Abstract
This study suggests the use of Convolutional Neural Network (CNN) to optimize the waste exchange system and classify waste. People can exchange waste for various needs, such as basic necessities, fuel, or money, thanks to this system. A type of artificial neural network known as CNN successfully recognizes image patterns with a dataset of junk images categorized into paper, plastic, and organic. The results show that the model can classify waste with 99% accuracy. This CNN-optimized waste exchange system has many advantages. These include more accurate waste classification, more efficient systems, lower costs, and greater community participation in waste management.