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  4. Automated Detection of Farrowing Events in Commercial Pig Farms Using Deep Learning
 
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Automated Detection of Farrowing Events in Commercial Pig Farms Using Deep Learning

Journal
2025 Asabe Annual International Meeting
Date Issued
2025
Author(s)
Chu Wang, Wen-Liang
Lin, En-Chung  
Kuo, Yan-Fu  
DOI
10.13031/aim.202500592
URI
https://www.scopus.com/record/display.uri?eid=2-s2.0-105015577795&origin=resultslist
https://scholars.lib.ntu.edu.tw/handle/123456789/732696
Abstract
The economic value of pig production in animal husbandry is considerable worldwide. According to the Ministry of agriculture, Taiwan, a total of 6.24 million commercial pigs were traded, creating approximately 563 million NTD of value in 2024. To keep up with the domestic demand of pork, the reproducibility of piglets is crucial. However, the farrowing process presents multiple challenges, including high mortality rates of piglets due to complications during delivery. Thus, workers usually have to stay long hours in the pig farm to expect the deliveries of sows and to assist the sows during delivery. The prolonged working hours make young generation hesitate to join the pig farming industry. These issues not only compromise animal welfare but also result in substantial financial losses for farmers. This research proposes to identify the farrowing events of sows using top-down videos and deep learning models. Top-down videos of farrowing crates from multiple pig farms across Taiwan were collected. The events of piglet delivery were annotated. Deep learning models were then trained using the annotated videos to detect the events of piglet delivery. Critical events related to farrowing, such as prolonged labor or stillbirths, were further identified using the results from the deep learning model. By integrating computer vision and deep learning techniques, this research seeks to establish a foundational framework for automated farrow detection systems that could enhance productivity and economic viability in pig farming management.
Event(s)
2025 American Society of Agricultural and Biological Engineers Annual International Meeting, ASABE 2025
Subjects
Deep Learning
Farrowing Events Detection
Pig Farming
SDGs

[SDGs]SDG2

[SDGs]SDG3

Publisher
American Society of Agricultural and Biological Engineers
Description
2025 American Society of Agricultural and Biological Engineers Annual International Meeting, ASABE 2025
2025 Asabe Annual International Meeting, 2025 Toronto, Ontario, Canada July 13-16, 2025
Type
conference paper not in proceedings

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