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Fabric Composition Detector (FABCOD)
The FABCOD project, as part of the DIH4AI initiative, was designed to innovate the process of fabric quality inspection in the textile industry. It aimed to enhance the detection of fabric anomalies and material properties, traditionally done by human operators, by implementing an AI-based Fabric Composition Detector. This detector, using optical and hyperspectral sensors, was intended to improve the fabric inspection process, making it faster and more efficient. The project sought to facilitate sustainability, reduce waste and production errors, and support the promotion of new products like natural, pollutant-free garments. The technology was to be integrated into existing inspection machines, processing data server-side and providing an operator dashboard for result visualization. This project represented a significant step towards digitalizing and automating quality control in textile manufacturing, aligning with Industry 4.0 and EU guidelines for sustainability and digital transformation.
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