Artificial Intelligence for Automatic Monitoring of Respiratory Health Conditions in Smart Swine Farming

Author:

Lagua Eddiemar B.12ORCID,Mun Hong-Seok13ORCID,Ampode Keiven Mark B.14ORCID,Chem Veasna1ORCID,Kim Young-Hwa5,Yang Chul-Ju12ORCID

Affiliation:

1. Animal Nutrition and Feed Science Laboratory, Department of Animal Science and Technology, Sunchon National University, Suncheon 57922, Republic of Korea

2. Interdisciplinary Program in IT-Bio Convergence System (BK21 Plus), Sunchon National University, 255 Jungangno, Suncheon 57922, Republic of Korea

3. Department of Multimedia Engineering, Sunchon National University, Suncheon 57922, Republic of Korea

4. Department of Animal Science, College of Agriculture, Sultan Kudarat State University, Tacurong City 9800, Philippines

5. Interdisciplinary Program in IT-Bio Convergence System (BK21 Plus), Chonnam National University, Gwangju 61186, Republic of Korea

Abstract

Porcine respiratory disease complex is an economically important disease in the swine industry. Early detection of the disease is crucial for immediate response to the disease at the farm level to prevent and minimize the potential damage that it may cause. In this paper, recent studies on the application of artificial intelligence (AI) in the early detection and monitoring of respiratory disease in swine have been reviewed. Most of the studies used coughing sounds as a feature of respiratory disease. The performance of different models and the methodologies used for cough recognition using AI were reviewed and compared. An AI technology available in the market was also reviewed. The device uses audio technology that can monitor and evaluate the herd’s respiratory health status through cough-sound recognition and quantification. The device also has temperature and humidity sensors to monitor environmental conditions. It has an alarm system based on variations in coughing patterns and abrupt temperature changes. However, some limitations of the existing technology were identified. Substantial effort must be exerted to surmount the limitations to have a smarter AI technology for monitoring respiratory health status in swine.

Publisher

MDPI AG

Subject

General Veterinary,Animal Science and Zoology

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