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多传感器监控,智能控制和数据处理,用于智能温室环境管理.

Emmanuel Bicamumakuba1, Md Nasim Reza1,2, Hongbin Jin2

  • 1Department of Agricultural Machinery Engineering, Graduate School, Chungnam National University, Daejeon 34134, Republic of Korea.

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概括
此摘要是机器生成的。

智能温室使用多传感器网络,智能控制和数据过用于精密农业. 本综述综合了用于高效,可扩展和弹性的智能温室系统的技术.

关键词:
卡尔曼过器可以过.环境监测 环境监测 环境监测预测控制 预测控制 预测控制智能温室是一个智能温室.无线传感器网络是一个无线传感器网络.

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科学领域:

  • 精准农业和可持续食品生产.
  • 在受控环境农业中集成先进技术.
  • 系统审查智能温室管理系统.

背景情况:

  • 传统的温室依赖于手动监控,限制了效率和资源优化.
  • 智能温室集成了传感器,物联网 (IoT) 和人工智能 (AI) 来实现自动化的环境控制.
  • 需要系统地审查能够实现智能温室管理的核心技术.

研究的目的:

  • 系统地研究智能温室管理的多传感器监控,智能控制和数据过技术.
  • 为了比较各种传感器技术,控制策略和数据过方法.
  • 综合对智能温室系统的技术性能和实施可行性的研究结果.

主要方法:

  • 在主要数据库中对114项同行评审研究进行了结构化的文献选.
  • 传感器技术的比较分析 (温度,湿度,二氧化碳,光,能量).
  • 控制策略的评估 (物联网自动化,模糊逻辑,模型预测控制,强化学习) 和过方法 (时间/频率域,卡尔曼,基于AI,混合).

主要成果:

  • 多传感器集成提高了精度和弹性,但面临着校准和互操作性挑战.
  • 智能控制提高了能源和水效率,但需要强大的数据和计算能力.
  • 先进的数据过确保了完整性,但引发了可扩展性和成本问题.

结论:

  • 将技术性能与实施可行性联系起来,对于开发智能温室至关重要.
  • 为了创建负担得起,可扩展和有弹性的智能温室系统,存在途径.
  • 进一步的研究应该涉及校准,互操作性,数据要求和计算成本,以便广泛采用.