Energy-Saving Data Acquisition Model of Wireless Sensor Network Based on Nonlinear Algorithm

Abstract

Wireless sensor network significant data acquisition has a high cost, long completion time, and low accuracy. This paper adopts a sensor network data acquisition method based on a nonlinear algorithm to solve the above problems. In this paper, a distributed data acquisition method based on nonlinear regression is established by combining the time series relationship of data. First, this paper uses nonlinear regression analysis technology to establish the sensing data model and retain the characteristics of the sensing data. This makes the node pass only the parametric data of the regression model. This paper uses this method to replace the transmission of actual monitoring sensory data information. Experiments show that this method can effectively reduce data redundancy and network traffic under any conditions. The method has been verified in practical WSN applications.