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Towards animal welfare monitoring in pig farming using sensors and machine learning

dc.contributor.authorRiekert, Martin
dc.contributor.authorZimpel, Tobias
dc.contributor.authorHoffmann, Christa
dc.contributor.authorWild, Andrea
dc.contributor.authorGallmann, Eva
dc.contributor.authorKlein, Achim
dc.contributor.editorGandorfer, Markus
dc.contributor.editorMeyer-Aurich, Andreas
dc.contributor.editorBernhardt, Heinz
dc.contributor.editorMaidl, Franz Xaver
dc.contributor.editorFröhlich, Georg
dc.contributor.editorFloto, Helga
dc.date.accessioned2020-03-04T13:06:39Z
dc.date.available2020-03-04T13:06:39Z
dc.date.issued2020
dc.description.abstractAnimal welfare monitoring has the potential to improve animal welfare and provide quality-oriented differentiation for producers at the same time. However, early approaches to animal welfare monitoring use manual injury scoring and evaluation of slaughter data and other biological data. These approaches are often characterized by manual data collection, with data being evaluated infrequently. Thus, production costs would increase substantially. However, with the advent of high-tech commercial sensor technology, monitoring can be conducted automatically, objectively, and at low cost. The aim of this study is to review the suitability of environmental sensors in combination with machine learning in an intelligent animal welfare monitoring system. The system automatically analyzes data from commercially available low-cost sensors, identifies animal welfare risks and recommends actions for animal welfare.en
dc.identifier.isbn978-3-88579-693-0
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/31908
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartof40. GIL-Jahrestagung, Digitalisierung für Mensch, Umwelt und Tier
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-299
dc.subjectAnimal welfare monitoring
dc.subjectenvironmental sensors
dc.subjectmachine learning
dc.titleTowards animal welfare monitoring in pig farming using sensors and machine learningen
dc.typeText/Conference Paper
gi.citation.endPage276
gi.citation.publisherPlaceBonn
gi.citation.startPage271
gi.conference.date17.-18. Februar 2020
gi.conference.locationWeihenstephan, Freising

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