Greenhouse gas emissions affect people from a variety of backgrounds, but only wealthy entities have the means to monitor their communities’ air quality with accuracy. Having a low-cost sensing device that achieves comparable accuracy therefore helps promote the common good. To achieve this goal, this project utilizes machine learning to build a self-calibrating sensing device. So far, I have played around multiple open-source machine learning models, such as artificial neural networks or support vector machines.