On acoustic monitoring of farm environments

Abstract

Green revolution suggests that agriculture systems, such as farms turn into dynamic entities boosting animal production in an eco-friendly way. In this direction, we propose exploiting the acoustic modality for farm monitoring. Such information could be used in a stand-alone or complimentary mode to monitor the farm constantly and provide a great level of detail. To this end, we designed a scheme classifying the vocalizations produced by farm animals. We employed a feature set able to capture diverse characteristics of generalized sound events seen from different domain representations (time, frequency, and wavelet). These are modeled using state of the art generative and discriminative classification schemes. We performed extensive experiments on a publicly available dataset, where we report encouraging recognition rates.