A Temperature Monitoring Method for Wireless Sensor Networks Based on Improved Kriging Algorithm

Abstract

The invention discloses a temperature monitoring method for a wireless sensor network based on an improved Kriging algorithm. Firstly, a layer-cluster wireless sensor network topology structure is established, and historical temperature data of a target area are analyzed, and a threshold ρ and a fusion period T are set. Then at the cluster head node, based on the threshold value ρ, the data of the nodes in the cluster are periodically fused to obtain the initial temperature data, which is transmitted to the local database stored in the monitoring host through the wireless link; the initial data is exported, and the variation structure analysis is performed on it. Generate the variation function expression; use the improved Nelder-Mead simplex method to optimize the variation function model, design the regular grid terrain, use the ordinary Kriging algorithm for temperature interpolation, perform error correction, and output the regular grid temperature field map. The invention optimizes the variation function model by using the improved Nelder-Mead simplex optimization method, corrects the weight of the ordinary kriging algorithm, and compensates the error of the interpolation result, so that the interpolation result is more scientific and closer to the actual situation.

Description

technical field [0001] The present invention relates to a temperature monitoring method based on wireless sensor network (Wireless Sensor Networks, WSNs) technology, in particular to a temperature monitoring method of wireless sensor network based on improved kriging algorithm. Background technique [0002] Temperature data is very important information in daily life, industrial and agricultural production, and scientific research, especially in environments such as grain depots, greenhouses, and forests, where temperature monitoring and control is more important. Wireless sensor network is one of the commonly used monitoring technologies. It overcomes the shortcomings of traditional monitoring methods such as single method, poor timeliness and flexibility. However, due to the limitation of the deployment density of sensor nodes, the accuracy of the temperature field map generated by the monitoring system based on limited sampling point data is poor, which cannot meet some ...

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to overcome the defects that the accuracy of the temperature field generated by the monitoring of the existing wireless sensor network is not high enough, and the network survival time is relatively short

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