• The Journal of Korean Institute of Information Technology
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• v.16 no.12
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• pp.127-137
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• 2018

Parturition is an important event for farmers as it provides economic gains for the farms. Thus, the effective management of parturition is essential to farm management. In particular, the unit price of cattle is higher than other livestock and the productivity of cattle is closely associated to farm income. In addition, 42% of calving occurs in the nighttime so accurate parturition predictions are all the more important. In this paper, we propose a method that accurately predicts the calving date by applying core body temperature of cattle to deep learning. The body temperature of cattle can be measured without being influenced by the ambient environment by applying an ingestible bio-sensor in the cattle's rumen. By experiment on cattle, we confirmed this method to be more accurate for predicting calving dates than existing parturition prediction methods, showing an average of 3 hour 40 minute error. This proposed method is expected to reduce the economic damages of farms by accurately predicting calving times and assisting in successful parturitions.