Our goal is to make the daily lives of farmers easier and more efficient. The conventional methods that farmers use to maintain barn conditions are outdated and stand to be optimized. Most farmer set their barn settings and don’t often modify this for months or years on end. We have created an application that would allow poultry farmers to enter information regarding their barn conditions and we would allow them to improve their conditions to optimize chicken yield, and thus drastically improve productivity.

Given all sensor data for several barns in various locations across the country, we were able to create a deep-learning algorithm that is able to predict the expected weight of the chickens produced, as well as creating recommendations for barn improvements to improve productivity. Would allow farmers to optimize their barn settings in order to achieve maximum productivity. Takes all available data into account as well as external factors, ex. weather.

As we went through the data, we saw a lot of issues how it was measured, missing data points, non-symmetrical timestamps, lack of detail. For example, when trying to look for the individual amount of feed that chickens received, the only data stored is the total amount of feed for the entire barn. We were not able to apply our algorithm to the swine dataset due to a lack of data. By expanding into other animals, we would allow farmers to optimize all factors of raising livestock, and thus maximize productivity. As of present, we only allow the farmer to enter a certain number of information regarding the livestock, as the corresponding datasets were often corrupt.

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