Frequency Analysis of Honey Bee Buzz for Automatic Recognition of Health Status: A Preliminary Study

Abstract

The study of honey bee health has received special attention in the last years.Researchers has been monitoring physical variables to determinate the status of the colony.This is a first approach in the development of a real time monitoring system to provide useful information to beekeepers that will help them to prevent colony losses.This study presents an analysis of the sound from two colonies of bees in the Mel frequency domain.The first is a healthy colony with queen and the second one is a hive with no queen and with a reduced population.Sound samples were acquired for each colony and characterized using Mel Frequency Cepstral Coefficients (MFCC).To summarizes the information, statistical descriptors was obtained for each Mel coefficient.An exploratory analysis of samples revealed two different hive characteristics; the presence and lack of a queen bee.For honey bee buzz recognition, a Logistic Regression Model was used.The preliminary results show that it is possible to classify both characteristics obtaining high classification rates using a reduced set of features.