Detecting Dairy Cow Behavior Using Vision Technology

The aim of this study was to investigate using existing image recognition techniques to predict the behavior of dairy cows. A total of 46 individual dairy cows were monitored continuously under 24 h video surveillance prior to calving. The video was annotated for the behaviors of standing, lying, wa...

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Bibliographic Details
Published in:Agriculture (Basel) 2021-07, Vol.11 (7), p.675
Main Authors: McDonagh, John, Tzimiropoulos, Georgios, Slinger, Kimberley R., Huggett, Zoë J., Down, Peter M., Bell, Matt J.
Format: Article
Language:English
Subjects:
Animal welfare
Automation
Behavior
behaviors
Birth
Cameras
computer vision
Dairy cattle
dairy cows
Datasets
Digital cameras
Livestock
management
monitoring
Neural networks
Object recognition
Surveillance
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Summary:The aim of this study was to investigate using existing image recognition techniques to predict the behavior of dairy cows. A total of 46 individual dairy cows were monitored continuously under 24 h video surveillance prior to calving. The video was annotated for the behaviors of standing, lying, walking, shuffling, eating, drinking and contractions for each cow from 10 h prior to calving. A total of 19,191 behavior records were obtained and a non-local neural network was trained and validated on video clips of each behavior. This study showed that the non-local network used correctly classified the seven behaviors 80% or more of the time in the validated dataset. In particular, the detection of birth contractions was correctly predicted 83% of the time, which in itself can be an early warning calving alert, as all cows start contractions several hours prior to giving birth. This approach to behavior recognition using video cameras can assist livestock management.
ISSN:2077-0472
2077-0472
DOI:10.3390/agriculture11070675