Research on Reconstruction Method of Random Missing Sensor Data Based on Fuzzy Logic Theory

Wireless sensor nodes are often deployed in the wild environment, and the data collected are often lost. It is very important to reconstruct the missing data for accurate scientific calculation or other applications. In this study, a random missing data reconstruction method based on fuzzy logic theory is presented. The method mainly studies how to combine the Euclidean distance between the sensor nodes and the correlation of the sensory data to construct a new method of determining neighbor nodes, while the weight calculation method of each neighbor node participating in reconstruction is studied, which is to solve the deficiencies of the neighbor node selection when there are obstacles between sensor nodes only rely on the Euclidean distance. The experimental results show that the accuracy of the proposed method is relatively high when the sensor data has a mutation or the acquisition time interval is large.