BinxBud

According to World Bank statistics, the world's waste output is expected to keep growing. While there are many reasons for this increase, only 19% of the waste is recovered through recycling. Most recycling efforts fail due to an excess of contaminants. To prevent this problem we developed BinBud to reduce the contaminants from the public. BinBud utilized VGG16 algorithm to classify the trash in accordance with the California government recycling program. We sourced data from Kaggle and trained the classification model on 22 thousand images. During this hackathon, we hoped to develop a user-friendly app that lets the user take an image of their trash and label the trash. The app would also include features that would allow farmers in Yolo County to sell their trash in bulk to local refineries however and a chatbot feature to help confused users, but we weren’t able to deploy these features before the deadline. But, our VGG 16 model outclasses most contemporary models and classifies trash across 14 categories with an average accuracy of 92%. With Bin Bud we give you the power to save the world with every click.