Summary
Multi-object tracking (MOT) methods have the potential to significantly improve precision livestock farming (PLF) by enabling simultaneous tracking of multiple animals in complex environments. However, research on MOT applications in livestock monitoring is limited, with state-of-the-art (SOTA) models primarily tested on benchmark datasets of pedestrians or vehicles. This systematic review was performed according to PRISMA guidelines. We identified 111 recent papers published from January 2019 to January 2025 using a keyword search for MOT and livestock from three scientific databases. The use-cases, datasets, and algorithms of MOT applied to livestock were thoroughly examined. This review addresses the limitations in existing systems to consistently preserve individual animal identities i
Dig deeper with Pulse AI.
Pulse AI has read the whole catalogue. Ask about this record, its theme, or how the findings apply to UK farming and policy — every answer cites the underlying studies.