# Enhancing the Performance of XR Environments Using Fog and Cloud Computing
## 3 Proposed System Architecture  
To provide a detailed explanation of the XR content slated for use as a testbed to validate the efficiency of the proposed cloud platform, the following description is provided. The experimental content facilitates a virtual environment wherein multiple users engage in collaborative interactions within a cubic space through an online platform. This virtual scenario takes the form of an interactive storybook. Upon touching the virtual walls, users trigger immediate interactions. The touch interactions are detected through LiDAR sensors embedded in the walls. To promptly respond to user actions, laser projectors are employed to project visuals onto the four walls and the floor, while speakers simultaneously reproduce corresponding audio feedback. Consequently, users experience real-time responses to their interactions in the virtual world. This content allows users to witness real-time reactions to their interactions in the virtual environment, where touching the walls or interacting with elements previously manipulated by other users leads to dynamic responses. The system is designed to offer users a multi-sensory experience, providing visual and auditory feedback in real-time. In a cloud-based XR environment, generating and transmitting large-scale 3D graphics and sensor data are essential. However, this can lead to network bandwidth issues and the need to prevent overload due to data streaming. In recognizing these challenges, we propose an alternative approach that leverages edge and fog computing, which proves to be more efficient in designing and implementing XR environments. Edge and fog computing is more efficient in designing and implementing XR environments by considering these constraints rather than relying solely on cloud-based systems, such as the real-time transport protocol (RTP) [25]. This approach minimizes data transmission to the cloud, especially for equipment with a significant volume of data, such as light detection and ranging (LiDAR) sensors and projectors installed in the real world. These devices can seamlessly receive data in the local environment through edge computers. Typically, in XR environments, content engages users through a process such as Figure 1. Users perform actions as required by the content in a designated space, and these actions need to be detected through sensing equipment provided in the XR environment (in our proposal, LiDAR sensors). Such equipment, like LiDAR sensors, typically transmits data such as point clouds. Based on this data, user actions are detected. These detected actions are then reflected in the XR content through character actions, enabling the content to provide feedback to users through screens and sound. The distinct characteristics of XR environments are that, when executed on local computers, there are fewer constraints on data communication and data processing. However, there are limitations, such as higher costs and difficulties in facilitating interactions among multiple users. Consequently, our proposal aims to address real-time processing challenges that arise when building XR environments in a cloud setting. We achieve this by optimizing the volume of data and leveraging dedicated servers. The input data for our system primarily consists of 3D point cloud data detected using a LiDAR sensor. These data are transmitted in real-time, with a scanning frequency of 20-30 times per second to determine whether the user's body is in contact with the wall. For touch interactions on the wall, multiple users may utilize various parts of their bodies, necessitating the detection of multiple touches from different positions. To achieve this, we deploy multiple sensors, as shown in Figure 2, to detect these touches with precision. However, it is worth noting that, while this sensor arrangement enables precise touch interactions, it can also result in data transmission delays due to the larger volume of data. These delays may ultimately hinder user interaction and cause delays in the XR environment's output.