摘要
农业无线传感器网络(WSNs)的终端节点存在着低功耗和低成本的要求,而现有的土壤湿度传感器难以满足这种要求。提出一种将土壤电阻传感器和土壤温度传感器的数据进行融合的方法,并利用多元线性回归和BP神经网络建立了土壤湿度的测定模型。该方法在实际的Zig Bee农业无线传感器网络中得到应用。实验结果表明:在同一种类型的土壤中,该方法测定土壤湿度的精度可达±2.5%RH,可用于实际农业大田的土壤湿度测定。
There are requirements of low power consumption and low cost for terminal nodes in agricultural wireless sensor networks （WSNs）, however, the existing soil moisture sensors are difficult to meet the requirements. A method to measure soil moisture by fusing datas of soil resistance sensor with soil temperature sensor is proposed, meanwhile, multiple linear regression and BP neural network are used to set up measurement model of soil moisture. The method is applied in agricultural WSNs based on Zig Bee. The results of experiments show that precision of the proposed method can reach ±2.5 % RH in the same type of soil, which means that the proposed method can be used for practical soil moisture measurement in agricultural field.
出处
《传感器与微系统》
CSCD
2015年第1期151-153,共3页
Transducer and Microsystem Technologies
基金
国家"863"计划资助项目(2011AA100701)
