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Using Acceleration Data to Automatically Detect the Onset of Farrowing in Sows
Imke Traulsen1, Christoph Scheel2, Wolfgang Auer3
1Livestock Systems Group, Department of Animal Science, Georg-August University, Albrecht-Thaer Weg 3, 37075 Göttingen, Germany. imke.traulsen@uni-goettingen.de.
Sensors (Basel, Switzerland)
|January 11, 2018
Summary
This study developed an automatic system to predict farrowing in sows using ear-mounted sensors. The system reliably detected the onset of farrowing, providing early alerts for improved animal management.
Area of Science:
- Animal Science
- Agricultural Technology
- Biomedical Engineering
Background:
- Automated surveillance tools are crucial for modern animal husbandry.
- Practical farming conditions necessitate reliable monitoring systems.
- Predicting farrowing onset is vital for sow and piglet welfare.
Purpose of the Study:
- To develop an automated method for predicting farrowing in crate-confined sows.
- To evaluate the efficacy of acceleration measurements for farrowing prediction.
- To support animal surveillance in commercial farming settings.
Main Methods:
- Sows were equipped with ear sensors to record acceleration data.
- Video recordings served as a reference for sow behavior.
- Cumulative Sum (CUSUM) charts analyzed acceleration indices and signal variations.
Main Results:
- Increased sow activity, indicative of nest building, was detected before farrowing.
- A specific statistical distribution and signal transformation reliably identified farrowing.
- Alarms were issued 48 hours (100% of sows) or 12 hours (85% of sows) prior to farrowing.
Conclusions:
- Ear-mounted acceleration sensors are effective for predicting farrowing in individually housed sows.
- Automated detection supports timely interventions in farrowing management.
- This technology enhances precision livestock farming and animal welfare.
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