SINC(I)   25518
INSTITUTO DE INVESTIGACION EN SEÑALES, SISTEMAS E INTELIGENCIA COMPUTACIONAL
Unidad Ejecutora - UE
artículos
Título:
Embedded system for real-time monitoring of foraging behavior of grazing cattle using acoustic signals
Autor/es:
DENIZ, NESTOR N.; PLANISICH, ALEJANDRA M.; GIOVANINI, LEONARDO L.; CHELOTTI, JOSÉ O.; LARRIPA, MARCELO J.; GALLI, JULIO R.; LEONARDO RUFINER, H.
Revista:
COMPUTERS AND ELETRONICS IN AGRICULTURE
Editorial:
ELSEVIER SCI LTD
Referencias:
Año: 2017 vol. 138 p. 167 - 174
ISSN:
0168-1699
Resumen:
Estimating forage intake and monitoring behavior of grazing livestock are difficult tasks. Real-time detection and classification of events like chew, bite and chew-bite are necessary to estimate that information. It is well-known that acoustic monitoring is one of the best ways to characterize feeding behavior in ruminants. Although several methods have been developed to detect and classify events, their implementation is restricted to desktop computers, fact that confines their application to off-line analysis of a reduced number of animals. In this work, we present the design and implementation of an electronic system specifically developed for real-time monitoring of feeding patterns in dairy cows. The system is based on an embedded circuit to process the sound produced by the animal in order to detect, classify and quantify events of ruminant feeding behavior. The system implements an algorithm recently developed, which was adapted to be executed on a microcontroller-based electronic system. Only the results of sound analysis are stored in flash memory units. In addition to sound information, data from a GPS receiver is also stored, thus building a package of information. A microcontroller with power management technology, combined with a high-efficiency harvesting power supply and power management firmware, enables long operational time (more than five days of continuous operation). The system was evaluated using audio signals derived from the feeding activity of dairy cows that were acquired under normal operational conditions. The system correctly detected 92% of the events (i.e. considering them as possible events without making a classification). When the three types of events (i.e. chew, bite and chew-bite) were considered for classification, the recognition rate was about 78%. These results were obtained using reference labels provided by experts in ruminant ingestive behavior. The technology presented within this publication is protected under the international patent application PCT/IB2015/053721.