A Data Cleaning Method and Its Application for Earthen Site Data Monitored by WSN.

This paper focuses on a data cleaning method to denoise and detect outliers of earthen site monitoring data with wireless sensor network (WSN). A data cleaning method, named DC_ESVS is proposed, which is based on the temporal and spatial characteristics of monitoring data with WSN. Using the cubic exponential smoothing algorithm and voting strategy, it can denoise and detect outliers of earthen site monitoring data based on the decision rule. We conduct various experiments on the dataset of the monitoring data of Xi'an Tang Hanguangmen city wall site with WSN to show detection accuracy of the presented method. Experimental results on anther dataset of the monitoring data of the Ming Great Wall in Shaanxi also show good performance of the proposed method.