Motivation The circular economy in the textile sector aims to transform the traditional linear model of “take, make, dispose” into a regenerative system in which products and materials continuously circulate within the economy. This approach includes strategies such as design for durability, repair, remanufacturing, as well as textile recycling and reuse, with a growing emphasis on technological innovation to optimize these processes. The integration of advanced technologies such as artificial intelligence, computer vision, and digitalization systems (IoT) continues to revolutionize the textile industry. These tools, whose importance was already identified in the previous project, enable more accurate material classification, optimize processes, and facilitate real-time monitoring and traceability throughout the textile lifecycle. Objectives The main objective is to develop and implement solutions based on artificial intelligence and digitalization that optimize textile recycling and manufacturing processes, promoting a circular economy in the sector.

Development of artificial vision and artificial intelligence tools for automatic classification and quality control of textiles. Creating a hyperspectral database of textile materials for training classification models. Training and validation of machine learning models capable of identifying visually similar fibers with high accuracy. Development of an artificial vision simulator that replicates real inspection conditions without stopping industrial machinery. Validation of algorithms for automatic detection of defects, color variations, and structural anomalies in fabrics. Demonstration of the feasibility of automatic systems for material classification and support for textile recycling processes.