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Prediction of Cow Calving in Extensive Livestock Using a New Neck-Mounted Sensorized Wearable Device: A Pilot Study.
Carlos González-Sánchez1, Guillermo Sánchez-Brizuela1, Ana Cisnal1
1ITAP (Instituto de las Tecnologías Avanzadas de la Producción), Universidad de Valladolid, Paseo del Cauce 59, 47011 Valladolid, Spain.
Sensors (Basel, Switzerland)
|December 10, 2021
Summary
A new wearable sensor helps farmers detect calving by monitoring cow behavior. Analyzing lying and standing transitions shows potential for early calving prediction in livestock farming.
Area of Science:
- Agricultural Engineering
- Animal Science
- Biotechnology
Background:
- Early detection of calving is crucial for optimizing livestock management and animal welfare.
- Existing methods for calving detection can be labor-intensive and may lack precision in extensive farming systems.
Purpose of the Study:
- To develop and evaluate a low-cost, neck-mounted wearable sensor device for detecting the onset of calving in cattle.
- To test the hypothesis that changes in lying-standing behavior (lying bouts) can predict calving events.
Main Methods:
- A sensorized wearable device integrating an Inertial Measurement Unit (IMU), Global Navigation Satellite System (GNSS) receiver, and thermometer was developed.
- A novel algorithm was created to analyze the frequency and duration of lying and standing postures for real-time processing on an embedded microcontroller.
- Six cows were monitored on an extensive livestock farm, with data collected from August 2020 to July 2021.
Main Results:
- Preliminary data suggest a correlation between lying-standing transitions and the prediction of calving.
- The developed algorithm demonstrated the feasibility of real-time data processing with minimal computational resources.
Conclusions:
- The study indicates that monitoring animal states and transitions between lying and standing postures holds promise for predicting calving.
- Further research with larger datasets is necessary to refine the calving detection algorithm.
