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Cited 12 time in webofscience Cited 17 time in scopus
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The Application of Cameras in Precision Pig Farming: An Overview for Swine-Keeping Professionalsopen access

Authors
Arulmozhi, ElanchezhianBhujel, AnilMoon, Byeong-EunKim, Hyeon-Tae
Issue Date
Aug-2021
Publisher
MDPI
Keywords
early disease detection; pig behavior; precision livestock farming; pig identification; cameras
Citation
ANIMALS, v.11, no.8
Indexed
SCIE
SCOPUS
Journal Title
ANIMALS
Volume
11
Number
8
URI
https://scholarworks.bwise.kr/gnu/handle/sw.gnu/3431
DOI
10.3390/ani11082343
Abstract
Simple Summary The preeminent purpose of precision livestock farming (PLF) is to provide affordable and straightforward solutions to severe problems with certainty. Some data collection techniques in PLF such as RFID are accurate but not affordable for small- and medium-sized farms. On the other hand, camera sensors are cheap, commonly available, and easily used to collect information compared to other sensor systems in precision pig farming. Cameras have ample chance to monitor pigs with high precision at an affordable cost. However, the lack of targeted information about the application of cameras in the pig industry is a shortcoming for swine farmers and researchers. This review describes the state of the art in 3D imaging systems (i.e., depth sensors and time-of-flight cameras), along with 2D cameras, for effectively identifying pig behaviors, and presents automated approaches for monitoring and investigating pigs' feeding, drinking, lying, locomotion, aggressive, and reproductive behaviors. In addition, the review summarizes the related literature and points out limitations to open up new dimensions for future researchers to explore. Pork is the meat with the second-largest overall consumption, and chicken, pork, and beef together account for 92% of global meat production. Therefore, it is necessary to adopt more progressive methodologies such as precision livestock farming (PLF) rather than conventional methods to improve production. In recent years, image-based studies have become an efficient solution in various fields such as navigation for unmanned vehicles, human-machine-based systems, agricultural surveying, livestock, etc. So far, several studies have been conducted to identify, track, and classify the behaviors of pigs and achieve early detection of disease, using 2D/3D cameras. This review describes the state of the art in 3D imaging systems (i.e., depth sensors and time-of-flight cameras), along with 2D cameras, for effectively identifying pig behaviors and presents automated approaches for the monitoring and investigation of pigs' feeding, drinking, lying, locomotion, aggressive, and reproductive behaviors.
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농업생명과학대학 (생물산업기계공학과)
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