Information perception in modern poultry farming: A review

农业 感知 家禽养殖 自动化 保护 比例(比率) 机器人 业务 人工智能 知识管理 工程类 计算机科学 地理 兽医学 生物 医学 护理部 考古 神经科学 机械工程 地图学
作者
Dihua Wu,Di Cui,Mingchuan Zhou,Yibin Ying
出处
期刊:Computers and Electronics in Agriculture [Elsevier]
卷期号:199: 107131-107131 被引量:5
标识
DOI:10.1016/j.compag.2022.107131
摘要

Poultry farming is an essential industry of animal husbandry, which is developing in the direction of scale, intelligence and unmanned. Intelligent information perception ideas for different application scenarios are stimulated with the rapid development of sensors, information communication and robotics technologies and artificial intelligence-based information processing technologies worldwide. Intelligent perception of information in the poultry farming process is important for the liberation of labor, safeguarding animal welfare, and improving the automation and efficiency of poultry farming. In this review, the information perception framework in modern poultry farming has been analyzed to fully illustrate the important role of information perception in modern poultry farming. In addition, we have reviewed the research of information perception technology in poultry farming in 26 countries around the world. According to the different research goals, it is mainly divided into five aspects: individual poultry target perception, behavior recognition, health and environmental monitoring, and breeding-related robots. Some tables are provided to summarize and review research information on different topics. We found that for the information perception in poultry breeding, many challenges still need to be solved, such as the accurate perception of poultry individual information in complex environment, multi-scale monitoring of poultry house environment, intelligent disease diagnosis and exception handling, robot function expansion and multi-robot coordination. To achieve the goal of accurate, efficient, and intelligent perception of information in the unmanned poultry farming system, we have also pointed out the future research focus and development trends respectively by combining the characteristics of different problems.
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