Inspiration - We know acquisition costs are a major barrier in the industry. Our teammates also have personally worked in community's with strong opposition to solar, creating issues and tremendous risk for the company.

What it does - Built a Machine Learning model using local data and solar deployment data to predict which communities are open to solar

How we built it - Using data from the US Census, NOAA, Zillow and OpenPV, we built a Machine Learning Algorithm in python and a web app to interface with the user.

Challenges we ran into - Lack of datasets, time spent building data,

Accomplishments that we're proud of - building a user-facing product and a good structure to build on with better data.

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