ArticleSensors (Basel, Switzerland)2024
Novel Method for Detecting Coughing Pigs with Audio-Visual Multimodality for Smart Agriculture Monitoring.
Article in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Exploratory Room-Level Acoustic Soundscape Monitoring of Cough-like Events Under Standard and Ventilation-Restricted Pig-Housing Conditions Using Audio Spectrogram Transformer.Animals : an open access journal from MDPI · 2026Article
- Pilot Room-Level Acoustic and Physiological Monitoring of Respiratory Disturbance in Pigs Following ExperimentalVeterinary sciences · 2026Article
- Classification of Goat Vocalization via Lightweight Machine Learning and High-Dimensional Acoustic Features.Animals : an open access journal from MDPI · 2026Article
- A Conformer-Based Time-Frequency Decoupling Network for Pig Vocalization Behavior Classification.Animals : an open access journal from MDPI · 2026Article
- JMSC: Joint Spatial-Temporal Modeling with Semantic Completion for Audio-Visual Learning.Sensors (Basel, Switzerland) · 2026Article
- Advances in Audio Classification and Artificial Intelligence for Respiratory Health and Welfare Monitoring in Swine.Biology · 2026Review
- ASAS-NANP Symposium: Mathematical modeling in animal nutrition: revolutionizing animal farming with artificial intelligence: trends, challenges, and opportunities.Journal of animal science · 2026Review
- Pig cough detection using deep features and an improved SKA-TDNN model.Tropical animal health and production · 2025Article
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Authors and funding
7 authors.
Funding
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Abstract
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.
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Registered trials
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