Our AI solutions
Ear recognition
Your Challenge Challenge Challenge
If abnormalities are overlooked, animal welfare certification is not granted.
Ear injuries are considered a sensitive indicator of animal welfare, but they are difficult to record in practice. There is often not enough time for reliable visual inspections on the slaughter line. At the same time, there are currently no digital methods for automatically detecting pathological changes and partial losses of ears.
Our Solution Solution Solution
AI-powered ear recognition
FOODFAIR's AI-based ear detection automatically identifies abnormalities, differentiates between slaughter artifacts and pathological changes, and documents the condition of each individual animal with images. The results are linked to the slaughter number and stored in the system.
What the solution does
- Automatic detection of partial losses and pathological changes
- Differentiation from artifact-related abnormalities
- Image-based recording by camera on the slaughter line
- Link to slaughter number and individual animal evaluation
- Integration into ERP and QA systems with feedback to animal welfare officers
Your benefits
What automated ear recognition does in everyday life
The FOODFAIR solution automatically records ear changes for the first time – completely, comprehensively, and with full documentation. This reduces the workload for specialist staff and provides reliable animal welfare data where previously only random samples and estimates were available.
Your possibilities – our goal
Making animal welfare measurable – with objective documentation on the animal itself
Ear recognition not only provides a health indicator—it also creates transparency, reduces staff workload, and contributes to traceability. Especially when combined with tail recognition and organ detection, a valid overall profile can be created for each animal.
With image-based documentation, real-time evaluation, and system integration, the solution makes all the difference—for greater trust among farmers, customers, and authorities.
- Comprehensive recording of ear changes during the slaughtering process
- Link to health, origin, and transport data
- Support for animal welfare officers and QA specialists
- Feedback capability to supply chain partners (e.g., farmers)
- Integration with other FOODFAIR modules for a comprehensive animal welfare profile
The next step starts here
Document animal health where it matters most: on the ear.
5 common questions about ear assessment with AI:
What exactly does AI recognize?
How is the data collected?
Is every animal tested or just random samples?
What happens to the data?
Can the system be combined with other modules?
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