## 1 Introduction  
Augmented Reality (AR) technology is an information-delivery paradigm that bridges physical and digital objects intuitively and seamlessly. Such synchronization occurs in real time through a user's engagement with the camera of a mobile device. Key factors that expand its usability are the access to digital content regardless location, the rapid evolution of sensors and the high visual coherence of virtual and real scene. Mobile Augmented Reality (MAR) is a promising support medium for motivating students in learning, recreating in-person event experiences, staff training in healthcare and retail products personalization. Respectively, the Cultural Heritage (CH) sector is undergoing a similar digital transformation. Recent applications for touristic sites [1, 2], museum exhibitions and art galleries [3, 4] demonstrate the profound impact of MAR on how data are delivered, perceived and recontextualized. \"Changdeok Airrang at Home\" is an Android AR application for remotely experiencing a complete navigation at an UNESCO World Heritage site, exploiting 5G mobile edge computing (MEC) for fast and seamless interaction with high-quality AR and Virtual Reality (VR) content [5]. Combined with adaptive data transmissions MEC technology, reduces the end-to-end latency while multiple users share AR and Mixed Reality (MR) content through the ShareAR application [6]. Such multiuser collaboration interfaces may be the response for open museums that seek a balance between interactivity and distance through AR technology [7]. In case of outdoor MAR, the fast transfer of real-world information and the location awareness complement each other. InvercARgill is a MAR urban tour guide that retrieves on the fly location-based information and navigates the user to cultural attractions and heritage activities [8]. Both applications leverage commercial AR Software Development Kits (SDKs) for pose estimation, tracking and rendering, i.e., ARCore [9] and Wikitude [10], respectively. Typically, the overlaid multimedia information comprises text, animation, 3D graphics as well as CAD, wireframe and low-poly models. However, the current advances in photogrammetry, range sensors and fast surface modelling enrich the CH datasets with high-resolution, geometrically accurate and realistic 3D reconstructions. Their large size and complex structure dictate their integration into MAR applications, where visual fidelity is encountered as a crucial factor. The obvious trade-off between visual quality and overall responsiveness is an issue that needs to be tackled even by the commercial AR SDKs. Regarding the technical requirements of the aforementioned MAR approaches and the trends in media, high-end smartphones and tablets have turned into a necessity. They incorporate depth APIs for depth maps using RGB cameras, 3D Time of Flight (ToF) depth sensors, scanner-less LiDARs, multiple GPU texture resolutions as well as the support required for 5G networks. Moreover, the AR SDKs are running on device models that fulfil certain minimum hardware requirements, such as quad-core CPUs and the existence of Inertial Sensor Units (IMU) sensors. The quality of the camera, the version of the operating system and the architecture also determine the compatibility. While the performance is increasing in terms of motion sensors and computational power, there is still a certain number of users who continue to rely on mobile devices going back almost a decade or long-abandoned versions of operating system. Since they are intended for basic usage, they lack a high-resolution camera sensor, a 3G network as well as the adequate CPU power and storage for intensive applications. Furthermore, their IMU sensors are susceptible to drift over time and their battery drains out in case of sending and receiving geo-coordinates [11]. They do not qualify support for dedicated SDKs and present outdated features and compatibility issues with well-established applications like Google Maps.