SUSTAINABLE FASHION THROUGH AI: PREDICTIVE WASTE REDUCTION AND ECO-FRIENDLY MATERIAL OPTIMIZATION - Sapariya, Jitesh Mansukh; Kumar, Naveen; Ansari, Amena; Chaturvedi, Dipti; Ahmad, Dr. Akbar; Nayak, Dinesh Kumar (ShodhKosh: Journal of Visual and Performing Arts, 2025)
Because of things like using a lot of resources, making a lot of trash, and using materials in ways that aren't sustainable, the fashion business is one of the biggest causes of environmental damage around the world. This research looks into how Artificial Intelligence (AI) can be used in sustainable fashion, focussing on predicting ways to cut down on waste and making the best use of eco-friendly materials. AI-powered systems can predict changes in demand, improve product management, and offer eco-friendly materials that can be used instead of standard ones by combining machine learning models, data analytics, and material science. The main purpose of this study is to look into how AI can help cut down on the trash that is made when clothes are made and when they are thrown away at the end of their useful life, while also encouraging the use of eco-friendly materials. AI, using advanced algorithms like predictive modelling, optimisation techniques, and lifetime analysis, can help find low-waste manufacturing methods and materials that can be recovered, biodegraded, or grown again. Fashion brands can also use circular economy models by making it easier for clothes to be recycled and used again by combining AI with digital platforms. The study results show fashion brands and producers how to use AI-based tools that are better for the environment, cheaper to make, and encourage new ideas in environmentally friendly fashion. The study also talks about the problems that might come up when the fashion industry tries to use AI. These include worries about data privacy, problems with growth, and the need for everyone in the industry to work together to make AI widely sustainable.