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精密乳制品营养数字双胞胎的计算架构:技术审查和实施框架

Shreya Rao¹, Suresh Neethirajan²

¹Faculty of Computer Science, Dalhousie University, 6050 University Avenue, Halifax, NS B3H 4R2, Canada.

Sensors (Basel, Switzerland)

|August 28, 2025

概括

通过将实时数据与模拟相结合,启用传感器的数字双胞胎 (DTs) 提高了精确的乳制品营养. 这一审查概述了DT的部署,为可持续农业实现了显著的料效率增长和排放减少.

科学领域:

农业工程
动物科学
计算生物学

背景情况:

精确的乳制品营养正在随着传感器技术和数字双胞胎 (DT) 整合而发展.
现有的研究缺乏一个结构化的框架来比较乳牛的不同DT架构.

研究的目的:

系统地审查和分类用于奶牛的传感器支持的数字双胞胎架构.
确定最佳的DT设计,挑战和准确奶牛养殖的未来研究方向.

主要方法:

对122项乳牛DT研究 (2010-2025) 的系统文献审查.
开发一个新的五维DT分类框架.
对混合边缘云架构和AI/ML模型性能进行分析.

主要成果:

嵌入CNN-LSTM模型的混合边缘云DT在行为识别中达到>90%的准确性.
基于云计算的模拟可以优化料,减少排放,平衡营养.
原型显示料转换效率提高了15-20%,用水量减少了高达40%.

结论:

能够使用传感器的DT为奶牛养殖提供了巨大的农业和环境效益.
主要挑战包括数据融合,网络同步和人工智能建议验证.
未来的工作需要可解释的人工智能,联合学习和标准化验证,

关键词:

数字双胞胎农业中的边缘计算混合模型动物监测精密乳制品营养实时数据集成传感器融合智能农业可持续的畜牧系统

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