基于PSO-BP数据融合的环境监控系统设计

传统的温室大棚监控系统一般都采用手动布线,存在控制难度大、成本高等问题,已不能满足农业发展的需求。针对上述问题,该文设计了一款基于PSO-BP的无线温室大棚环境监控系统。在大棚内部署Zig Bee传感器节点网络采集环境信息,利用ECDS算法选择路由节点。同时为了能够直观地展示大棚内各环境信息的分布情况,使用Kriging方法构建环境信息分布图。构造了反馈调节系统:由于大棚的各因数之间是相互作用的,为了有一个准确的决策结果,该系统将BP神经网络和PSO算法结合。利用改进后算法良好的映射能力和优化能力,对温室数据进行融合,精确决策。实验结果表明,该系统能够合理分配路由节点节省网络开销,较好地展示环境信息分布情况,同时能够精确地调节大棚环境。

Design of Environmental Monitoring System Based on PSO-BP Data Fusion

Traditional greenhouse greenhouse monitoring systems generally use manual wiring,which has problems such as difficult control and high cost,which cannot meet the needs of agricultural development. In response to the above problems,a PSO-BP-based wireless greenhouse greenhouse monitoring system was designed. The Zig Bee sensor node network is deployed in the greenhouse to collect environmental information,and the ECDS algorithm is used to select the routing node. At the same time,in order to visually display the distribution of various environmental information in the greenhouse,the Kriging method is used to construct the environmental information distribution map. And the feedback adjustment system is constructed:Because the factors of the greenhouse interact,in order to have an accurate decision result,the system combines BP neural network and PSO algorithm. Utilize the improved mapping ability and optimization ability of the improved algorithm to integrate the greenhouse data and make accurate decisions. The experimental results show that the system can reasonably allocate routing nodes to save network overhead,better display the distribution of environmental information,and accurately adjust the greenhouse environment.