Ruvinga, Stenford, Hunter, Gordon, Nebel, Jean-Christophe and Duran, Olga (2022) Prediction of honeybee swarms using audio signals and convolutional neural networks. In: Workshop on Edge AI for Smart Agriculture (EAISA 2022); 20-23 Jun 2022, Biarritz, France.
Abstract
Honeybees are of vital importance to both agriculture and ecology. Unfortunately, their populations have been in serious decline over recent years. Swarms from hives are both of great importance to wider success of a colony and of major significance to beekeepers. In this paper, we contribute to the challenge of predicting when a swarm is going to occur. We have employed a Convolutional Neural Network (CNN) approach applied to audio data recorded from hives. Our initial results are extremely encouraging, since they allow us to distinguish hives which are preparing to swarm from those which are not with high levels of accuracy.
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