Russia Is Using AI to Spot Lameness in Cattle Before Farmers Can See It

Researchers in Moscow have developed an AI-powered system that can detect subtle signs of lameness in livestock, potentially transforming veterinary care and boosting farm efficiency.

A team at the K. A. Timiryazev Moscow Agricultural Academy is building a digital platform that uses computer vision, thermal imaging, 3D video capture, and neural network data analysis to spot early signs of lameness in cattle. The system doesn’t just look at gait — it also monitors other physiological parameters to flag problems before they become visible to the human eye.

Using its AI model, the platform can detect tiny deviations in joint angles, curvature of the spine, and movement symmetry. It then assigns a lameness score and alerts farm staff when an animal might be developing a condition. According to the researchers, this predictive capability could help farmers intervene earlier, preventing worsening health issues and reducing productivity losses.

The neural network has already been trained on more than 60 terabytes of annotated video data, giving it the ability to recognize health abnormalities with over 96 percent accuracy. This vast dataset allows the system to adapt to variations in breed, size, and movement patterns, making it suitable for different farm environments.

If implemented widely, the technology could significantly improve veterinary oversight, reduce livestock losses, and enhance animal welfare — giving farms a data-driven way to safeguard their herds.