Using simple gestures, you could soon be able to alter the color of your clothes. Researchers have developed a stretchable, machine-washable textile embedded with a tiny camera that responds to body movements. Intelligent textiles also use artificial intelligence to recognize and display color information. The Hong Kong team behind the tech — the Laboratory for Artificial Intelligence in Design (AiDLab) — says it could help reduce waste by giving people more color choices for an item of clothing.
The textile is made from a soft, knitted polymer-optical fiber fabric. It has conductive threads that change color when electricity is applied, and it’s embedded with sensors that can track the wearer’s motion. When the wearer raises or lowers their arms, the color of the garment changes in response. The fabric can also be used to display digital information.
For instance, the AiDLab has experimented with a striped scarf that shows real-time bus information. In addition to their practicality, the versatility of intelligent textiles’ is attracting the fashion world’s attention. The label Anteprima launched a collection at Milan Fashion Week that showcased its capabilities. Its founder and creative director, Izumi Ogino, explains the textile’s flexibility allowed her to integrate subtle lighting elements into her designs.
Another way AI is reducing waste is by helping with food distribution and production. The technology can scan food and determine its quality, which can be helpful for businesses that want to optimize their supply chains or sell more premium products.
Moreover, it can help track food production and consumption patterns to identify ways to save on costs or produce more efficiently. In the future, AI may help in food waste reduction. The decomposition of unused food in landfills produces methane, a potent greenhouse gas.
While AI is already transforming our lives, the industry still faces challenges in maximizing its potential to solve problems. It is essential to find solutions that can guarantee that AI is implemented responsibly and used to address societal and ethical concerns, such as data privacy and the ability for algorithms to learn from biased information.
