Trantor

Inspiration

Solar energy has unlimited potential and can provide enough renewable energy sources to improve environmental conditions. However, it isn't being used to its full potential due to the lack of information. Our role is to provide publicly available data to improve this situation.

What it does

Our program detects all solar panels on rooftops to determine where the bulk of solar panels are located.

How we built it

We built this program through python tensor flow machine learning and neural networks.

Challenges we ran into

The toughest challenge we ran into was collecting specific data for small areas of land or cities. Most of the data available about energy consumption and climate were general and only showed provincial averages.

Accomplishments that we're proud of

We ware able to make a prototype that works for small samples of land. This prototype can easily be upscaled and used globally

What we learned

Through this experience, we learned how to make easy, simple, and effective graphs using Microsoft Power BI.

What's next for Trantor

Our next goal is to use our prototype on a global scale. We can then use the data provided by our program to effectively increase solar energy consumption