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Stress Detection and Classification of Laying Hens by Sound Analysis

Authors
Lee, JongukNoh, ByeongjoonJang, SuinPark, DaiheeChung, YongwhaChang, Hong-Hee
Issue Date
4월-2015
Publisher
ASIAN-AUSTRALASIAN ASSOC ANIMAL PRODUCTION SOC
Keywords
Laying Hens; Stress Recognition; Sound Analysis; Monitoring System
Citation
ASIAN-AUSTRALASIAN JOURNAL OF ANIMAL SCIENCES, v.28, no.4, pp.592 - 598
Indexed
SCIE
SCOPUS
KCI
Journal Title
ASIAN-AUSTRALASIAN JOURNAL OF ANIMAL SCIENCES
Volume
28
Number
4
Start Page
592
End Page
598
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/93992
DOI
10.5713/ajas.14.0654
ISSN
1011-2367
Abstract
Stress adversely affects the wellbeing of commercial chickens, and comes with an economic cost to the industry that cannot be ignored. In this paper, we first develop an inexpensive and non-invasive, automatic online-monitoring prototype that uses sound data to notify producers of a stressful situation in a commercial poultry facility. The proposed system is structured hierarchically with three binary-classifier support vector machines. First, it selects an optimal acoustic feature subset from the sound emitted by the laying hens. The detection and classification module detects the stress from changes in the sound and classifies it into subsidiary sound types, such as physical stress from changes in temperature, and mental stress from fear. Finally, an experimental evaluation was performed using real sound data from an audio-surveillance system. The accuracy in detecting stress approached 96.2%, and the classification model was validated, confirming that the average classification accuracy was 96.7%, and that its recall and precision measures were satisfactory.
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Park, Dai Hee
과학기술대학 (컴퓨터융합소프트웨어학과)
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