Digital technologies including computer vision, wearable sensors, and AI-based behaviour analysis are transforming how farm animal welfare is monitored, assessed, and verified.
Conventional welfare auditing relies on infrequent farm visits by inspectors whose presence may temporarily improve conditions and whose assessments capture only a brief time window. Technology-based monitoring systems offer the possibility of continuous, objective welfare data collection that provides a far more accurate picture of habitual conditions. The main barriers to adoption are cost, the need for validated thresholds between acceptable and problematic welfare signals, and questions about data ownership and privacy. Collaborative development of open welfare monitoring standards that allow interoperability between systems would accelerate adoption and improve the consistency of welfare assessment across farming systems.