We developed a website that allows users to see a wide array of residential solar data to aid in their buying decisions. By utilizing Google Maps and Artificial Intelligence, this project provides access to an array of services including, but not limited to, displays of how much solar is placed on a particular house and display of how much clean energy is being created. The data is mainly provided by crowd sourcing but we have also incorporated a machine learning model that is able to guess if the location has solar panels. This application will prove to be a valuable tool in galvanizing people in the solar market to make wiser buying decisions.
Project Team Member(s):
College of Engineering Unit(s):
Electrical Engineering and Computer Science