Inspiration
Because of a lack of public information on our first idea to make supply chain information accessible, we decided to go the other way and make a statistical tool on the consumer side.
What it does
AgVis takes advantage of publicly available crop production and nutritional data, relating the two by answering the questions, "How much of food do we make, and how much do we need?"
How we built it
We began with scraps of an older project built with React and a backend in Python + Flask. The new project through Next.js and a C utility into the mix. With the addition of modern UI libraries like NextUI and Recharts. We developed something not just useful, but easy on the eyes.
Challenges we ran into
We were first faced with how exactly to answer the objective and had to come up with specialized formulas based on what information was available. We whittled that down to its essential parts, then compiled them (through tiresome hours) into CSVs. The primary bottlenecks for our progress were the C utility that was responsible for interpreting and calculating the results of these formulas, and the React pages that had to display the data accurately and in an aesthetically acceptable way.
Accomplishments that we're proud of
- Creation of a functional webserver whose API was hooked up to a legitimate domain
- Being able to ideate and have the guts to pivot
- Experimentation with skills in web dev (3.js, Next.js, React, Flask)
- Efficient Git collaboration
What we learned
- How to engineer a webapp's backend
- Coordinated coding (outside of schoolwork)
- Research aggregating public data
What's next for AgVisualizer
- Improvements to support scale
- More research into the factors that affect waste, consumption, and scarcity in general
- Expandable database that efficiently aggregates public data
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