A Catalyst for Automated Capture and Analysis of Behaviour and Performance Changes in Pigs for Early Detection of Health and Welfare Problems

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Subclinical & clinical disease is the main factor responsible for pig system inefficiency & reduction in pro-ductivity and welfare. Currently disease detection is done through human observation or diagnostic sur-veillance, but monitoring continuously involves significant costs & effort.The project aims to develop & validate technology to automatically monitor performance and behaviour in growing pigs. Individual pig and group movements will be automatically captured and analysed using low cost camera installations and computer vision and learning techniques, thereby providing information about pig performance, behaviour and group dynamics so as to allow rapid intervention to improve health and welfare and increase farm efficiency. The consortium has skills in the design of software solutions, animal health & diagnostics, and pig management, with the academic partner being at the forefront of research in computer vision/recognition techniques and pig management & health.