Abstract
There is an urgent need for objective, evidence-based tools to monitor animal health and welfare. Locomotor dynamics offer promising opportunities to quantitatively and continuously track individual animal behaviour, to improve management of health and welfare. This project aims to use computer vision and machine-learning (or artificial intelligence, AI) to detect and classify poultry motion within group-housing. Automation of behaviour monitoring has commercialisation potential in precision livestock farming, treatment response monitoring of research animals (vaccine and drug development), and companion animal healthcare. This project aligns well with Key Challenges in the BBSRC strategic framework, including One Health and Biotechnology for Health.
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