This project is all about determining the stress factor of broilers, based upon a sample of their noice. Often, the farmers ear can easily detect the difference between stressed or relaxed broilers within the first seconds of sound. However, designing a computer program to do this turns out to be a bit trickier.
This project is al about the design of a computer program to model acoustic analysis of broiler sound for determining the stable stress factor. The model is constructed using recorded samples of stable sound. The samples are processed using acoustic analysis and then applied to an artificial intelligence/machine learning algorithm to learn broiler-specific traits. The used algorithm was tested on a model that determines human gender based on voice with high accuracy.
The next step is to collect more broiler sound samples that are labeled using farmers’ expertise.