As the price of eggs rises so does the demand? How can we maintain this strenuous supply and demand relationship given the current conditions regarding livestock?
Inspiration: Rising Price in eggs has one major factor, the Avian Flu
What it does: WingGuard uses a trained predictive model to anticipate the likelihood that chickens in a flock may contract the Avian Flu
How we built it: We've trained an API through a dataset regarding information of locations that have and have not seen cases of the Avian flu in their livestock. We used this information to determine whether a livestock is at risk of infection due to proximity to other outbreaks.
Challenges we ran into: The model was strenuous process due to the limited amount of research available and the time constraints though it was achievable, however the integration of API via web development proved to be a cumbersome task.
Accomplishments that we're proud of: Training an accurate API model that will benefit those effected by the shortage in eggs.
What we learned: We learned about different ways to train models and different algorithms in order to see which would fit our model best. We also learned lots about cleaning and processing data and how important that truly can be in the machine learning process.
What's next for WingGuard: We hope to further refine our model and acheive a higher accuracy based on more relevant research and data. We also hope to further improve the UI of the website and allow for more information to be released because of our model.
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