基于NB-IoT技术的智能农业环境监测系统设计

Design of intelligent agricultural environment monitoring system based on NB-IoT technology

在农业生产管理中,利用农业物联网可以高效地获取农作物的生长环境信息,但是农田中终端节点之间分布距离较远,同时受限于接入容量,设备功耗等,从而给农作物环境监测带来一定的困扰。针对智慧农业存在的问题,利用NB-IoT技术组建无线传感网络对农作物生长环境进行实时采集和监测,同时研究基于多传感器数据融合方法,利用自适应加权平均融合以及神经网络方法对各区域内的传感器数据进行融合,从而得到农作物环境状况的综合判断。该方法可以针对不同农作物及其生存环境需求,有效提升农作物生存状态预测精度,本方法相比传统方法预测误差降低45%以上,验证本方法的有效性和优越性。

In agricultural production management,the agricultural Internet of Things can be used to efficiently obtain the growth environment information of crops.However,the distribution distance between terminal nodes in farmland is relatively long.It is limited by the access capacity and equipment power consumption,which brings difficulties to crop environment monitoring.To address the problems exiting in smart agriculture,this paper uses NB-IoT technology to build a wireless sensor network to collect and monitor the crop growth environment in real-time.Furthermore,a method based on multi-sensor data fusion that uses adaptive weighted average fusion and neural network methods to fuse the sensor data is studied.This approach yields a comprehensive assessment of the crop environment.This method can effectively improve the prediction accuracy of crop status.Compared with the traditional method,the prediction error is reduced by more than 45%,which verifies the effectiveness and superiority of this method.