Waste Classification and Segregation using Machine Learning

Abstract— Waste management is a key component of sustainable development, and Waste classification and recycling are essential to minimizing the harm that garbage causes to the environment. Recently, garbage classification jobs have showed considerable potential for computer vision algorithms. In this article, we provide a method that integrates knowledge of garbage recycling with classification using CNN's VGG16 Transfer Learning algorithm. The suggested method would let people categorise rubbish using their smartphones in an effort to raise awareness of waste recycling. The system utilises CNN's VGG16 Transfer Learning algorithm, which has been pretrained on a sizable dataset of images and is a superb option for feature extraction. There are two phases to the system: training and testing. In the training stage, the VGG16 model is fine-tuned on a small dataset of waste images. In the testing stage, users can take a picture of the waste material using their smartphone, and the system classifies the waste material into one of the predefined categories.