PICVISA 4.0

The PICVISA 4.0 project represents a significant step forward in how machine vision systems for solid waste recycling are designed and operated, incorporating artificial intelligence and other digital technologies to make sorting equipment smarter, more adaptable, and more precise.

Traditional optical sorting systems rely on sensors – near-infrared, colour cameras, and other detectors – combined with pre-programmed rules to classify materials as they pass through the machine. While highly effective, these rule-based systems can struggle with edge cases: materials with unusual shapes, colours, or compositions that fall outside the parameters they were originally configured for.

Artificial intelligence, and machine learning in particular, changes this dynamic. Instead of relying solely on fixed rules, AI-powered systems can be trained on large volumes of real-world material samples, learning to recognise patterns and variations that would be impractical to programme manually. Over time, and with continued exposure to new data, these systems can improve their classification accuracy – adapting to the gradual changes in waste composition that every recycling facility experiences.

Beyond the sorting decision itself, the PICVISA 4.0 project also incorporates broader digital technologies into the equipment – including improved data capture and connectivity, allowing machines to generate detailed records of what they process and how. This data has value well beyond the sorting line itself: it can inform maintenance schedules, help operators understand trends in incoming waste composition, and support the kind of traceability and reporting increasingly required by environmental regulations.

Together, these advances point towards a new generation of sorting equipment – one that doesn't just separate materials, but continuously learns from what passes through it, and provides operators with the information they need to run their facilities more efficiently.

Explore PICVISA optical sorting solutions