Application of Correction Methods for Measured Data from a Model Object's Microclimate Monitoring System

This paper describes the correction methods for humidity sensors included in the microclimate monitoring system based on the model object located in Murmansk, Russia. The first part of the paper provides the sensor placement scheme for wall and log parts of the model object. Zonal correction method (with splitting and sorting data by humidity groups) and regression correction (linear regression based) method are described. Advantages and potential caveats of aforementioned methods are provided. The second part of the paper describes the correction experiment carried on data being collected from the model object during 2022. Correlation coefficients describing the connection between indicative humidity sensors and reference sensors were calculated from the data. Further calculations through correction methods were made; each corrected sensor was evaluated via mean squared error (MSE) score. The final part of the paper provides the conclusive evaluation of performance of each correction method with considerations of various correlation coefficients and external influences.