Use Cases for Augmented Reality Applications in Enterprise Modeling: A Morphological Analysis

Abstract

The evaluation of modeling languages for augmented reality applications poses particular challenges due to the three-dimensional environment they target. The previously introduced Augmented Reality Workflow Modeling Language (ARWFML) enables the model-based creation of augmented reality scenarios without programming knowledge. Building upon the first design cycle of the language's specification, this paper presents two further design iterations for refining the language based on multi-faceted evaluations. These include a comparative evaluation of implementation options and workflow capabilities, the introduction of a 3D notation, and the development of a new 3D modeling environment. On this basis, a comprehensibility study of the language was conducted. Thereby, we show how modeling languages for augmented reality can be evolved towards a maturity level suitable for empirical evaluations.

Augmented Reality Frameworks for Object Recognition in Learning Application Domain: A Systematic Review

“…In addition, [32] used a CAD model to enhance the techniques in AR development and perceptions of the environment to recognize an object whose 3D pose is detected and tracked in real-time (online training), but has an issue with visible conics in the image. The work of [13], which focused on AR technology for object recognition and used context-dependent AR of machine learning, ontologies, and reasoning, found that the framework benefits genericity and flexibility in the object pattern but has limitations due to simulating object recognition by using marker patterns that provide information about the recognized objects. The research by [33] also focused on AR technology and showed the benefits of designing a cache and matching system but had limitations on cache size in the component framework.…”

“…Calvary et al, reported that the factors influencing object recognition in AR were the tracking techniques [12], detection level, the accuracy, the camera resolution, the size and the compatibility of devices to which the users need to carry out the interactive task and the physical environment [11]. In addition, Muff and Fill [13] reported that AR applications for object recognition need to determine the current situation according to action for information display with the devices which have to dispose of different sensors for detecting the environment. This is means using various sensors to assess the current state of the environment and thus derive the artificially generated information for the user through visual means.…”

Informing Possible Future Worlds

“…Figure 11.7 shows a mockup of an application following this direction (Muff and Fill 2022b). It features an AR-based application for the collaborative modeling of a Business Model Canvas (BMC) (Osterwalder et al 2010).…”

“…Despite some first elaborations on possible use cases for augmented reality and conceptual modeling -cf. Muff and Fill (2022b) -it will have to be further investigated which scenarios would be most beneficial for the combination of these technologies. Further, also the conceptual foundations for integrating AR in modeling and metamodeling frameworks will have to be further researched.…”

“…These developments led to a revival of research for investigating how augmented reality may be combined with conceptual modeling, e. g., Muff and Fill (2021a), Muff and Fill (2021b), Muff and Fill (2022b), Grambow et al (2021), Seiger et al (2021), Grum and Gronau (2018) and Havard et al (2015). Although several applications of using augmented reality together with conceptual models have been demonstrated, a fundamental discussion of how conceptual modeling and augmented reality are related seems to be missing so far.…”