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dc.contributor.author
Chelotti, Jose Omar  
dc.contributor.author
Vanrell, Sebastián Rodrigo  
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Milone, Diego Humberto  
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Utsumi, Santiago A.  
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Galli, Julio Ricardo  
dc.contributor.author
Rufiner, Hugo Leonardo  
dc.contributor.author
Giovanini, Leonardo Luis  
dc.date.available
2018-06-05T16:33:53Z  
dc.date.issued
2016-05  
dc.identifier.citation
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  
dc.identifier.issn
0168-1699  
dc.identifier.uri
http://hdl.handle.net/11336/47319  
dc.description.abstract
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.  
dc.format
application/pdf  
dc.language.iso
eng  
dc.publisher
Elsevier  
dc.rights
info:eu-repo/semantics/openAccess  
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/  
dc.subject
Acoustic Monitoring  
dc.subject
Jaw Movement Classification  
dc.subject
Real-Time Execution  
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Signal Processing  
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Cattle Grazing Behavior  
dc.subject.classification
Ciencias de la Computación  
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Ciencias de la Computación e Información  
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CIENCIAS NATURALES Y EXACTAS  
dc.title
A real-time algorithm for acoustic monitoring of ingestive behavior of grazing cattle  
dc.type
info:eu-repo/semantics/article  
dc.type
info:ar-repo/semantics/artículo  
dc.type
info:eu-repo/semantics/publishedVersion  
dc.date.updated
2018-05-31T21:01:23Z  
dc.journal.volume
127  
dc.journal.pagination
64-75  
dc.journal.pais
Países Bajos  
dc.journal.ciudad
Amsterdam  
dc.description.fil
Fil: Chelotti, Jose Omar. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional; Argentina  
dc.description.fil
Fil: Vanrell, Sebastián Rodrigo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional; Argentina  
dc.description.fil
Fil: Milone, Diego Humberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional; Argentina  
dc.description.fil
Fil: Utsumi, Santiago A.. Michigan State University; Estados Unidos  
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Fil: Galli, Julio Ricardo. Universidad Nacional de Rosario. Facultad de Ciencias Agrarias; Argentina  
dc.description.fil
Fil: Rufiner, Hugo Leonardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional; Argentina. Universidad Nacional de Entre Ríos. Facultad de Ingeniería; Argentina  
dc.description.fil
Fil: Giovanini, Leonardo Luis. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional; Argentina  
dc.journal.title
Computers and Eletronics in Agriculture  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S0168169916303076  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1016/j.compag.2016.05.015