## 3 Ubiquitous Tourist System Based on MCDM and AR
### UTS-mAR Methodology
#### 3.2.2 AR Visualization Model  
The AR visualization model uses context and AR technology to display the properties of information for visualization, and involves three models: text-size setting, LOD setting, and visualization. These models employ various statistical techniques, such as rule definition, distance calculation, and the use of fuzzy functions. These statistical techniques result in the determination of the features of the displayed information, such as its text size and LOD, and these features are subsequently used in AR visualization. As shown in Figure 4, the AR visualization model contains several stages, as follows: First, the context that represents the user and environmental data is prepared. Next, a text-size-setting model is used to adjust the text size of the information based on the rules defined in the user context of the system. Subsequently, the LOD-setting model is used, which sets the LOD for the information based on distance, fuzzy function, or user preference. Because this model requires an estimation of the distance between the user and the visited object using the haversine formula, the corresponding distance is estimated. Finally, a visualization model is employed. At this stage, the LOD and text size, which are defined in the previous stage, are used for augmenting information on the visited object via AR technology. As discussed, our real-time system links the modules of the LOD-setting model and visualization with AR technology. * **Preparing context** As shown in Algorithm A2 (Appendix A), context preparation is the first step in creating the AR visualization model. The user context comprises a variety of information, including user position, general user information--such as age--and user health information (including vision problems). The positional information of the user is obtained  
Figure 4: AR visualization model. using the fused tracking function in the system. Other user information, such as age and health status (e.g., presence of vision problems), is entered by the user through the system interface. Moreover, the environmental context includes two categories of information: the time of day during system execution, and visited-object information, such as images, location, and textual information. In this regard, time of day information is entered via the system interface, and the visited-object information for Sejong University as the test area is stored. Table 2 provides a description of the context. In the Table 2, some explanation detail related table items are shown with \"\". Context data are used by the system for defining information properties, which is achieved using the following three components of the AR visualization model: the text-size-setting model, which adjusts the text size of the information; the LOD-setting model, which adjusts the level of information detail; and the visualization model, which uses AR technology. * **Text-size-setting model** The text-size-setting model considers two general modes for adjusting the text size. The first is an automatic setting, which determines the text size based on the information provided by the system. The second is a manual setting, which determines the size based on the settings entered by the user. The automatic setting applies predefined rules to the system employing context information, such as age, status of vision problems, and time of day. This setting renders text in a small size for young users without vision problems, in a medium size for middle-aged users without vision problems, and in a large size for older users, users with vision problems, or when system execution occurs during nighttime. * **LOD-setting model** The LOD-setting model determines the LOD of the information. First, the distance between the user and the visited object is calculated using the haversine formula [41; 42] on the corresponding locations. The next step is the selection of the LOD-setting model by the user.