Detectability of multi-dimensional movement and behaviour in cattle using sensor data and machine learning algorithms: Study on a Charolais bull

Detectability of multi-dimensional movement and behaviour in cattle using sensor data and machine learning algorithms: Study on a Charolais bull

The development of motion sensors for monitoring cattle behaviour has enabled farmers to predict the state of their cattle's welfare more efficiently. While most studies work with one dimensional output with disjunct behaviour categories, more accurate prediction can still be achieved by includ...

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Bibliographic Details
Main Authors: Miklós Biszkup, Gábor Vásárhelyi, Nuri Nurlaila Setiawan, Aliz Márton, Szilárd Szentes, Petra Balogh, Barbara Babay-Török, Gábor Pajor, Dóra Drexler
Format: Article
Language:English
Published: KeAi Communications Co., Ltd. 2024-12-01
Series:Artificial Intelligence in Agriculture
Subjects:
Cattle
PLF
Motion sensors
RumiWatch
Complex behaviour
Multi-dimensional
Online Access:http://www.sciencedirect.com/science/article/pii/S2589721724000412
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