Evidence map›Paper›PMID 39611113›Full record

ArticleFrontiers in veterinary science2024

Human-computer interactions with farm animals-enhancing welfare through precision livestock farming and artificial intelligence.

Suresh Neethirajan, Stacey Scott, Clara Mancini, Xavier Boivin, Elizabeth Strand

Abstract read
In one paragraph

Article in Frontiers in veterinary science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Suresh NeethirajanFaculty of Agriculture and Computer Science, Dalhousie University, Halifax, NS, Canada.
Stacey ScottSchool of Computer Science, University of Guelph, Guelph, ON, Canada.
Clara ManciniThe Open University Milton Keynes, Nottingham, United Kingdom.
Xavier BoivinUniversité Clermont Auvergne, INRAE, Saint-Genès Champanelle, France.
Elizabeth StrandCollege of Social Work and College of Veterinary Medicine, University of Tennessee, Knoxville, TN, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

While user-centered design approaches stemming from the human-computer interaction (HCI) field have notably improved the welfare of companion, service, and zoo animals, their application in farm animal settings remains limited. This shortfall has catalyzed the emergence of animal-computer interaction (ACI), a discipline extending technology's reach to a multispecies user base involving both animals and humans. Despite significant strides in other sectors, the adaptation of HCI and ACI (collectively HACI) to farm animal welfare-particularly for dairy cows, swine, and poultry-lags behind. Our paper explores the potential of HACI within precision livestock farming (PLF) and artificial intelligence (AI) to enhance individual animal welfare and address the unique challenges within these settings. It underscores the necessity of transitioning from productivity-focused to animal-centered farming methods, advocating for a paradigm shift that emphasizes welfare as integral to sustainable farming practices. Emphasizing the 'One Welfare' approach, this discussion highlights how integrating animal-centered technologies not only benefits farm animal health, productivity, and overall well-being but also aligns with broader societal, environmental, and economic benefits, considering the pressures farmers face. This perspective is based on insights from a one-day workshop held on June 24, 2024, which focused on advancing HACI technologies for farm animal welfare.

Indexed as

animal-computer interactionartificial intelligencefarm animal welfarehuman-computer interactionone welfareprecision livestock farmingsensor technologysustainable agriculture

Identifiers

PMID39611113
PMCPMC11604036

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.