Computer Vision Techniques for Intelligent Detection and Classification of Waste Sorting

This paper focuses on the application of computer vision techniques in waste classification and sorting within the context of Industry 4.0. The Fourth Industrial Revolution has revolutionized manufacturing and industrial processes through advanced technologies such as artificial intelligence, the Internet of Things, and automation. Computer vision, coupled with machine learning algorithms, has emerged as a critical enabler, offering transformative solutions for various industrial applications. In this study, we explore the potential of computer vision techniques as a user-friendly tool for improving waste management practices. By leveraging advanced algorithms and neural networks, we develop a waste classification model capable of automating the identification and sorting of waste materials. The model is trained using a diverse dataset of waste material images and refined through an iterative process. The results demonstrate the effectiveness of the trained model in accurately classifying and sorting waste items. This research contributes to the optimization of waste management processes within the industry 4.0 framework, driving advancements towards efficient and sustainable waste management practices.