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Artículo

A real-time algorithm for acoustic monitoring of ingestive behavior of grazing cattle

Chelotti, Jose OmarIcon ; Vanrell, Sebastián RodrigoIcon ; Milone, Diego HumbertoIcon ; Utsumi, Santiago A.; Galli, Julio Ricardo; Rufiner, Hugo LeonardoIcon ; Giovanini, Leonardo LuisIcon
Fecha de publicación: 05/2016
Editorial: Elsevier
Revista: Computers and Eletronics in Agriculture
ISSN: 0168-1699
Idioma: Inglés
Tipo de recurso: Artículo publicado
Clasificación temática:
Ciencias de la Computación

Resumen

Assessment of both grazing behavior and herbage intake are two very difficult tasks that can be concurrently accomplished by means of accurate detection, classification and measurement of grazing events such as chews, bites and chew-bites. It is well known that acoustic monitoring is among the best methods to automatically quantify and classify ingestive and rumination events in grazing animals. However, most existing methods of signal analysis appear to be computationally complex and costly, and are therefore difficult to implement. In this work, we present and test a novel analysis system called Chew-Bite Real-Time Algorithm (CBRTA) that works fully automatically in real-time to detect and classify ingestive events of grazing cattle. The system employs a directional wide-frequency microphone facing inwards on the forehead of animals, and a coupled signal analysis and decision logic algorithm that measures shape, amplitude, duration and energy of sound signals to iteratively detect and classify ingestive events. Performance and validation of the CBRTA was determined using two databases of grazing signals. Signals were recorded on dairy cows offered either, natural pasture (N=25), or experimental micro-swards in indoor controlled environment (N=50). The CBRTA exhibited a simple linear complexity capable to execute 50 times faster than real-time and without undermining overall recognition rate and accuracy when signals were processed at 4 kHz sampling frequency and 8 bits quantization. Furthermore, CBRTA was capable to detect ingestive events with a 97.4% success rate, while achieving up to 84.0% success for their classification as exclusive chews, bites or composite chew-bites. The methodology proposed with CBRTA has promising application in embedded microcomputer systems that necessarily depend on fast real-time execution to minimize computational load, power source and storage memory. Such a system can readily facilitate the transmission of processed data through wireless network or the storage in an onboard device.
Palabras clave: Acoustic Monitoring , Jaw Movement Classification , Real-Time Execution , Signal Processing , Cattle Grazing Behavior
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info:eu-repo/semantics/openAccess Excepto donde se diga explícitamente, este item se publica bajo la siguiente descripción: Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Unported (CC BY-NC-SA 2.5)
Identificadores
URI: http://hdl.handle.net/11336/47319
URL: http://www.sciencedirect.com/science/article/pii/S0168169916303076
DOI: http://dx.doi.org/10.1016/j.compag.2016.05.015
Colecciones
Articulos(CCT - SANTA FE)
Articulos de CTRO.CIENTIFICO TECNOL.CONICET - SANTA FE
Articulos(SINC(I))
Articulos de INST. DE INVESTIGACION EN SEÑALES, SISTEMAS E INTELIGENCIA COMPUTACIONAL
Citación
Chelotti, Jose Omar; Vanrell, Sebastián Rodrigo; Milone, Diego Humberto; Utsumi, Santiago A.; Galli, Julio Ricardo; et al.; A real-time algorithm for acoustic monitoring of ingestive behavior of grazing cattle; Elsevier; Computers and Eletronics in Agriculture; 127; 5-2016; 64-75
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