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Before 1949, computers lacked intelligence. They could not record commands, but they could carry them out. However, between 1957 and 1974, artificial intelligence flourished. Computer storage has increased, as has speed, cost, and accessibility. Artificial intelligence (AI) means that machines can perform various jobs that humans or animals need to do with their natural intelligence. The fathers of artificial intelligence, Marvin Minsky and John McCarthy, defined artificial intelligence in 1950. Artificial intelligence enables machines to understand and achieve certain goals. Deep learning, on the other hand, makes it possible to absorb huge amounts of unstructured data in the form of text, images and audio. Artificial intelligence is appearing in almost every industry that is the future of humanity. It will also be the driving force behind new technologies such as big data, robotics and the Internet of Things (IoT) in the near future. Computer algorithms and machine learning have been widely used in textile testing since the 1980s. Testing and quality control functions can be handled by image processing, automation, deep learning and neural networks. Most of the textile industry today uses computer-aided machinery to produce certain designs on a larger scale and more efficiently. AI can access maintenance data in real time to provide insights that can be used to increase operational efficiency. Artificial Neural Network (ANN) technology makes it easier to improve the quality of life in the industry and detect defects, check patterns, match colors and classify fabrics for textile production more objectively. It also precisely defines the advantages of fine, solid and staple fiber. The use of artificial intelligence in the manufacture of textiles has emerged with a new possibility, i.e. smart clothes that use the Internet of Things and electronic sensors to create a more pleasant health experience. In this article, the researcher tried to give an overview of the artificial intelligence used in the textile industry.
Bansode et al. (Fri,) studied this question.