Automatic Detection and Recognition of Pig Wasting Diseases Using Sound Data in Audio Surveillance Systems
Automatic detection of pig wasting diseases is an important issue in the management of group-housed pigs. Further, respiratory diseases are one of the main causes of mortality among pigs and loss of productivity in intensive pig farming. In this study, we propose an efficient data mining solution fo...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2013-09-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | http://www.mdpi.com/1424-8220/13/10/12929 |
| _version_ | 1798040802244427776 |
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| author | Yongwha Chung Seunggeun Oh Jonguk Lee Daihee Park Hong-Hee Chang Suk Kim |
| author_facet | Yongwha Chung Seunggeun Oh Jonguk Lee Daihee Park Hong-Hee Chang Suk Kim |
| author_sort | Yongwha Chung |
| collection | DOAJ |
| description | Automatic detection of pig wasting diseases is an important issue in the management of group-housed pigs. Further, respiratory diseases are one of the main causes of mortality among pigs and loss of productivity in intensive pig farming. In this study, we propose an efficient data mining solution for the detection and recognition of pig wasting diseases using sound data in audio surveillance systems. In this method, we extract the Mel Frequency Cepstrum Coefficients (MFCC) from sound data with an automatic pig sound acquisition process, and use a hierarchical two-level structure: the Support Vector Data Description (SVDD) and the Sparse Representation Classifier (SRC) as an early anomaly detector and a respiratory disease classifier, respectively. Our experimental results show that this new method can be used to detect pig wasting diseases both economically (even a cheap microphone can be used) and accurately (94% detection and 91% classification accuracy), either as a standalone solution or to complement known methods to obtain a more accurate solution. |
| first_indexed | 2024-04-11T22:12:41Z |
| format | Article |
| id | doaj.art-8575d5e0522c48a38ef24956e410229e |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-11T22:12:41Z |
| publishDate | 2013-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-8575d5e0522c48a38ef24956e410229e2022-12-22T04:00:31ZengMDPI AGSensors1424-82202013-09-011310129291294210.3390/s131012929Automatic Detection and Recognition of Pig Wasting Diseases Using Sound Data in Audio Surveillance SystemsYongwha ChungSeunggeun OhJonguk LeeDaihee ParkHong-Hee ChangSuk KimAutomatic detection of pig wasting diseases is an important issue in the management of group-housed pigs. Further, respiratory diseases are one of the main causes of mortality among pigs and loss of productivity in intensive pig farming. In this study, we propose an efficient data mining solution for the detection and recognition of pig wasting diseases using sound data in audio surveillance systems. In this method, we extract the Mel Frequency Cepstrum Coefficients (MFCC) from sound data with an automatic pig sound acquisition process, and use a hierarchical two-level structure: the Support Vector Data Description (SVDD) and the Sparse Representation Classifier (SRC) as an early anomaly detector and a respiratory disease classifier, respectively. Our experimental results show that this new method can be used to detect pig wasting diseases both economically (even a cheap microphone can be used) and accurately (94% detection and 91% classification accuracy), either as a standalone solution or to complement known methods to obtain a more accurate solution.http://www.mdpi.com/1424-8220/13/10/12929pig wasting diseasessound datamel frequency cepstrum coefficientsupport vector data descriptionsparse representation classifier |
| spellingShingle | Yongwha Chung Seunggeun Oh Jonguk Lee Daihee Park Hong-Hee Chang Suk Kim Automatic Detection and Recognition of Pig Wasting Diseases Using Sound Data in Audio Surveillance Systems Sensors pig wasting diseases sound data mel frequency cepstrum coefficient support vector data description sparse representation classifier |
| title | Automatic Detection and Recognition of Pig Wasting Diseases Using Sound Data in Audio Surveillance Systems |
| title_full | Automatic Detection and Recognition of Pig Wasting Diseases Using Sound Data in Audio Surveillance Systems |
| title_fullStr | Automatic Detection and Recognition of Pig Wasting Diseases Using Sound Data in Audio Surveillance Systems |
| title_full_unstemmed | Automatic Detection and Recognition of Pig Wasting Diseases Using Sound Data in Audio Surveillance Systems |
| title_short | Automatic Detection and Recognition of Pig Wasting Diseases Using Sound Data in Audio Surveillance Systems |
| title_sort | automatic detection and recognition of pig wasting diseases using sound data in audio surveillance systems |
| topic | pig wasting diseases sound data mel frequency cepstrum coefficient support vector data description sparse representation classifier |
| url | http://www.mdpi.com/1424-8220/13/10/12929 |
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