Reconocimiento automático de la actividad de vacunos en pastoreo

  • John Fredy Ramirez Agudelo Universidad de Antioquia
  • Sebastian Bedoya Mazo Universidad de Antioquia
  • Sandra Lucia Posada Ochoa Universidad de Antioquia
  • Jaime Ricardo Rosero Noguera Universidad de Antioquia
Palabras clave: Aplicaciones Android, Acelerómetros, Tensorflow, Comportamiento Animal, Ganadería de Precisión


El uso de podómetros o collares para registrar el comportamiento del ganado en períodos cortos de tiempo (e.g. 24 h) es costoso. En esta situación particular, el desarrollo de tecnologías de bajo costo y fáciles de usar es relevante. Al igual que las aplicaciones de teléfonos inteligentes para el reconocimiento de la actividad humana, las cuales analizan datos de sensores de aceleración integrados, en este trabajo desarrollamos una aplicación de Android para registrar la actividad del ganado. Para el desarrollo de esta aplicación, se siguieron cuatro pasos principales: a) adquisición de datos para el entrenamiento del modelo, b) entrenamiento del modelo, c) desarrollo de la aplicación y d) utilización de la aplicación. Para la adquisición de datos, desarrollamos un sistema en el que se utilizaron tres componentes: dos teléfonos inteligentes (uno en la vaca y otro para el observador) y una cuenta de Google Firebase para el almacenamiento de datos. Para el entrenamiento del modelo, la base de datos generada se utilizó para entrenar una red neuronal recurrente. El rendimiento del entrenamiento se evaluó mediante la matriz de confusión. Para todas las actividades, el modelo entrenado proporcionó una predicción alta (> 96 %). El modelo entrenado se utilizó para desarrollar una aplicación de Android con la API de TensorFlow. Finalmente, se utilizaron tres teléfonos celulares (LG gm730) para registrar la actividad de seis vacas Holstein (3 en producción y 3 secas). Se realizaron observaciones directas y no sistemáticas de los animales para contrastar las actividades registradas por el dispositivo. Los resultados mostraron coherencia entre las observaciones directas y la actividad registrada por el dispositivo.


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Comportamiento animal

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Cómo citar
Ramirez Agudelo, J. F., Bedoya Mazo, S., Posada Ochoa, S. L. ., & Rosero Noguera, J. R. . (2022). Reconocimiento automático de la actividad de vacunos en pastoreo. Biotecnología En El Sector Agropecuario Y Agroindustrial, 20(2), 117–128.
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