CANADIAN SHEEP FEDERATION
FaceTrace
Sheep facial identification software designed to ease the burden of traceability and reporting on farmers.
In this 8-month long capstone project, we as a team of 6 undergraduate students worked with the Canadian Sheep Federation to develop a sheep facial recognition software using Machine Learning (ML) technology. This tool introduces facial biometrics as a replacement for manual ear tag scanning to make the tracing and reporting processes more efficient and accurate.
Problem 1
New traceability regulation requires farmers to report sheep ID after each movement event. Existing ear tagging systems are inefficient and unreliable for traceability.
Solution 1
Replace manual ear tags with a facial ID system developed using ML technology, enabling automatic facial recognition of sheep upon scanning using mobile phones or barn cameras.
Problem 2
Movement events are stress-inducing for sheep, but there is no way to know if sheep are fit for travel.
Solution 2
Real-time assessment of sheep welfare by measuring differences in facial expression.
