Automation in canine science: enhancing human capabilities and overcoming adoption barriers

Nareed Farhat*, Dirk van der Linden, Anna Zamansky, Tal Assif

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)
4 Downloads (Pure)

Abstract

The emerging field of canine science has been slow in adopting automated approaches for data analysis. However, with the dramatic increase in the volume and complexity of the collected behavioral data, this is now beginning to change. This paper aims to systematize the field of automation in canine science. We provide an examination of current automation processes and pipelines by providing a literature review of state-of-the-art studies applying automation in this field. In addition, via an empirical study with researchers in animal behavior, we explore their perceptions and attitudes toward automated approaches for better understanding barriers for a wider adoption of automation. The insights derived from this research could facilitate more effective and widespread utilization of automation within canine science, addressing current challenges and enhancing the analysis of increasingly complex and voluminous behavioral data. This could potentially revolutionize the field, allowing for more objective and quantifiable assessments of dog behavior, which would ultimately contribute to our understanding of dog-human interactions and canine welfare.
Original languageEnglish
Article number1394620
Number of pages13
JournalFrontiers in Veterinary Science
Volume11
DOIs
Publication statusPublished - 14 Jun 2024

Keywords

  • artificial intelligence
  • animal behavior
  • motion tracking
  • automation
  • canine science

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