Inspiration
We all care about global warming, and wanted to build a tool to visualize how we, as individuals, can make an impact.
What it does
Individuals can input their addresses and receive a estimate of how much power potential solar panels on their homes can generate per year. Governments can get an overview of the distribution of where solar panels are most useful.
How we built it
We used a full python stack. We used streamlit for the frontend, and flask for the API/backend.
Challenges we ran into
Our laptops did not provide adequate computing resources to handle the large geo datasets. But due to some issue with the encoding of the data files (.osm.bf), we weren't able to utilize the Azure resources either. Extracting the area from the geo data was very difficult, as we had to convert between different units (the initial data provided was unitless). For some reason, we were not able perform query searches on our TinyDB database. This meant we had to adapt and utilize python's dataframe structure itself in our server to serve API calls.
Accomplishments that we're proud of
Hopefully, we have something we can actually demo. Also, we didn't give up.
What we learned
A lot about python.
What's next for Solar Opposites
We'll see...
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