## 4 Discussion and Conclusions  
In this work, we introduced and evaluated a cloud framework to host a server application that enables users to connect from multiple locations and collaborate in an immersive XR environment. The importance of this platform is that it is the first step to proving that by utilizing an efficient cloud platform, we can overcome current processing limitations to expand the utilization of XR. This platform also provides an elevated user experience by eliminating the need to be physically present or in close proximity to the application server, which will result in enhanced quality of medical training. We also demonstrated that using the Holo-Cloud architecture is easy to implement, efficiently uses hardware resources, and is cloud platform-independent. To evaluate the performance of the cloud platforms, it is crucial to measure CPU, memory, and network utilization. The experimental results show that the resource utilization of the FI3D application process hosted on the Holo-Cloud virtual machine container is minimal; therefore, the Holo-Cloud model has the potential to be utilized in various fields, such as surgery and surgical and radiology training. Figure 15: (**a**) The user rotates, tilts, and zooms the brain model using the Microsoft HoloLens 2 HMD hand gestures. (**b**) The projection of the brain model in the user’s HoloLens see-through display. (**c**) Projection of the brain model using another user’s Android HHD. (**d**) The user interacts with a molecular ribbon 3D model using Microsoft HoloLens 2 HMD hand gestures. (**e**) The projection of the molecular ribbon model in HoloLens 2 FOV. (**f**) Another user interacts with the molecular ribbon model using an Android device. There are some limitations associated with this framework. First, because this platform can be implemented on any cloud service provider, it may be challenging for the end user to decide between different providers. Secondly, in multiuser interaction scenarios with the immersive scene, every user registered with the system can modify the orientation and visual characteristics of the projected models, and the server will update the visual characteristics of the scene for all other users. Confusion may occur if more than one user interacts with the object simultaneously. To avoid this conflict, we plan to develop locking mechanisms. Apart from these limitations, some inherent limitations may impact user experience. Because the Holo-Cloud is multiplatform and accessible via a wide range of HMDs and HHDs, the visual experience of users regarding the projected model (delays in frame updates due to device hardware limitations, spatial resolution, luminance, contrast, and color profile of the models) may not be the same when using different hardware. Another limitation is the network quality of the end users. End users need to ensure that they have uninterrupted internet connectivity to have an optimal experience interacting with the platform. Because the objective of this study is to evaluate the Holo-Cloud framework, the FI3D software's original deployment and parameters were not changed or reconfigured, and this software was used as is. However, multiple FI3D software parameters, such as parallel processing, can be optimized for utilization on the cloud. Also, in the future, we plan to integrate medical imaging and medical IoT devices into the Holo-Cloud framework to enable users to interact and control devices via XR through the cloud. Moreover, we plan to integrate artificial intelligence models into the Holo-Cloud platform to leverage the high-performance and on-demand resources of the cloud for real-time diagnosis and data enhancement, such as on-the-fly medical image segmentation using various methods [34]. An economic analysis of using Holo-Cloud is also planned. Conceptualization, H.N., J.D.V.-G. and N.V.T. ; methodology, H.N., J.D.V.-G. and N.V.T. ; software, H.N. and J.D.V.-G.; validation, H.N. and J.D.V.-G.; formal analysis, H.N. ; investigation, H.N. and J.D.V.-G.; resources, N.V.T. ; data curation, H.N.