基于嵌入式和窄带物联网的农业种植智能测控系统

Agricultural Planting Intelligent Measurement and Control System Based on Embedded and Narrowband Internet of Things

针对市场上农产品质量良莠不齐的问题,设计了一种基于嵌入式和窄带物联网的农业种植智能测控系统,系统采用窄带物联网技术,结合嵌入式微控制技术和GRNN神经网络技术,能够实时对农作物种植过程中的环境参数进行测量和控制。MatLab仿真试验表明:GRNN神经网络对冬麦土壤种植适宜性等级的预测准确性为93.33%,与实测值非常接近,且耗时很短,能够实现预警作用,有助于农民提前进行施肥、浇水和调整土壤pH值。

In view of the uneven quality of agricultural products in the market,it designs an intelligent measurement and control system for agricultural planting based on embedded and narrow-band Internet of things.The system adopts narrow-band Internet of things technology,combined with embedded micro control technology and GRNN neural network technology,which can measure and control the environmental parameters in the process of crop planting in real time.Matlab simulation results show that GRNN neural network for winter wheat soil planting suitability grade prediction accuracy is 93.33%,very close to the measured value,and time consuming is very short,achieve early warning function,help farmers to fertilize,water and adjust soil pH value in advance.