## 4 Results
### MI System Architectures
#### 4.2.3 Markerless (Without Identifier) AR  
Variations in the patterns that are displayed in Figure 4 can be achieved by omitting the AR marker, which is a type of identifier. Our analysis of previous MI system architectures suggests that markerless (i.e., without an identifier) tracking approaches have been used instead of AR markers to identify an IoT device or another entity. In this subsection, we discuss one variation of each pattern that is displayed in Figure 4.  
The MI system that was proposed by [PERSON] et al. [33] is a variation of Figure 4a that uses another AR target tracking technique instead of AR markers. [PERSON] et al. [33] developed an AR mobile application for workers in a factory to monitor the temperature of machines. IoT devices are attached to each machine to stream the temperature data in real-time. The AR mobile application uses object recognition instead of AR markers to identify the IoT devices. Furthermore, in this MI system, all of the IoT devices have the same appearance; thus, LED colors on IoT devices are used to distinguish devices by the AR mobile application.  
As a variation of the architecture presented in Figure 4b, [PERSON] et al. [41] developed a system for a work space that can recognize an electric cabinet placed on a specific location on a table. When the electric cabinet is located within the camera view, the system presents the assembly instructions for the electric cabinet. The assembly instructions are displayed on a Microsoft HoloLens device using 3D models that are drawn over the electric cabinet. Cameras with a depth sensor installed in the work space are used to identify the position of the agent's hands, and the built-in HoloLens camera is used to detect the position of virtual content (e.g., virtual buttons, virtual interfaces) to allow agents to interact with the system while using their hands. Agents can follow the assembly instructions in the real-world and they can navigate the instructions and other information by manipulating the virtual content with their hands. In the work space that was described by [PERSON] et al. [41], RGB-D cameras are used in combination with the HoloLens camera to increase the accuracy of hand gesture detection. There are two projectors that visualize information regarding the assembly instructions and temperature of the work space on the table.  
The MI system that was proposed by [PERSON] et al. [34] utilizes both an AR marker and object recognition. In their system, an application on the agent's mobile device uses anAR marker to recognize an environment to initiate indoor navigation (Figure 4b), and uses object recognition to identify a machine (variation of Figure 4c). Such an MI system can be classified as both Figure 4b and Figure 4c, due to its ability to monitor and control the recognized machine by object recognition.  
[PERSON] et al. [42] developed an MI system that is a variation of Figure 4d architecture. Their system employs object recognition to recognize miniature building structures (i.e., another entity) for visualizing an AR building structure on them. When an AR building structure is displayed on a mobile device, information on energy consumption that is sent by IoT devices installed within the building and rooms is presented. Based on this information, the agent can control the light power in a building or room by touching the menu in the AR interface. The commands that were issued by the agent through the AR interface affect lights that are installed not only in the AR building structure, but also in the real-world miniature building structures.