The Design And Implementation Of Collection And Transmission System For Crop Growth Information Based On NB-IoT

Agriculture is an important basic industry which supporting national economic construction,and the level of agricultural modernization is a symbol of a country's comprehensive strength.Since the 21 st century,the combination of information technologies,such as cloud computing,the Internet of Things and intelligent perception,with agriculture has created a new model of agricultural development,named smart agriculture.At present,the level of agricultural modernization in China still has a large gap,compared with developed countries.Smart agriculture is an important way to promote agricultural modernization.This paper designs and implements a sparse collection and transmission system of crop growth environment information based on the cellular narrowband IoT technology,sparse sampling technology and matrix filling algorithm.Based on modern sensor technology,collect information about the growth environment of crops such as temperature,humidity,pH,and conductivity in the farmland environment.Each group of sensor acquisition nodes rely on the STM32 L series of low-power microcontrollers as the main control,and collect data according to a certain rule,so that the microcontroller is in low-power mode for most of the time.This paper innovatively proposes a sparse data collection method.Sparse sampling is performed by generating a random sparse matrix,which reduces the amount of data collected and the working time of the system,and greatly saves power consumption and bandwidth.This paper realizes long-distance,high-reliability transmission of information about the growth environment of crops such as temperature,humidity,pH,and conductivity based on the wide area Internet of Things technology,NB communication module M5310 A,and relies on telecommunications operators' NB network and LWM2 M IoT protocol.Relying on the IoT open cloud platform OneNET,this paper realizes the management of the system's access devices and the visualization of the data flow,and then the data is pushed from OneNET to the Alibaba Cloud server to save and restore.This paper also studies the recovery and reconstruction of the sensor's uncollected data by the matrix filling algorithm,and analyzes the impact of the sampling rate and the number of iterations on the recovery accuracy,and verifies the effectiveness and feasibility of the sparse sampling method.Finally,in actual field debugging operation,the system runs stably and reliably,and realizes sparse collection and transmission of crop growth information.