AI enabled Real time clean bone lamb hindquarter monitoring solution (Phase 1)

This project aims to develop and trial a real-time feedback system for lamb leg boning, ultimately improving yield recovery during the boning process. The goal is to evaluate the effectiveness of an off-the-shelf AI camera in providing real-time feedback on boning efficacy. At the JBS Bordertown facility, where 12,000 legs are boned daily, this system could recover 600 kg of meat per day, worth approximately $1,766,875 annually. Achieving a 20% improvement in yield could result in an additional $353,375 annually. This project will develop AI-trained algorithms to validate the benefit and effectiveness of Cognex's lab-based AI camera, capable of differentiating red and white pixels. This technology is highly suitable for the Australian red meat processing sector. Successful validation in this project will lay the groundwork for the adoption of higher-value cameras for future development.