Lifestock tracking

Computer vision tasks, especially on multi-object tracking, can be challenging in complex farm environments, which are very different to typical computer vision scenarios.

Quantum computing could improve workflows related to, e.g., image recognition, pattern matching, or temporal tracking algorithms, supporting consistency in the tracking of individual animals over time.

Improved accuracy in livestock monitoring, can lead to better disease detection, faster interventions by the farmer, and hence improved animal welfare and operational efficiency across the agrifood sector.