物联网中的自动化智能滴灌系统使用适应性残留混合网络用于精密农业
Ahmad Y A Bani Ahmad1, Jafar A Alzubi2, Chanthirasekaran K3
1Department of Accounting and Finance, Faculty of Business, Middle East University, Amman, 11831, Jordan.
Scientific reports
|January 30, 2026
概括
本研究介绍了一种基于物联网 (IoT) 的负担得起的滴灌系统,该系统使用自适应残留混合网络 (ARHN) 来优化精密灌的用水量. 该系统大大减少了水浪费和农民的努力,提高了作物生产率.
科学领域:
- 农业工程 农业工程
- 计算机科学 计算机科学
- 环境科学 环境科学
背景情况:
- 精确灌对于农业节水至关重要,尤其是在受气候变化影响的缺水地区.
- 传统的灌传感器对于小型农场来说往往成本过高,阻碍了采用高效的水资源管理实践.
- 越来越需要具有成本效益的技术驱动的解决方案来优化灌和确保粮食安全.
研究的目的:
- 开发和评估基于物联网 (IoT) 的负担得起的滴灌系统,用于精确的灌安排.
- 提高用水效率,减少农业实践中的资源浪费.
- 通过智能灌控制,尽量减少农民劳动力,提高作物生产率.
主要方法:
- 设计了一个基于物联网的滴灌系统,通过传感器收集实时数据.
- 一个自适应的残留混合网络 (ARHN),结合空间自编码器和堆叠的CapsNet,被开发用于灌控制.
- 在ARHN模型的参数被优化使用现代化随机变量为基础的Frilled Lizard优化 (MRV-FLO) 算法.
主要成果:
- 开发的ARHN模型在灌控制中实现了高精度 (99.24%) 和低RMSE (97.32%).
- 该系统表现出与现有方法相比显著的性能改进,大大优于LEA-ARHN,FDA-ARHN,AOA-ARHN和FLO-ARHN.
- 这种基于物联网的系统有效地减少了水的浪费,并减少了农民的努力.
结论:
- 拟议的基于物联网的精密灌系统为提高农业的水效率提供了具有成本效益的解决方案.
- 通过MRV-FLO优化ARHN模型,为实时灌调度提供了强大而准确的方法.
- 这项技术有可能显著提高作物生产率,并支持可持续的农业实践,特别是在水资源有限的环境中.
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