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Analysis of Technologies for Visual Tracking of Physiological Condition of Cattle

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Agriculture Digitalization and Organic Production

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 331))

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Abstract

At the moment, devices for monitoring the physiological condition of the animal are beginning to play an increasingly important role. These devices and systems allow for operational control and monitoring of the animal 24 h a day, 7 days a week, which allows specialists and engineers to make effective decisions on cattle management. The purpose of the paper: the development of models, analysis of methods and systems that allow predicting and assessing the physical condition of animals, detecting, and preventing diseases in cattle in real time. As a result of our analysis, we identified 25 promising studies and technologies that tested the accuracy and conditions for improving the accuracy of various monitoring devices for dairy herd animals to measure the duration and number of activities under different conditions, with different frequency, sampling intervals and editing criteria. This paper provides an overview of other popular studies conducted on cattle. The authors define the current state, problems, and possible ways of further development of dairy cattle health monitoring and herd management technologies based on visual feature recognition using artificial neural networks.

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Acknowledgements

This work is supported by state research № FFZF-2022-0005.

Author information

Authors and Affiliations

  1. ITMO University, Kronverksky avenue, 49, bldg. A, 197101, St. Petersburg, Russia

    Kirill Trezubov

  2. St. Petersburg Federal Research Center of the Russian Academy of Sciences (SPC RAS), St. Petersburg Institute for Informatics and Automation of the Russian Academy of Sciences, 39, 14th Line, 199178, St. Petersburg, Russia

    Elena Avksentieva

  3. Petersburg Federal Research Center of the Russian Academy of Sciences (SPC RAS), Institute of Agricultural Economics and Rural Development (IAERD), Podbelskogo road, 7, 196608, Pushkin, St. Petersburg, Russia

    Valeriya Luzhnyak & Ilya Shulgin

Authors
  1. Kirill Trezubov
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  2. Elena Avksentieva
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  3. Valeriya Luzhnyak
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  4. Ilya Shulgin
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Corresponding author

Correspondence to Elena Avksentieva .

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Editors and Affiliations

  1. St. Petersburg Federal Research Center of the Russian Academy of Sciences, St. Petersburg, Russia

    Andrey Ronzhin

  2. St. Petersburg Federal Research Center of the Russian Academy of Sciences, St. Petersburg, Russia

    Alexander Kostyaev

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Trezubov, K., Avksentieva, E., Luzhnyak, V., Shulgin, I. (2023). Analysis of Technologies for Visual Tracking of Physiological Condition of Cattle. In: Ronzhin, A., Kostyaev, A. (eds) Agriculture Digitalization and Organic Production . Smart Innovation, Systems and Technologies, vol 331. Springer, Singapore. https://doi.org/10.1007/978-981-19-7780-0_23

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