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Automated monitoring of dairy cow body condition, mobility and weight using a single 3D video capture device

Hansen, M. F.; Smith, M. L.; Smith, L. N.; Abdul Jabbar, K.; Forbes, D.

Authors

Mark Hansen Mark.Hansen@uwe.ac.uk
Professor of Machine Vision and Machine Learning

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Melvyn Smith Melvyn.Smith@uwe.ac.uk
Research Centre Director Vision Lab/Prof

Lyndon Smith Lyndon.Smith@uwe.ac.uk
Professor in Computer Simulation and Machine

K. Abdul Jabbar

D. Forbes



Abstract

© 2018 Here we propose a low-cost automated system for the unobtrusive and continuous welfare monitoring of dairy cattle on the farm. We argue that effective and regular monitoring of multiple condition traits is not currently practicable and go on to propose 3D imaging technology able to acquire differing forms of related animal condition data (body condition, lameness and weight), concurrently using a single device. Results obtained under farm conditions in continuous operation are shown to be comparable or better than manual scoring of the herd. We also consider inherent limitations of using scoring and argue that sensitivity to relative change over successive observations offers greater benefit than the use of what may be considered abstract and arbitrary scoring systems.

Citation

Hansen, M. F., Smith, M. L., Smith, L. N., Abdul Jabbar, K., & Forbes, D. (2018). Automated monitoring of dairy cow body condition, mobility and weight using a single 3D video capture device. Computers in Industry, 98, 14-22. https://doi.org/10.1016/j.compind.2018.02.011

Journal Article Type Article
Acceptance Date Jan 10, 2018
Online Publication Date Mar 5, 2018
Publication Date Jun 1, 2018
Deposit Date Mar 6, 2018
Publicly Available Date Jan 10, 2020
Journal Computers in Industry
Print ISSN 0166-3615
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 98
Pages 14-22
DOI https://doi.org/10.1016/j.compind.2018.02.011
Keywords 3D imaging, body condition score, lameness, weight
Public URL https://uwe-repository.worktribe.com/output/874288
Publisher URL https://doi.org/10.1016/j.compind.2018.02.011

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