Following the launch of the PICVISA 4.0 project, work continues on integrating artificial intelligence and digital technology directly into the machine vision systems used in PICVISA's waste sorting equipment.

The goal is to give sorting machines the ability to recognise a wider range of materials, shapes and conditions than rule-based systems alone can handle – using models trained on large volumes of real waste samples to improve classification accuracy over time.

At the same time, the project is adding digital capabilities that go beyond sorting itself: better data capture, connectivity, and reporting, so that operators get more visibility into what their machines are processing and how performance changes over time.

As this work progresses, the result is sorting equipment that becomes more capable the longer it operates – learning from the material that passes through it and giving recycling facilities better tools to manage and report on their operations.

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