Emerging AI Technologies Inspiring the Next Generation of E-textiles

Cleary, Frances and Srisa-An, Witawas and Henshall, David C. and Balasubramaniam, Sasitharan (2023) Emerging AI Technologies Inspiring the Next Generation of E-textiles. Other. UNSPECIFIED.

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The smart textile and wearables sector is looking towards advancing technologies to meet both industry, consumer and new emerging innovative textile application demands, within a fast paced textile industry. In parallel inspiration based on the biological neural workings of the human brain is driving the next generation of artificial intelligence. Artificial intelligence inspired hardware (neuromorphic computing) and software modules mimicking the processing capabilities and properties of neural networks and the human nervous system are taking shape. The textile sector needs to actively look at such emerging and new technologies taking inspiration from their workings and processing methods in order to stimulate new and innovative embedded intelligence advancements in the etextile world. This emerging next generation of Artificial intelligence(AI) is rapidly gaining interest across varying industries (textile, medical, automotive, aerospace, military). How such properties can inspire and drive advancements within the etextiles sector needs to be considered. This paper will provide an insight into current nanotechnology and artificial intelligence advancements in the etextiles domain before focusing specifically on the future vision and direction around the potential application of neuromorphic computing and spiking neural network inspired AI technologies within the textile sector. We investigate the core architectural elements of artificial neural networks, neuromorphic computing and how such neuroscience inspired technologies could impact and inspire change and new research developments within the e-textile sector.

Item Type: Monograph (Other)
Additional Information: 14 pages, 8 figures, 2 tables
Departments or Groups:
Depositing User: Admin SSL
Date Deposited: 07 Apr 2023 23:00
Last Modified: 10 Apr 2023 23:02
URI: https://repository.wit.ie/id/eprint/7697

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