COMPARISON OF SELECTED AUGMENTED REALITY FRAMEWORKS FOR INTEGRATION IN GEOGRAPHIC CITIZEN SCIENCE PROJECTS

Abstract

Augmented reality (AR) offers functionalities that can be beneficial for citizen science (CS) projects. Especially location-based approaches have potential for geographically oriented CS projects, as objects can be placed based on geographic coordinates. Since choosing a suitable AR framework for integration into a CS project can be challenging, this paper gives an overview of the common AR frameworks and takes a closer look at three selected ones that are particularly suitable for CS projects (AR.js, AR Foundation, and ViroReact). Prototypes were implemented for the selected frameworks to investigate which framework is best suited for specific use cases. Marker-based tracking approaches, image recognition and location-based placement were considered. The results show that the framework AR.js is particularly suitable for marker-based tracking with very simple markers and therefore represents a good entry point for CS projects to integrate initial AR functionality into their project. AR Foundation and ViroReact, on the other hand, are faster and more reliable with the detection of more complex markers. The location-based approach can be implemented with all three frameworks, but the precision of the placement of the objects strongly depends on the accuracy of the sensors of the mobile device.