Journal of Animal Science and Technology
Korean Society of Animal Science and Technology
Article

A Review of Sound-based Pig Monitoring for Enhanced Precision Production

Md Nasim Reza1,2, Md Razob Ali1, Md Asrakul Haque1, Hongbin Jin2, Hyunjin Kyoung3, Young Kyoung Choi4, Gookhwan Kim5, Sun-Ok Chung1,2,*
1Department of Agricultural Machinery Engineering, Graduate School, Chungnam National University, Daejeon 34134, Korea.
2Department of Smart Agricultural Systems, Graduate School, Chungnam National University, Daejeon 34134, Korea.
3Division of Animal and Dairy Science, Chungnam National University, Daejeon 34134, Korea.
4DAWOON Co., Ltd., Incheon 22847, Korea.
5National Institute of Agricultural Sciences, Rural Development Administration, Jeonju 54875, Korea.
*Corresponding Author: Sun-Ok Chung, Department of Agricultural Machinery Engineering, Graduate School, Chungnam National University, Daejeon 34134, Korea, Republic of. Department of Smart Agricultural Systems, Graduate School, Chungnam National University, Daejeon 34134, Korea, Republic of. E-mail: sochung@cnu.ac.kr.

© Copyright 2024 Korean Society of Animal Science and Technology. This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Received: Oct 17, 2024; Revised: Nov 18, 2024; Accepted: Nov 18, 2024

Published Online: Nov 19, 2024

Abstract

Pig farming is experiencing significant transformations, driven by technological advancements, which have greatly improved management practices and overall productivity. Sound-based technologies are emerging as a valuable tool in enhancing precision pig farming. This review explores the advancements in sound-based technologies and their role in improving precision pig farming through enhanced monitoring of health, behavior, and environmental conditions. When strategically placed on farms, non-invasive technologies such as microphones and sound sensors can continuously collect data without disturbing the animals, making them highly efficient. Farmers using sound data, can monitor key factors such as respiratory conditions, stress levels, and social behaviors, leading to improved animal welfare and optimized production. Advancements in sensor technology and data analytics have enhanced the capabilities of sound-based precision systems in pig farming. The integration of machine learning and artificial intelligence (AI) is further enhancing the capacity to interpret complex sound patterns, enabling the automated detection of abnormal behaviors or health issues. Moreover, sound-based precision technologies offer solutions for improving environmental sustainability and resource management in pig farming. By continuously monitoring ventilation, feed distribution, and other key factors, these systems optimize resource use, reduce energy consumption, and detect stressors such as heat and poor air quality. The integration of sound technologies with other precision farming tools, such as physiological monitoring sensors and automated feeding systems, further enhances farm management and productivity. However, despite the advantages, challenges remain in terms of low accuracy and high initial costs, and further research is needed to improve specificity across different pig breeds and environmental conditions. Nonetheless, acoustic technologies hold immense promise for pig farming, offering enhanced management, an optimized performance, and improved animal welfare. Continued research can refine these tools and address the challenges, paving the way for a more efficient, profitable, and sustainable future for the industry.

Keywords: Smart livestock production; Pig health monitoring; ig behavior; Respiratory diseases; Sound sensor; Machine learning