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The Research Progress of Vision-Based Artificial Intelligence in Smart Pig Farming
Pork accounts for an important proportion of livestock products. For pig farming, a lot of manpower, material resources and time are required to monitor pig health and welfare. As the number of pigs in farming increases, the continued use of traditional monitoring methods may cause stress and harm t...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9460267/ https://www.ncbi.nlm.nih.gov/pubmed/36080994 http://dx.doi.org/10.3390/s22176541 |
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author | Wang, Shunli Jiang, Honghua Qiao, Yongliang Jiang, Shuzhen Lin, Huaiqin Sun, Qian |
author_facet | Wang, Shunli Jiang, Honghua Qiao, Yongliang Jiang, Shuzhen Lin, Huaiqin Sun, Qian |
author_sort | Wang, Shunli |
collection | PubMed |
description | Pork accounts for an important proportion of livestock products. For pig farming, a lot of manpower, material resources and time are required to monitor pig health and welfare. As the number of pigs in farming increases, the continued use of traditional monitoring methods may cause stress and harm to pigs and farmers and affect pig health and welfare as well as farming economic output. In addition, the application of artificial intelligence has become a core part of smart pig farming. The precision pig farming system uses sensors such as cameras and radio frequency identification to monitor biometric information such as pig sound and pig behavior in real-time and convert them into key indicators of pig health and welfare. By analyzing the key indicators, problems in pig health and welfare can be detected early, and timely intervention and treatment can be provided, which helps to improve the production and economic efficiency of pig farming. This paper studies more than 150 papers on precision pig farming and summarizes and evaluates the application of artificial intelligence technologies to pig detection, tracking, behavior recognition and sound recognition. Finally, we summarize and discuss the opportunities and challenges of precision pig farming. |
format | Online Article Text |
id | pubmed-9460267 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-94602672022-09-10 The Research Progress of Vision-Based Artificial Intelligence in Smart Pig Farming Wang, Shunli Jiang, Honghua Qiao, Yongliang Jiang, Shuzhen Lin, Huaiqin Sun, Qian Sensors (Basel) Review Pork accounts for an important proportion of livestock products. For pig farming, a lot of manpower, material resources and time are required to monitor pig health and welfare. As the number of pigs in farming increases, the continued use of traditional monitoring methods may cause stress and harm to pigs and farmers and affect pig health and welfare as well as farming economic output. In addition, the application of artificial intelligence has become a core part of smart pig farming. The precision pig farming system uses sensors such as cameras and radio frequency identification to monitor biometric information such as pig sound and pig behavior in real-time and convert them into key indicators of pig health and welfare. By analyzing the key indicators, problems in pig health and welfare can be detected early, and timely intervention and treatment can be provided, which helps to improve the production and economic efficiency of pig farming. This paper studies more than 150 papers on precision pig farming and summarizes and evaluates the application of artificial intelligence technologies to pig detection, tracking, behavior recognition and sound recognition. Finally, we summarize and discuss the opportunities and challenges of precision pig farming. MDPI 2022-08-30 /pmc/articles/PMC9460267/ /pubmed/36080994 http://dx.doi.org/10.3390/s22176541 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Wang, Shunli Jiang, Honghua Qiao, Yongliang Jiang, Shuzhen Lin, Huaiqin Sun, Qian The Research Progress of Vision-Based Artificial Intelligence in Smart Pig Farming |
title | The Research Progress of Vision-Based Artificial Intelligence in Smart Pig Farming |
title_full | The Research Progress of Vision-Based Artificial Intelligence in Smart Pig Farming |
title_fullStr | The Research Progress of Vision-Based Artificial Intelligence in Smart Pig Farming |
title_full_unstemmed | The Research Progress of Vision-Based Artificial Intelligence in Smart Pig Farming |
title_short | The Research Progress of Vision-Based Artificial Intelligence in Smart Pig Farming |
title_sort | research progress of vision-based artificial intelligence in smart pig farming |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9460267/ https://www.ncbi.nlm.nih.gov/pubmed/36080994 http://dx.doi.org/10.3390/s22176541 |
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