Intelligent Robotics for Sorting Clothing and Textile Waste Using Cloud-Integrated Recycling Systems and CNN

The textile industry has a significant problem dealing with massive quantities of textile and clothing waste. To address this, this paper introduces a new method for automating textile waste sorting using Convolutional Neural Networks (CNNs), cloud-integrated recycling systems, and intelligent robots. Using CNNs, our proposed system combines advanced robotics with sophisticated computer vision capabilities. Using characteristics like fabric type, color, and condition, robots can sort textile waste effectively. To further facilitate scalability and flexibility in dealing with high waste quantities, the system uses cloud computing infrastructure to process data in real time and make decisions. We lay forth the plan for the system and how it will work, including the robotic sorting mechanism, CNN s models for item identification, and the cloud-based integration that will make everything run smoothly. It conducts experimental trials to assess the system's performance, showing that it efficiently sorts textile waste, reduces human work, and improves recycling efficiency. The results show great potential in solving the problems of textile waste management. This might lead to a more sustainable and eco-friendly strategy in the textile sector.