推进精准畜牧业:整合人工智能和新兴技术,实现可持续畜牧管理
Luis Orlindo Tedeschi1, Pablo Guarnido Lopez1, Hector M Menendez Iii2
1Texas A&M University, College Station, United States.
Animal bioscience
|August 14, 2025
概括
精密畜牧业 (PLF) 使用人工智能和先进的传感器来改善动物福利和农场效率. 未来的发展旨在整合大型语言模型并解决数据隐私问题,以便更广泛地采用.
科学领域:
- 农业科学 农业科学
- 计算机科学 计算机科学
- 工程 工程师 工程师 工程师
背景情况:
- 精密畜牧业 (PLF) 已经从基本的监测发展到人工智能驱动的系统.
- 这些系统提高了牲畜管理,可持续性和动物福利.
研究的目的:
- 审查自2017年以来PLF的技术演变.
- 突出传感,计算机视觉和人工智能的进步.
主要方法:
- 审查最近在PLF的技术进步.
- 分析非侵入式传感技术 (RGB-D摄像头,3D成像,物联网).
- 检查AI在疾病检测,养和繁殖中的应用.
主要成果:
- 复杂的非侵入性技术捕获实时生物识别和行为数据.
- 人工智能算法有助于早期发现疾病,并优化管理策略.
- 混合智能框架将技术与精密营养的机械模型集成在一起.
结论:
- 未来的PLF将整合大型语言模型和数据隐私的联合学习.
- 挑战包括数据标准化,农村连接,成本和道德.
- 跨学科的合作是可持续和高效的畜牧生产的关键.
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