Embedded system for real-time monitoring of foraging behavior of grazing cattle using acoustic signals

Autores
Deniz, Nestor Nahuel; Chelotti, Jose Omar; Galli, Julio Ricardo; Planisich, Alejandra M.; Larripa, Marcelo J.; Rufiner, Hugo Leonardo; Giovanini, Leonardo Luis
Año de publicación
2017
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
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.
Fil: Deniz, Nestor Nahuel. 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
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
Fil: Galli, Julio Ricardo. Universidad Nacional de Rosario; Argentina
Fil: Planisich, Alejandra M.. Universidad Nacional de Rosario; Argentina
Fil: Larripa, Marcelo J.. Universidad Nacional de Rosario; Argentina
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; Argentina
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
Materia
Acoustic Monitoring
Embedded System
Microcontroller
Real-Time Operation
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/47041
Acceder
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network_name_str CONICET Digital (CONICET)
spelling Embedded system for real-time monitoring of foraging behavior of grazing cattle using acoustic signalsDeniz, Nestor NahuelChelotti, Jose OmarGalli, Julio RicardoPlanisich, Alejandra M.Larripa, Marcelo J.Rufiner, Hugo LeonardoGiovanini, Leonardo LuisAcoustic MonitoringEmbedded SystemMicrocontrollerReal-Time Operationhttps://purl.org/becyt/ford/2.2https://purl.org/becyt/ford/2Estimating 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.Fil: Deniz, Nestor Nahuel. 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; ArgentinaFil: 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; ArgentinaFil: Galli, Julio Ricardo. Universidad Nacional de Rosario; ArgentinaFil: Planisich, Alejandra M.. Universidad Nacional de Rosario; ArgentinaFil: Larripa, Marcelo J.. Universidad Nacional de Rosario; ArgentinaFil: 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; ArgentinaFil: 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; ArgentinaElsevier2017-06info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/47041Deniz, Nestor Nahuel; Chelotti, Jose Omar; Galli, Julio Ricardo; Planisich, Alejandra M.; Larripa, Marcelo J.; et al.; Embedded system for real-time monitoring of foraging behavior of grazing cattle using acoustic signals; Elsevier; Computers and Eletronics in Agriculture; 138; 6-2017; 167-1740168-1699CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/http://linkinghub.elsevier.com/retrieve/pii/S016816991631242Xinfo:eu-repo/semantics/altIdentifier/doi/10.1016/j.compag.2017.04.024info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T09:52:17Zoai:ri.conicet.gov.ar:11336/47041instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-03 09:52:17.879CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Embedded system for real-time monitoring of foraging behavior of grazing cattle using acoustic signals
title Embedded system for real-time monitoring of foraging behavior of grazing cattle using acoustic signals
spellingShingle Embedded system for real-time monitoring of foraging behavior of grazing cattle using acoustic signals
Deniz, Nestor Nahuel
Acoustic Monitoring
Embedded System
Microcontroller
Real-Time Operation
title_short Embedded system for real-time monitoring of foraging behavior of grazing cattle using acoustic signals
title_full Embedded system for real-time monitoring of foraging behavior of grazing cattle using acoustic signals
title_fullStr Embedded system for real-time monitoring of foraging behavior of grazing cattle using acoustic signals
title_full_unstemmed Embedded system for real-time monitoring of foraging behavior of grazing cattle using acoustic signals
title_sort Embedded system for real-time monitoring of foraging behavior of grazing cattle using acoustic signals
dc.creator.none.fl_str_mv Deniz, Nestor Nahuel
Chelotti, Jose Omar
Galli, Julio Ricardo
Planisich, Alejandra M.
Larripa, Marcelo J.
Rufiner, Hugo Leonardo
Giovanini, Leonardo Luis
author Deniz, Nestor Nahuel
author_facet Deniz, Nestor Nahuel
Chelotti, Jose Omar
Galli, Julio Ricardo
Planisich, Alejandra M.
Larripa, Marcelo J.
Rufiner, Hugo Leonardo
Giovanini, Leonardo Luis
author_role author
author2 Chelotti, Jose Omar
Galli, Julio Ricardo
Planisich, Alejandra M.
Larripa, Marcelo J.
Rufiner, Hugo Leonardo
Giovanini, Leonardo Luis
author2_role author
author
author
author
author
author
dc.subject.none.fl_str_mv Acoustic Monitoring
Embedded System
Microcontroller
Real-Time Operation
topic Acoustic Monitoring
Embedded System
Microcontroller
Real-Time Operation
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.2
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv 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.
Fil: Deniz, Nestor Nahuel. 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
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
Fil: Galli, Julio Ricardo. Universidad Nacional de Rosario; Argentina
Fil: Planisich, Alejandra M.. Universidad Nacional de Rosario; Argentina
Fil: Larripa, Marcelo J.. Universidad Nacional de Rosario; Argentina
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; Argentina
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
description 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.
publishDate 2017
dc.date.none.fl_str_mv 2017-06
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/47041
Deniz, Nestor Nahuel; Chelotti, Jose Omar; Galli, Julio Ricardo; Planisich, Alejandra M.; Larripa, Marcelo J.; et al.; Embedded system for real-time monitoring of foraging behavior of grazing cattle using acoustic signals; Elsevier; Computers and Eletronics in Agriculture; 138; 6-2017; 167-174
0168-1699
CONICET Digital
CONICET
url http://hdl.handle.net/11336/47041
identifier_str_mv Deniz, Nestor Nahuel; Chelotti, Jose Omar; Galli, Julio Ricardo; Planisich, Alejandra M.; Larripa, Marcelo J.; et al.; Embedded system for real-time monitoring of foraging behavior of grazing cattle using acoustic signals; Elsevier; Computers and Eletronics in Agriculture; 138; 6-2017; 167-174
0168-1699
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://linkinghub.elsevier.com/retrieve/pii/S016816991631242X
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.compag.2017.04.024
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.13397

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