From Mechanical Detection to Intelligent Vision In traditional egg-sorting systems, crack detection relied on mechanical and acoustic sensors to identify broken shells. While effective, these systems had limitations in precision and scalability. Our engineering team developed a new generation of vision-based crack detection, powered by deep learning and real-time data visualization — transforming how egg quality is analyzed and presented.
Intelligent Insight at Industrial Scale The system processes large volumes of eggs with remarkable accuracy, automatically classifying each one by crack type and severity. A modern, intuitive human–machine interface (HMI) displays all detection results in real time, making it easy for operators to monitor production and analyze quality trends at a glance.
The interface brings data to life — showing exactly which eggs belong to each classification, and how performance evolves over time. It combines responsive visualization with smooth interactivity, allowing users to move fluidly through different views, from batch overview to individual egg data.
Seamless User Experience by Design Developed by the same multidisciplinary team behind our 3D data analytics platform, this project brings together front-end and back-end development, user experience design, and AI integration into a single cohesive product. The result: a highly functional, visually engaging tool that turns industrial inspection data into clear, actionable insight.
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