基于DNN的WSN智慧大棚可视化与控制系统研究

传统的温室大棚监测与控制系统一般采用布线方式,存在难度大、成本高等问题,已不能满足农业发展的需求。针对上述问题,研发一种基于DNN的WSN智慧大棚可视化与控制系统。在大棚内部署LoRa传感器网络采集环境信息。为直观地表达大棚内环境因子分布情况,采用Kriging方法构建环境因子分布图,并利用DNN神经网络建立专家知识库,能够自主科学地决策。通过反馈控制系统调节大棚内环境,使农作物具有最佳的生长环境。实验结果表明,该系统能够较好地展现环境因子分布情况且能够科学地调节大棚环境。

VISUALIZATION AND CONTROL SYSTEM OF WSN INTELLIGENT GREENHOUSE BASED ON DNN

The traditional greenhouse monitoring and control system generally adopts wiring method,which is difficult and costly,and cannot meet the needs of agricultural development.Aiming at the above problems,we developed a WSN intelligent greenhouse visualization and control system based on DNN.LoRa sensor network was deployed in the greenhouse to collect environmental information.In order to intuitively express the distribution of environmental factors in the greenhouse,the Kriging method was used to construct the distribution map of environmental factors.We adopted DNN neural network to establish the expert knowledge base,which could make decisions independently and scientifically.The environment in the greenhouse could be adjusted by feedback control system,so that crops had the best growth environment.The experimental results show that the intelligent greenhouse system can show the distribution of environmental factors better and adjust the environment scientifically.