A Framework for Poultry Diseases Monitoring System Using K- Nearest Neighbor (KNN) Algorithm

Abstract

The absence of disease is the most crucial element in growth and productivity 
of chickens raised for food. Reduced production and a high death rate can result 
from the temperature and humidity in the cage being unmonitored and 
unregulated. A farm can be completely destroyed in a matter of minutes by illnesses 
like cholera, Newcastle disease, avian influenza, and paralysis in poultry. The KNN 
algorithm will be used in this study to automatically monitor these variables. Within 
the cage, a digital camera will be installed to record the birds' activity. The system 
will promptly report any abnormal indication since the algorithm will be educated 
on the typical behavior of a healthy or unhealthy bird based on the clinical 
indicators. The research's ultimate product will assist chicken farmers in keeping an 
eye on poultry illnesses. An additional benefit is that it is extremely beneficial to 
farm owners and the poultry industry as a whole, as over 40% of chicken deaths 
annually are caused by unrelated illnesses. Over the year, this significant loss will be 
greatly impacted by our studies. It's critical to focus on poultry infection at its 
earliest stages in order to also prevent negative outcomes.