Activity-Integrated Hidden Markov Model to Predict Calving Time
Autor: | Pyke Tin, Yoichiro Horii, Ikuo Kobayashi, Thi Thi Zin, Swe Zar Maw, Kosuke Sumi |
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Rok vydání: | 2021 |
Předmět: |
040301 veterinary sciences
Computer science Ice calving Early detection Production cycle Machine learning computer.software_genre Hidden Markov Model Article 0403 veterinary science behavior changes Health problems lcsh:Zoology lcsh:QL1-991 calving Hidden Markov model lcsh:Veterinary medicine General Veterinary business.industry 0402 animal and dairy science Process (computing) prediction 04 agricultural and veterinary sciences Integrated approach 040201 dairy & animal science lcsh:SF600-1100 Animal Science and Zoology Artificial intelligence business Lying computer |
Zdroj: | Animals, Vol 11, Iss 385, p 385 (2021) Animals : an Open Access Journal from MDPI Animals Volume 11 Issue 2 |
ISSN: | 2076-2615 |
DOI: | 10.3390/ani11020385 |
Popis: | Accurately predicting when calving will occur can provide great value in managing a dairy farm since it provides personnel with the ability to determine whether assistance is necessary. Not providing such assistance when necessary could prolong the calving process, negatively affecting the health of both mother cow and calf. Such prolongation could lead to multiple illnesses. Calving is one of the most critical situations for cows during the production cycle. A precise video-monitoring system for cows can provide early detection of difficulties or health problems, and facilitates timely and appropriate human intervention. In this paper, we propose an integrated approach for predicting when calving will occur by combining behavioral activities extracted from recorded video sequences with a Hidden Markov Model. Specifically, two sub-systems comprise our proposed system: (i) Behaviors extraction such as lying, standing, number of changing positions between lying down and standing up, and other significant activities, such as holding up the tail, and turning the head to the side and, (ii) using an integrated Hidden Markov Model to predict when calving will occur. The experiments using our proposed system were conducted at a large dairy farm in Oita Prefecture in Japan. Experimental results show that the proposed method has promise in practical applications. In particular, we found that the high frequency of posture changes has played a central role in accurately predicting the time of calving. |
Databáze: | OpenAIRE |
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