Artificial intelligence in animal farming: A systematic literature review

被引:111
作者
Bao, Jun [1 ,3 ]
Xie, Qiuju [2 ,3 ]
机构
[1] Northeast Agr Univ, Coll Anim Sci & Technol, Harbin 150030, Peoples R China
[2] Northeast Agr Univ, Coll Elect & Informat, Harbin 150030, Peoples R China
[3] Key Lab Swine Facil Engn, Minist Agr, Harbin, Peoples R China
基金
中国国家自然科学基金;
关键词
Artificial intelligence; Behavior detection; Sustainable production; Animal welfare; NEURAL-NETWORK; DAIRY-COWS; AGGRESSIVE BEHAVIORS; ENERGY-CONSUMPTION; FEATURE-EXTRACTION; DRINKING BEHAVIOR; PRESSURE SENSOR; IMAGE-ANALYSIS; RECOGNITION; IDENTIFICATION;
D O I
10.1016/j.jclepro.2021.129956
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Some scientific researches have been conducted recently based on Artificial Intelligence (AI) to solve animal welfare and health related problems. However, no review study was conducted to assess the potential of AI in solving the diverse application problems in several animal species including ruminants, pig and poultry. To fill in this gap, this paper provides a systematic review on scientific research advancement in AI related animal farming based on 131 research publications over the past four decades. It was shown that the number of related studies has increased significantly since 2016, and the most intensive studies were focused on animal behavior detection and recognition, and concentrated mostly on farm animal species of pig (37.95%), cattle (37.44%), and poultry (16.92%); Also, most scientific research in animal farming driven by sensors and AI models were focused on data collection, processing, assessment, and analysis in the areas of animal behavior detection, disease monitoring, growth estimation, and environment monitoring at the experimental stage; Moreover, some technical challenges on AI like the accuracy and cost need to be improved before it could come into use in the commercial animal farming.
引用
收藏
页数:13
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