When we first entered the Hackathon, we set out to find an agricultural problem we could attempt to solve. While the challenges provided a few common and large-scale problems, we discovered an unsung one: farmers in the United States have always been under the control of "distributers," who are just middle men contributing nothing essential to the process. Our team has embarked on a mission to create a way for farmers to be freed.

What it does

It provides a marketplace for farmers to input what crops they are selling and a few descriptors (quantity, price, GMO/non-GMO, and a short description) and buyers to input what they are looking to buy. We then created a ranking algorithm to match farmers to buyers based on these factors, and then users are able to connect with and message potential partners. The last step was to use a machine learning algorithm to create a recommendation process for buyers based off of historical data of crop prices vs temperature, rainfall, and weather.

How we built it

We built the UI on Android Studio and coded the backend on Java, which was simple to integrate together.

Challenges we ran into

Several technical aspects of designing the UI gave us difficulty, but we were able to solve each challenge with enough time.

Accomplishments that we're proud of

We're proud of making an entire app in 24 hours, and specifically being able to create and integrate smart ranking and recommendation algorithms.

What we learned

We learned valuable skills integrating coding in teams (this is our first Hackathon!) and being able to plan out a short-term project.

What's next for Farma

We intend to take our recommendation and ranking algorithms a bit further by involving more variables and improving accuracy, because those are the most interesting aspects of Farma.

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