Visualization System For WIFI Indoor Positioning Data

With the continuous indepth research of indoor positioning technology,information analysis of indoor individual behavior or crowd behavior has become a significant topic in spatial and temporal data mining.In particular,with the popularization of smartphones,indoor positioning technology represented by WiFi positioning has accumulated a large amount of user's spatio-temporal location data.Differing from the outdoor positioning data,these high-precision and fine-grained indoor positioning data,which also have the characteristics of high dimension and strong dispersion,are restricted to the complexity of indoor space.However,the visualization analysis method can recognize the explicit interaction between the positioning data and the indoor space as well as reveal the regular pattern of hidden knowledge in the positioning data.It is also helpful to explore the spatial/temporal behavior patterns of indoor individuals or groups.In this paper,the WiFi location data of customers in a large shopping mall are taken as the research object.Firstly,this study analyzes the characteristics of indoor spatial data and the positioning data,and extracts and stores the effective information.Then,according to the features of indoor spatial data,the indoor spatial 3D visualization model is constructed with reference to the IndoorGML indoor modeling standard.Thirdly,accroding to the characteristics of indoor positioning data,the visualization model and implementation method are constructed on the basis of the 3D visualization model from three aspects: spatio-temporal trajectory of passengers,spatio-temporal distribution and POI correlation.Finally,according to the analysis of crowd behaviors in the mall,the prototype of the indoor passenger flow analysis system of the mall is developed and implemented,and the validity of the study results have been verified.The main results of the study are as follows:(1)Constructing positioning data analysis and extraction process oriented towards indoor visual analysis of large shopping malls.Based on the analysis of indoor spatial data and positioning data characteristics of large shopping malls,it studies the data processing,which concludes the data preprocessing,the extraction of POI data and the extraction of the spatio-temporal trajectory data,the contents of extraction and the storage mode.Hence,a data processing model for indoor data visualization is built.(2)The 3D visualization model of indoor space is built according to the IndoorGML standard.On basis of IndoorGML indoor modeling standard,the conceptual model of indoor geographic elements is contructed from three aspects: the structure of geographic element,the structure of geographic network and geographic geometry.Based on these,the topological relationship among geographic elements are abstracted.The data of geographic elements are organized by the object-oriented method,and two kinds of methods of indoor three-dimensional spatial visualization are finally defined.(3)Construction and implementation of visualization representation model for indoor positioning data.Based on the indoor data extraction and 3D visualization model of indoor space,it visually studies the spatial and temporal trajectory of passenger flow,the spatial and temporal distribution of passenger flow group and the POI relationship.Combined with some visualization methods and techniques such as road network matching,animation simulation flow graph,force orientation figure and charts,visualization representation models are developed and built.