<div class="csl-bib-body">
<div class="csl-entry">Hoxhallari, K., Purcell, W., & Neubauer, T. (2022). The potential of Explainable Artificial Intelligence in Precision Livestock Farming. In D. Berckmans, M. Oczak, M. Iwersen, & K. Wagener (Eds.), <i>Precision Livestock Farming 2022 : papers presented at the 10th European Conference on Precision Livestock Farming</i> (pp. 710–717). University of Veterinary Medicine Vienna. https://doi.org/10.34726/4701</div>
</div>
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/187886
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dc.identifier.uri
https://doi.org/10.34726/4701
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dc.description.abstract
In the discussion on the increasing demand for food, which is to be met by efficient and sustainable increases in productivity, animal welfare is becoming increasingly important. Animal health issues must be identified to prevent epidemics that significantly impact the economic performance of farms or even cause societal harm.
The use of cutting-edge technologies (IoT, sensors, Big Data processing, etc.) is increasingly enabling early intervention in livestock farming to curb productivity losses through real-time monitoring, alerts, and decision support. The ubiquity of these technological solutions has enabled stakeholders to create more robust agricultural supply chains, that deliver sustainable nutrition for a growing population. However, the increasing use of Artificial Intelligence (AI), which is responsible for many of the current breakthroughs in Precision Livestock Farming (PLF) and agriculture in general, has meant that modern decision-support solutions have increasingly transitioned toward black box systems. It has become apparent that a gap exists between efforts to develop more advanced machine learning models, and the growing demands for ethical assessment and transparency in agriculture decision-making. Explainable Artificial Intelligence (XAI) is one such solution that could prove effective in overcoming the current limitations of black-box models, by allowing the decision-making process of such models to be explored. Through a literature review, we evaluate the potential of XAI in various agricultural use cases and demonstrate the potential benefits of its application to precision livestock management.
en
dc.description.sponsorship
Vereine, Stiftungen, Preise
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dc.language.iso
en
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dc.rights.uri
http://creativecommons.org/licenses/by-nc-nd/4.0/
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dc.subject
Artificial Intelligence
en
dc.subject
Explainability
en
dc.subject
Animal welfare
en
dc.subject
Monitoring
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dc.subject
Farm management
en
dc.title
The potential of Explainable Artificial Intelligence in Precision Livestock Farming
en
dc.type
Inproceedings
en
dc.type
Konferenzbeitrag
de
dc.rights.license
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
en
dc.rights.license
Creative Commons Namensnennung - Nicht kommerziell - Keine Bearbeitungen 4.0 International
de
dc.identifier.doi
10.34726/4701
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dc.contributor.affiliation
SBA Research gGmbH, Austria
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dc.contributor.editoraffiliation
University of Veterinary Medicine Vienna, Austria
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dc.contributor.editoraffiliation
University of Veterinary Medicine Vienna, Austria
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dc.contributor.editoraffiliation
University of Veterinary Medicine Vienna, Austria
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dc.contributor.editoraffiliation
University of Veterinary Medicine Vienna, Austria
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dc.relation.isbn
978-83-965360-0-6
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dc.description.startpage
710
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dc.description.endpage
717
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dc.relation.grantno
000000
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dc.type.category
Full-Paper Contribution
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tuw.booktitle
Precision Livestock Farming 2022 : papers presented at the 10th European Conference on Precision Livestock Farming
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tuw.peerreviewed
true
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tuw.relation.publisher
University of Veterinary Medicine Vienna
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tuw.relation.publisherplace
Vienna
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tuw.project.title
Digitalisierungs- und Innovationslabor in den Agrarwissenschaften - Doktorats Kolleg und Innovationsplattform.
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tuw.researchTopic.id
E6
-
tuw.researchTopic.id
I4
-
tuw.researchTopic.id
C6
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tuw.researchTopic.name
Sustainable Production and Technologies
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tuw.researchTopic.name
Information Systems Engineering
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tuw.researchTopic.name
Modeling and Simulation
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tuw.researchTopic.value
25
-
tuw.researchTopic.value
50
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tuw.researchTopic.value
25
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tuw.publication.orgunit
E194-04 - Forschungsbereich Data Science
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tuw.publication.orgunit
E194 - Institut für Information Systems Engineering
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dc.description.numberOfPages
8
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tuw.author.orcid
0000-0002-1886-2632
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tuw.author.orcid
0000-0002-9814-6045
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dc.rights.identifier
CC BY-NC-ND 4.0
en
dc.rights.identifier
CC BY-NC-ND 4.0
de
tuw.editor.orcid
0000-0002-2974-6055
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tuw.editor.orcid
0000-0003-1045-7568
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tuw.editor.orcid
0000-0001-7893-6050
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tuw.editor.orcid
0000-0002-8291-2323
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tuw.event.name
10th European Conference on Precision Livestock Farming ECPLF 2022
en
tuw.event.startdate
29-08-2022
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tuw.event.enddate
02-09-2022
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tuw.event.online
On Site
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tuw.event.type
Event for scientific audience
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tuw.event.place
Vienna
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tuw.event.country
AT
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tuw.event.institution
University of Veterinary Medicine Vienna
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tuw.event.presenter
Purcell, Warren
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wb.sciencebranch
Informatik
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wb.sciencebranch
Wirtschaftswissenschaften
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wb.sciencebranch.oefos
1020
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wb.sciencebranch.oefos
5020
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wb.sciencebranch.value
90
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wb.sciencebranch.value
10
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item.openaccessfulltext
Open Access
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item.cerifentitytype
Publications
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item.languageiso639-1
en
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item.openairecristype
http://purl.org/coar/resource_type/c_5794
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item.grantfulltext
open
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item.fulltext
with Fulltext
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item.mimetype
application/pdf
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item.openairetype
conference paper
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crisitem.author.dept
SBA Research gGmbH, Austria
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crisitem.author.dept
E194-04 - Forschungsbereich E-Commerce
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crisitem.author.dept
E194-04 - Forschungsbereich E-Commerce
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crisitem.author.orcid
0000-0002-1886-2632
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crisitem.author.orcid
0000-0002-9814-6045
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crisitem.author.parentorg
E194 - Institut für Information Systems Engineering
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crisitem.author.parentorg
E194 - Institut für Information Systems Engineering