Novel Method for Detecting Coughing Pigs with Audio-Visual Multimodality for Smart Agriculture Monitoring
While the pig industry is crucial in global meat consumption, accounting for 34% of total consumption, respiratory diseases in pigs can cause substantial economic losses to pig farms. To alleviate this issue, we propose an advanced audio-visual monitoring system for the early detection of coughing,...
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-11-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/24/22/7232 |
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| _version_ | 1846152513827373056 |
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| author | Heechan Chae Junhee Lee Jonggwan Kim Sejun Lee Jonguk Lee Yongwha Chung Daihee Park |
| author_facet | Heechan Chae Junhee Lee Jonggwan Kim Sejun Lee Jonguk Lee Yongwha Chung Daihee Park |
| author_sort | Heechan Chae |
| collection | DOAJ |
| description | While the pig industry is crucial in global meat consumption, accounting for 34% of total consumption, respiratory diseases in pigs can cause substantial economic losses to pig farms. To alleviate this issue, we propose an advanced audio-visual monitoring system for the early detection of coughing, a key symptom of respiratory diseases in pigs, that will enhance disease management and animal welfare. The proposed system is structured into three key modules: the cough sound detection (CSD) module, which detects coughing sounds using audio data; the pig object detection (POD) module, which identifies individual pigs in video footage; and the coughing pig detection (CPD) module, which pinpoints which pigs are coughing among the detected pigs. These modules, using a multimodal approach, detect coughs from continuous audio streams amidst background noise and accurately pinpoint specific pens or individual pigs as the source. This method enables continuous 24/7 monitoring, leading to efficient action and reduced human labor stress. It achieved a substantial detection accuracy of 0.95 on practical data, validating its feasibility and applicability. The potential to enhance farm management and animal welfare is shown through proposed early disease detection. |
| format | Article |
| id | doaj-art-b4301b37c2a643ee891b93e23f3793f8 |
| institution | Kabale University |
| issn | 1424-8220 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj-art-b4301b37c2a643ee891b93e23f3793f82024-11-26T18:21:12ZengMDPI AGSensors1424-82202024-11-012422723210.3390/s24227232Novel Method for Detecting Coughing Pigs with Audio-Visual Multimodality for Smart Agriculture MonitoringHeechan Chae0Junhee Lee1Jonggwan Kim2Sejun Lee3Jonguk Lee4Yongwha Chung5Daihee Park6Info Valley Korea Co., Ltd., Anyang 14067, Republic of KoreaInfo Valley Korea Co., Ltd., Anyang 14067, Republic of KoreaInfo Valley Korea Co., Ltd., Anyang 14067, Republic of KoreaInfo Valley Korea Co., Ltd., Anyang 14067, Republic of KoreaDepartment of Computer Convergence Software, Korea University, Sejong 30019, Republic of KoreaDepartment of Computer Convergence Software, Korea University, Sejong 30019, Republic of KoreaDepartment of Computer Convergence Software, Korea University, Sejong 30019, Republic of KoreaWhile the pig industry is crucial in global meat consumption, accounting for 34% of total consumption, respiratory diseases in pigs can cause substantial economic losses to pig farms. To alleviate this issue, we propose an advanced audio-visual monitoring system for the early detection of coughing, a key symptom of respiratory diseases in pigs, that will enhance disease management and animal welfare. The proposed system is structured into three key modules: the cough sound detection (CSD) module, which detects coughing sounds using audio data; the pig object detection (POD) module, which identifies individual pigs in video footage; and the coughing pig detection (CPD) module, which pinpoints which pigs are coughing among the detected pigs. These modules, using a multimodal approach, detect coughs from continuous audio streams amidst background noise and accurately pinpoint specific pens or individual pigs as the source. This method enables continuous 24/7 monitoring, leading to efficient action and reduced human labor stress. It achieved a substantial detection accuracy of 0.95 on practical data, validating its feasibility and applicability. The potential to enhance farm management and animal welfare is shown through proposed early disease detection.https://www.mdpi.com/1424-8220/24/22/7232agriculture ITsmart agriculture monitoringaudio-visual datapig cough detection |
| spellingShingle | Heechan Chae Junhee Lee Jonggwan Kim Sejun Lee Jonguk Lee Yongwha Chung Daihee Park Novel Method for Detecting Coughing Pigs with Audio-Visual Multimodality for Smart Agriculture Monitoring Sensors agriculture IT smart agriculture monitoring audio-visual data pig cough detection |
| title | Novel Method for Detecting Coughing Pigs with Audio-Visual Multimodality for Smart Agriculture Monitoring |
| title_full | Novel Method for Detecting Coughing Pigs with Audio-Visual Multimodality for Smart Agriculture Monitoring |
| title_fullStr | Novel Method for Detecting Coughing Pigs with Audio-Visual Multimodality for Smart Agriculture Monitoring |
| title_full_unstemmed | Novel Method for Detecting Coughing Pigs with Audio-Visual Multimodality for Smart Agriculture Monitoring |
| title_short | Novel Method for Detecting Coughing Pigs with Audio-Visual Multimodality for Smart Agriculture Monitoring |
| title_sort | novel method for detecting coughing pigs with audio visual multimodality for smart agriculture monitoring |
| topic | agriculture IT smart agriculture monitoring audio-visual data pig cough detection |
| url | https://www.mdpi.com/1424-8220/24/22/7232 |
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