Survey of indoor tracking systems using augmented reality

Abstract

<p><span lang="EN-US">Augmented reality overlays virtual content on the physical world, displaying location-based information more efficiently. Tracking is a trace detail of the location recorded, either by taking a reading based on a set time interval, set distance, and change in direction by more than a certain angle, or a combination of these. Tracking is divided into two types, outdoor tracking, and indoor tracking. Augmented reality added value and information to tracking applications, whether indoor or outdoor. Recently, outdoor tracking by the global positioning system (GPS) became an essential component in navigation applications. However, indoor tracking is still challenging in the augmented reality field. Most augmented reality indoor tracking use optical and sensor-based tracking, such as markers, beacons, Raspberry Pi, and route planner modules for the building. With the technology enhancement, indoor tracking started to rely on WiFi, Bluetooth, geographic information system, radiofrequency identification, and sensor chip technologies. Our paper describes the recent augmented reality tracking techniques from 2011 to 2021. The paper compares image detection algorithms with various communication technologies, disscusing the advantages and the limitations of each technology.</span></p>

Indoor AR Navigation Framework Based on Geofencing and Image-Tracking with Accumulated Error Correction

“…Komianos [26] also indicated that AR is easy to employ in museums compared to Virtual Reality (VR) and Mixed Reality (MR) because it is mostly based on the Bring Your Own Device (BYOD) concept as it reduces costs and is easier for users to handle their own device. The survey by Shewail et al [27] revealed that, for the purpose of indoor tracking, communication technology-based tracking can be faulty for applications that need accurate tracking and registration, while image-based tracking can be more accurate and reliable. However, they also pointed out the scalability problems of image-tracking-based solutions.…”