在农业食品中嵌入人工智能支持的数据基础设施,以实现可持续性:软果和酒厂的使用案例观点
Milan Markovic1,2, Andy Li2, Tewodros Alemu Ayall2
1Interdisciplinary Institute, University of Aberdeen, Aberdeen AB24 3FX, UK.
Sensors (Basel, Switzerland)
|November 27, 2024
概括
人工智能 (AI) 通过优化资源使用和减少碳足迹,为净零农业食品系统提供了潜力. 然而,要使人工智能有效,必须解决数据质量和用户采用等挑战.
科学领域:
- 农业科学 农业科学
- 环境科学 环境科学
- 计算机科学 计算机科学
背景情况:
- 农业食品行业需要进行重大转型以实现净零转型,需要在生产,交付,技术和数据基础设施方面进行创新.
- 实现净零排放需要对食品系统进行根本性的改变,包括先进的技术和数据驱动的方法.
研究的目的:
- 探索部署基于人工智能的数据基础设施在农业食品行业的可持续发展的机遇和挑战.
- 调查物联网 (IoT) 传感器和人工智能对资源效率,碳足迹减少以及软果生产和酒厂运营中的决策的好处.
主要方法:
- 案例研究重点关注软果生产和酒厂运营.
- 对AI和物联网传感器集成进行分析,以改善可持续性.
- 识别技术采用和数据质量问题的障碍.
主要成果:
- 人工智能和物联网传感器显示出改善资源利用,减少碳足迹和加强决策的潜力.
- 关键的挑战包括用户参与,环境波动影响数据质量,模型通用性和社会技术障碍.
- 用户参与,细粒度数据的可用性和透明的碳计算至关重要.
结论:
- 人工智能是一个有价值的工具,而不是一颗银弹,用于实现农业食品行业的净零目标.
- 人工智能解决方案必须适当设计并与其他方法协同部署.
- 未来的方向包括语义数据集成,合成数据生成和多目标优化系统.
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