基于LPWAN物联网与专家系统的果园精准灌溉研究  

Research on the Orchard Precision Irrigation Based on LPWAN Internet of Things and Expert System

作　　者：海涛[1] 陆猛 周文杰 李娜娜 李伏生[2] HAI Tao;LU Meng;ZHOU Wen-jie;LI Na-na;LI Fu-sheng(College of Electrical Engineering,Guangxi University,Nanning 530004,Guangxi,China;Agricultural College,Guangxi University,Nanning 530004,Guangxi,China)

机构地区：[1]广西大学电气工程学院,南宁530004 [2]广西大学农学院,南宁530004

出　　处：《中国农村水利水电》2021年第9期128-133,共6页China Rural Water and Hydropower

基　　金：国家自然科学基金项目(51867003);广西科技计划基金项目(桂科AB16380193);科技创新平台(基地)与服务能力建设(AE30200067)。

摘　　要：针对传统通信技术传输距离短、抗干扰能力差以及传统灌溉不合理、水资源利用率低等问题,构建了基于LPWAN物联网与专家系统的果园精准灌溉系统。该系统通过节点采集果园空气、土壤温湿度等环境信息,通过LoRa和NB-IoT网络将数据包上传到云服务器,专家系统根据采集到的环境数据和决策数学模型,实现需水量预测与灌溉决策,并将决策结果反馈到灌溉控制模块。为提高预测精度,引入GA-BP需水量预测算法,以芒果园为实验对象,结果表明传输距离在1200 m内系统平均丢包率为0.45%,数据传输稳定可靠;GA-BP模型的均方根误差和平均绝对误差分别为0.0745和0.1091 mm/d,相较于BP模型GA-BP模型具有更高的预测精度。试验期间果园土壤相对湿度维持在80%-90%,满足芒果树生长所需条件。该系统能够实现果园环境的实时监测与精准灌溉,可为进一步提高灌溉对水果产量与质量效果提供借鉴。Targeted at the problems of short transmission distance and poor anti-interference ability of traditional communication technology,unreasonable and low water resource utilization of traditional irrigation,this paper constructs a precision irrigation system for orchards based on LPWAN Internet of Things and expert system.The system collects environmental information such as air temperature and humidity,soil temperature and humidity through the acquisition nodes,then uploads data packets to the cloud server through LoRa and NB-IoT networks.The expert system realizes water requirement prediction and irrigation decision-making and other functions based on the collected environ⁃mental data and the decision-making mathematical model,and feedback the decision-making results to the irrigation control module.In or⁃der to improve the prediction accuracy,the GA-BP water requirement prediction algorithm is introduced,and the mango orchard is used as the experimental object.The results show that the average packet loss rate of the system is 0.45%within 1200 m,revealing that the data transmission is stable and reliable.The root mean square error and mean absolute error are 0.0745 and 0.1091 mm/d,respectively,which have higher prediction accuracy than the BP model.During the experiment,the relative humidity of the orchard soil is between 80% and 90%,which meets the conditions required for the growth of mango trees.The system can realize real-time monitoring and precise irrigation of the orchard environment,and can provide a reference for further improving the effect of irrigation on fruit yield and quality.

关 键 词：物联网 专家系统 GA-BP 精准灌溉 

分 类 号：TV93[水利工程—水利水电工程] S126[农业科学—农业基础科学]