Inspiration
My family has a farm and when we are unable to predict the weather it causes in a net loss.
What it does
The web app supports farmers' expertise by predicting future weather patterns and increasing global food production. By using weather data to predict weather and then using Claude to report on how weather concerns would influence grain farming, we were able to provide reccomendations for agriculture practices for prospective users.
How we built it
The frontend was built using React with TypeScript and styled using CSS. The backend was implemented using FastAPI with Python. Data processing and visualization were handled using the pandas and matplotlib libraries and data was stored using JSON-based storage.
Challenges we ran into
AI agent integration, open-source data.
Accomplishments that we're proud of
Creating a future year-long prediction, accessible UI that has a variety of features, integrate a multitude of models.
What we learned
We learned that climate is complex and data heavy topic, how to use a variety of new libraries and models such as Map Libre and SARIMA, and how to integrate an AI agent into our frontend.
What's next for Climate Crop
We want to increase the database that we have and create yearly calendars and predictions for a variety of cities. We would also like to further improve the prediction model to be more accurate and include other factors.
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