Lagua Eddiemar B, Mun Hong-Seok, Ampode Keiven Mark B, Chem Veasna, Kim Young-Hwa, Yang Chul-Ju
Animal Nutrition and Feed Science Laboratory, Department of Animal Science and Technology, Sunchon National University, Suncheon 57922, Republic of Korea.
Interdisciplinary Program in IT-Bio Convergence System (BK21 Plus), Sunchon National University, 255 Jungangno, Suncheon 57922, Republic of Korea.
Animals (Basel). 2023 Jun 2;13(11):1860. doi: 10.3390/ani13111860.
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.
猪呼吸道疾病综合征是养猪业中一种具有重要经济影响的疾病。疾病的早期检测对于在农场层面立即应对该疾病以预防和尽量减少其可能造成的潜在损害至关重要。本文综述了人工智能（AI）在猪呼吸道疾病早期检测和监测中的应用的最新研究。大多数研究将咳嗽声音作为呼吸道疾病的一个特征。对使用AI进行咳嗽识别的不同模型的性能和所采用的方法进行了综述和比较。还对市场上现有的一种AI技术进行了综述。该设备使用音频技术，可通过咳嗽声音识别和量化来监测和评估猪群的呼吸道健康状况。该设备还具有温度和湿度传感器以监测环境条件。它有一个基于咳嗽模式变化和温度突然变化的报警系统。然而，也发现了现有技术的一些局限性。必须付出巨大努力来克服这些局限性，以拥有更智能的用于监测猪呼吸道健康状况的AI技术。
