Categorising sheep activity using a tri-axial accelerometer

Abstract

An animal's behaviour can be a useful indicator of their physiological and physical state. As resting, eating, walking and ruminating are the predominant daily activities of ruminant animals, monitoring these behaviours could provide valuable information for management decisions and individual animal health status. Traditional animal monitoring methods have relied on labour intensive, human observation of animals. Accelerometer technology offers the possibility to remotely monitor animal behaviour continuously 24/7. Commercially, an ear worn sensor would be the most suitable for the Australian sheep industry. Therefore, the aim of this current study was to determine the effectiveness of different methods of accelerometer deployment (collar, leg and eartag) to differentiate between three mutually exclusive behaviours in sheep: grazing, standing and walking. A subset of fourteen summary features were subjected to Quadratic Discriminant Analysis (QDA) with 94%, 96% and 99% of grazing, standing and walking events respectively, being correctly predicted from ear acceleration signals. These preliminary results are promising and indicate that an ear deployed accelerometer is capable of identifying basic sheep behaviours. Further research is required to assess the suitability of accelerometers for behaviour detection across different sheep classes, breeds and environments.