Classification of behaviour with low-frequency accelerometers in female wild boar.

ABSTRACT: Accelerometers with low sampling rates (1 Hz) are commercially available as ear tags. While an automated and therefore undisturbed sampling of animal behaviour can be useful not only in behavioural studies but also in ecological or wildlife management studies, the usefulness of such 'a low data collection rate for the prediction of behaviours was the key question addressed here. We classified the behaviour of female wild boar, kept under semi-natural conditions in a large outdoor enclosure, using acceleration data. Predictions were based on a machine learning algorithm, specifically a random forest model in the open software h2o. Remarkably, prediction of many behaviours was possible using ear-tag acceleration sensors that sampled data only at a low frequency. This measurement device was m

SUBMITTER: Ruf T 

PROVIDER: S-EPMC11864551 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature