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为探讨智能化在农业中的应用，研究基于5G、ZigBee与多维环境动态自适应优化(Multidimensional Environmental Dynamic Adaptive Optimization, MEDAO)算法的智能温室管理系统。通过构建多节点环境监测网络，利用ZigBee技术实时采集温度、湿度、光照、氧气、二氧化碳浓度、土壤微量元素等关键环境数据，并通过5G网络上传至云端分析，利用MEDAO算法进行精确预测，实现对作物生长状况的识别与控制。结果表明，系统在优化资源利用和提高生产效益方面表现出显著优势，能够生成个性化种植方案，满足作物需求，并具备自学习能力，提升环境管理水平。
Abstract：To explore the application of intelligence in agriculture, an intelligent greenhouse management system based on 5G, ZigBee, and the Multidimensional Environmental Dynamic Adaptive Optimization(MEDAO) algorithm is studied. By constructing a multi-node environmental monitoring network, the system uses ZigBee technology to collect key environmental data such as temperature, humidity, light, oxygen, carbon dioxide concentration and soil trace elements in real time, and the data is uploaded to the cloud for analysis through the 5G network. The MEDAO algorithm is employed for precise predictions, enabling the identification and control of crop growth. The results show that the system can offer significant benefits in optimizing resource utilization and improving production efficiency. It can generate personalized planting plans, meet crop requirements and possesses self-learning capabilities, which improves the level of environmental management.
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基本信息:
DOI：10.20149/j.cnki.issn1008-1739.2025.05.001
中图分类号:S625;TP315
引用信息:
[1]郭泽飞,邬杰,赵佳伟,等.5G+MEDAO赋能的智能温室管理系统设计[J].计算机与网络,2025,51(05):419-428.DOI:10.20149/j.cnki.issn1008-1739.2025.05.001.
基金信息:
西藏大学研究生高水平人才培养计划项目(2025-GSP-S143)