Symmetrized Dot Pattern Representation of Audio Measurements for Queen Bee Presence Classification

The queen bee plays a vital role in the beehive because she produces chemical scents that help regulate the colony's unity and can lay eggs. For this reason, it is essential to detect the queen's absence to guarantee a prompt intervention of the beekeeper. However, the manual search for the queen is a laborious and repetitive task for the beekeeper and can perturb the beehive's normal life cycle. The analysis of the sound emitted by the bees can give information about the state of the beehive and the queen's presence. In this scenario, this work presents an algorithm for queen bee presence classification taking into consideration a Symmetrized Dot Pattern (SDP) representation of the audio measurements performed by an instrumented beehive. Starting from a dataset of acoustic measurements acquired in a real scenario, different experiments have been carried out in order to test the performance of the proposed system confirming its potentiality.