Sensor technology, machine learning, and computer vision are transforming the capacity to monitor animal welfare on farms, in transport, and in the wild.
Welfare monitoring technology addresses a fundamental barrier to welfare improvement: the impossibility of human observation at the scale and frequency needed to detect welfare problems early. Automated systems can continuously monitor hundreds or thousands of animals, flagging deviations from normal behavior for human follow-up. This transforms welfare monitoring from periodic inspection to continuous surveillance, enabling earlier detection and treatment of lameness, disease, and stress. The technology is advancing rapidly and becoming cost-accessible for mid-scale farms. Its adoption should be incentivized through welfare certification and regulation.