Predicting Lameness in Sheep Activity Using Tri-Axial Acceleration Signals
Precision Agriculture Research Group, University of New England, Armidale, NSW 2351, Australia
Sheep Cooperative Research Centre, University of New England, Armidale, NSW 2351, Australia
New South Wales Department of Primary Industries, Livestock Industries Centre, University of New England, Armidale, NSW 2351, Australia
Formerly Precision Agriculture Research Group, University of New England, Armidale, NSW 2351, Australia
Institute for Future Farming Systems, School of Medical and Applied Sciences, Central Queensland University, Central Queensland Innovation and Research Precinct, Rockhampton, QLD 4702, Australia
Author to whom correspondence should be addressed.
Received: 14 November 2017 / Revised: 22 December 2017 / Accepted: 6 January 2018 / Published: 11 January 2018
Monitoring livestock farmed under extensive conditions is challenging and this is particularly difficult when observing animal behaviour at an individual level. Lameness is a disease symptom that has traditionally relied on visual inspection to detect those animals with an abnormal walking pattern. More recently, accelerometer sensors have been used in other livestock industries to detect lame animals. These devices are able to record changes in activity intensity, allowing us to differentiate between a grazing, walking, and resting animal. Using these on-animal sensors, grazing, standing, walking, and lame walking were accurately detected from an ear attached sensor. With further development, this classification algorithm could be linked with an automatic livestock monitoring system to provide real time information on individual health status, something that is practically not possible under current extensive livestock production systems.