Behavior Classification of A Grazing Goat in the Argentine Monte Desert by Using Inertial Sensors

The knowledge generated by animal behavior studies has been gaining importance due to it can be used to improve the efficiency of animal production systems. In recent years, sensor-based approaches for animal behavior classification has emerged as a promising alternative for analyzing animals grazin...

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Detalles Bibliográficos
Autores principales: Páez Lama, Sebastián, González, Rodrigo, Catania, Carlos
Formato: Objeto de conferencia
Lenguaje:Inglés
Publicado: 2019
Materias:
Ciencias Informáticas
Goat
Classification
Behaviour
Inertial sensors
Argentine Monte Desert
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/88075
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-88075
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Informáticas
Goat
Classification
Behaviour
Inertial sensors
Argentine Monte Desert
spellingShingle Ciencias Informáticas
Goat
Classification
Behaviour
Inertial sensors
Argentine Monte Desert
Páez Lama, Sebastián
González, Rodrigo
Catania, Carlos
Behavior Classification of A Grazing Goat in the Argentine Monte Desert by Using Inertial Sensors
topic_facet Ciencias Informáticas
Goat
Classification
Behaviour
Inertial sensors
Argentine Monte Desert
description The knowledge generated by animal behavior studies has been gaining importance due to it can be used to improve the efficiency of animal production systems. In recent years, sensor-based approaches for animal behavior classification has emerged as a promising alternative for analyzing animals grazing patterns. In the present article it is proposed the use of a classification system based on inertial sensors for identifying a goat’s grazing behavior in the Argentine Monte Desert. The data acquisition system is based on commercial off-the-self devices. It is used to create a reliable dataset for performing the animal behavior predictions. By fixing the system on the head of a goat it was possible to log its movements when it was grazing in a natural pasture. A preliminary version of the dataset is evaluated using a classical statistical learning algorithm. Results show that goat activities can be predicted with an average precision value above 85% and a recall of 84%.
format Objeto de conferencia
Objeto de conferencia
author Páez Lama, Sebastián
González, Rodrigo
Catania, Carlos
author_facet Páez Lama, Sebastián
González, Rodrigo
Catania, Carlos
author_sort Páez Lama, Sebastián
title Behavior Classification of A Grazing Goat in the Argentine Monte Desert by Using Inertial Sensors
title_short Behavior Classification of A Grazing Goat in the Argentine Monte Desert by Using Inertial Sensors
title_full Behavior Classification of A Grazing Goat in the Argentine Monte Desert by Using Inertial Sensors
title_fullStr Behavior Classification of A Grazing Goat in the Argentine Monte Desert by Using Inertial Sensors
title_full_unstemmed Behavior Classification of A Grazing Goat in the Argentine Monte Desert by Using Inertial Sensors
title_sort behavior classification of a grazing goat in the argentine monte desert by using inertial sensors
publishDate 2019
url http://sedici.unlp.edu.ar/handle/10915/88075
work_keys_str_mv AT paezlamasebastian behaviorclassificationofagrazinggoatintheargentinemontedesertbyusinginertialsensors
AT gonzalezrodrigo behaviorclassificationofagrazinggoatintheargentinemontedesertbyusinginertialsensors
AT cataniacarlos behaviorclassificationofagrazinggoatintheargentinemontedesertbyusinginertialsensors
bdutipo_str Repositorios
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