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AI Analysis Method Utilizing Ingestible Bio-Sensors for Bovine Calving Predictions

  • 투고 : 2018.11.21
  • 심사 : 2018.12.17
  • 발행 : 2018.12.31

초록

가축의 분만은 농가의 재산을 늘릴 수 있는 중요한 수단이므로 이를 관리하는 것은 농업 경영에 필수적인 항목이다. 특히 축우는 다른 가축에 비해 단가가 높고, 생산성 측면에서 농가의 소득과 밀접히 연관되어 있으며 축우의 42%는 밤에 분만이 이루어지고 있어 정확한 분만 예측은 더 중요하다고 할 수 있다. 그리하여 본 논문에서는 경구 투여용 센서를 통해 반추위 내의 심부 체온을 외부 환경의 간섭 없이 안정적으로 실시간 측정하고 이를 딥러닝에 적용함으로써 분만 시점을 예측하는 방법을 제안 하였고, 실제 축우를 대상으로 실험을 수행한 결과 실제 분만 시간 대비 평균 3시간 40분의 오차만 보여 기존 분만 예측 방법보다 정확하게 분만일을 예측하는 것을 확인하였다. 제안하는 방법을 통해 축우의 분만을 정확하게 예측하여 난산의 위험 없이 성공적으로 분만 하도록 도움을 줌으로써 농가의 경제적 피해를 절감할 수 있을 것으로 기대한다.

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.

키워드

과제정보

연구 과제 주관 기관 : Korea Institute of Planning and Evaluation for Technology in Food, Agriculture, Forestry(IPET)

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