Real-time analysis of chicken embryo sounds to monitor different incubation stages
The objective of this paper is to develop an algorithm that could be used in order to reduce the spread of chicken hatching in industrial incubators for chicken eggs. The approach that is used is based on frequency analysis of sounds recorded inside the industrial incubator and aims at identifying the time at which all the eggs inside the incubator have reached the internal pipping stage. The developed algorithm is able to be calibrated automatically in order to adjust for sounds around the incubator and the acoustics of every incubator. The algorithm has been implemented in a Digital Signal Processor and applied in real-time in an industrial environment. It is shown that the algorithm can correctly identify the time at which 9398% of the eggs have had been in the internal pipping stage. This level of accuracy is considered adequate for a practical application focusing on reduction of the hatching window.
sound analysis chicken incubation precision livestock farming digital signal processing bioacoustics zoosemiotic