Audio Modulation Spectral Features for Improved Honeybee Colony Population Prediction

Honeybees (Apis mellifera) are vital to agriculture and biodiversity, serving as primary pollinators for numerous crops and wild plants. However, the decline in bee populations due to factors such as pesticides, pathogens, parasites, and climate variations poses a serious threat to food security and ecological balance. This study introduces the use of modulation spectral features, extracted from beehive acoustic signals, to better predict the strength of the honeybee colony. Experiments conducted on the public UrBAN dataset, comprised of over 3,000 hours of beehive audio recordings, show the proposed features offering improved predictive performance compared to traditional audio features. This work underscores the potential of automated, non-invasive acoustic monitoring systems to support sustainable beekeeping and ecological preservation.