Computer vision and artificial intelligence-based salmon identification and automated long-term welfare assessment in aquaculture net-pens (cAIge)

Technology development in cAIge will allow automated, machine-assisted monitoring of fish health and welfare in aquaculture farms at hitherto unprecedented precision levels.

This is to be achieved by leveraging advanced AI-based computer vision technology along with individual fish re-identification algorithms for uninterrupted welfare assessment over time. In addition, the relationship between observed welfare status, environmental factors, and farming practices will be integrated into comprehensive models, thereby gaining a better understanding of how these factors interact to shape optimal holding conditions of fish in aquaculture. Monitoring the welfare and responses to operational and environmental factors of individual fish over a prolonged period represents a significant advancement over current practices, enabling researchers to assess fish welfare and behavior on an unprecedented scale.

Start Date: 15/09/2023
End Date: 03/01/2027

Lead Contact: Christian Schellewald (christian.schellewald@sintef.no)