人工智能在家禽养殖场管理和抗微生物药物耐药性中的应用

Reham A. Hosny, N. Alatfeehy, M. Abdelaty
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摘要

抗生素耐药性(AMR)是目前世界面临的最危险的危机之一。在动物中发现的抗菌素耐药性(AMR)出现了令人不安的上升,这种耐药性可能通过直接接触、环境污染和食物消费转移给人类。有效的家禽健康和福利管理以及家禽养殖场细菌感染的快速诊断可以减少对抗生素的需求,这反映在流行病和抗生素耐药性的传播上。思维互联网和机器学习是人工智能的分支,它们使智能自主系统与人类工人远程管理操作成为可能。机器学习技术在跟踪和预防家禽养殖场感染方面发挥着重要作用,这可以减少家禽对抗生素治疗的需求,从而限制耐抗生素病原体向人类的传播。这些信息由强大的处理计算机在海量存储设备的帮助下进一步分析,以寻找趋势和线索,以查明疾病爆发和耐药性病例的位置。利用这些知识将使将来预防流行病变得更加容易,从而减少对抗生素的需求。因此,这篇综述对目前家禽养殖场管理中的人工智能实践以及世界各地抗生素耐药性的机遇和担忧提供了见解。
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Application Of Artificial Intelligence In The Management Of Poultry Farms And Combating Antimicrobial Resistance
A ntimicrobial resistance (AMR) is currently one of the most danger-ous crises facing the world. There has been an unsettling rise in the antimicrobial resistance (AMR) identified in animals, which may transfer to people through direct contact, environmental pollution, and food consumption. Efficient poultry health and welfare management and quick diagnosis of bacterial infections in poultry farms can lessen the demand for antibiotics, which is reflected on the spreading of epidemics and AMR. Internet of thinking and machine learning are branches of Artificial intelligence that enable intelligent autonomous systems with human workers remotely managing operations. Machine learning technology plays a role in tracking and preventing infections in poultry farms, which can reduce the need for antibiotic treatment in poultry and, as a result, limit the transmission of antibiotic-resistant pathogens to humans. This information is further analyzed by powerful processing computers with the aid of massive storage devices to seek for trends and hints to pinpoint the locations of disease outbreaks and cases of resistance. The utilization of this knowledge will make it easier to prevent epidemics in the future, reducing the demand for antibiotics. Therefore, this review offers insight on the current AI practices in the management of poultry farms as well as opportunities and concerns around antibiotic resistance throughout the world.
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