A rising dilemma that many farmers encounter across the Africa and the Middle East are swarms of Locust. They are small hoppers/insects that can eat mass vegetation in a short amount of time. This leaves economically deprived and at a loss of resources to rebuild what has been destroyed.

What it does

Our project is based upon and easy to use app that allows farmers to enter their phone number and location of their farm. Using this information an automated Azure Function/Code will run. This code consists of a KNN machine learning model which predicts the next location for the locust swarms. The predicted location is compared with the farmer's location to determine if their farm is in danger of a swarm. They will be notified via SMS if they are in danger.

How we built it

We built this using Xcode to build the app and used python to build our comparison tools and machine learnign algorithm to predict the next swarm location using prior data from past years.

Challenges we ran into

Across the hackathon, our main challenge mainly included building the machine learning model because we had very little data to work with.

Accomplishments that we're proud of

We are very proud of the entire integration and how it can hopefully help farmers around the world that maybe in danger of these locust swarms.

What we learned

We learned alot during this hackathon. As high school students and in one of our first hackathons we grateful to have learned the process and the hardships that go along with participating in a hackathon.

What's next for Locust Locator

We hope to fully automate our app with our predictions to make the project seamless for farmers around the world.

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