Analysis of parameters in algorithms for signal processing for swarming of honeybees

Swarming is a natural event that causes economic losses for beekeepers and impacts the economic and ecological balance. Sound emitted by honeybees can be used for detection of swarming. The aim of this study is to find an approach for early detection of swarming using sound analysis. The Short Time Fourier Transform (STFT) was investigated based on two different interpretations: the filter bank and the overlap-add methods. The overlap-add interpretation showed better execution time compared to the filter bank and decimated filter bank approaches. It also gave satisfying results in its spectro-temporal representation of the audio signals generated by the bees during swarming.