WEDA Released AI Tool for Pig Welfare Monitoring
The newly debuted PigTail system automates tail-biting detection in large herds to improve animal welfare compliance.
Updated on Sept. 25, 2026 in Artificial Intelligence
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WEDA has released PigTail, an AI-powered diagnostic tool designed to automatically identify injuries and tail biting in pig herds. The system was recognized with a silver DLG Innovation Award at EuroTier 2026.
Why it matters
The tool addresses the inefficiency of manual welfare inspections in industrial agriculture, where monitoring thousands of animals is error-prone and labor-intensive. By automating the data collection process, it streamlines the qualification for welfare-based production premiums.
The system processes herds of 400 or more pigs by utilizing overhead camera-based image processing. It matches visual segmentation of tail conditions directly to individual pig ear-tag data for automated tracking.
The players
WEDA
An agricultural technology firm specializing in liquid feeding systems and automation software for livestock management.
DLG
The German Agricultural Society, an organization that hosts EuroTier and recognizes technological advancements in farming.
The details
As each animal moves through a sorting chute, an overhead camera captures a top-down image of the pig. An AI algorithm then segments this image to evaluate whether the tail is intact or shows signs of biting injuries. The software correlates these findings with the animal’s digital ID, providing farmers with specific alerts for injured pigs and generating reports for welfare premium certifications.
Timeline
2026: PigTail won a silver DLG Innovation Award at EuroTier 2026.
The Tech Race
The PigTail system follows a growing trend of replacing manual, error-prone visual checks with automated computer vision in livestock management. It competes against existing pen-level monitoring solutions by shifting the granularity of animal welfare data to the individual pig level.
Producers operating herds of at least 400 pigs can integrate this system into existing sorting chutes to automate welfare reporting. The technology replaces labor-intensive manual inspections with direct ID-linked alerts, immediately impacting the administrative burden of applying for welfare premiums.
The takeaway
Automated vision systems are increasingly replacing traditional manual diagnostic methods in high-volume agricultural settings. Watch for further performance benchmarks on injury detection sensitivity compared to human assessment in upcoming livestock management research.
Further reading
For more on how machine learning is optimizing industrial farming practices, visit our Artificial Intelligence section.
Source note: This article includes information reported by The Scottish Farmer.
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