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Detecting Dairy Cow Behavior Using Vision Technology

Author

Listed:
  • John McDonagh

    (Jubilee Campus, School of Computer Science, University of Nottingham, Nottingham NG8 1BB, UK)

  • Georgios Tzimiropoulos

    (School of Electrical Engineering and Computer Science, Queen Mary University of London, London E1 4NS, UK)

  • Kimberley R. Slinger

    (Sutton Bonington Campus, School of Biosciences, University of Nottingham, Sutton Bonington LE12 5RD, UK)

  • Zoë J. Huggett

    (Sutton Bonington Campus, School of Biosciences, University of Nottingham, Sutton Bonington LE12 5RD, UK)

  • Peter M. Down

    (Sutton Bonington Campus, School of Veterinary Medicine and Science, University of Nottingham, Sutton Bonington LE12 5RD, UK)

  • Matt J. Bell

    (Agriculture Department, Hartpury University, Gloucester GL19 3BE, UK)

Abstract

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.

Suggested Citation

  • John McDonagh & Georgios Tzimiropoulos & Kimberley R. Slinger & Zoë J. Huggett & Peter M. Down & Matt J. Bell, 2021. "Detecting Dairy Cow Behavior Using Vision Technology," Agriculture, MDPI, vol. 11(7), pages 1-8, July.
    • Handle: RePEc:gam:jagris:v:11:y:2021:i:7:p:675-:d:596081
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    Cited by:

    1. Yongfeng Wei & Hanmeng Zhang & Caili Gong & Dong Wang & Ming Ye & Yupu Jia, 2023. "Study of Pose Estimation Based on Spatio-Temporal Characteristics of Cow Skeleton," Agriculture, MDPI, vol. 13(8), pages 1-14, August.

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