The tool identifies houbara bustards alongside potential nest intruders, including foxes and monitor lizards that threaten the bird's natural habitat. Monitoring the vulnerable houbara bustard — a shy, ground-nesting bird of arid landscapes — is one of conservation’s quiet hard problems. Camera traps can help, but teaching algorithms to reliably recognise houbaras — and the many intruders that threaten them — has long been held back by lack of suitable data. Newer real-time systems, particularly YOLOv10, performed best, accurately distinguishing houbaras from intruders even under poor lighting or partial occlusion. Beyond one species, the researchers see HBID24K as a template for conservation AI in difficult environments.

Source: The North Africa Journal February 11, 2026 12:51 UTC