Digital Knowledge Base for Industrial Augmented Reality Systems Based on Semantic Technologies

Augmented Reality is a technology that offers enormous potential in the industry. Due to a lack of expertise, however, companies are facing various challenges in exploiting this potential. This includes the demand-oriented configuration of the AR system. Depending on the planned use case and company-specific influencing factors and general conditions, suitable AR devices are to be identified and functionalities need to be purposefully selected. The necessary knowledge is implicitly available in numerous sources and difficult to access for companies. In the scope of this work, therefore, a machine-readable knowledge base is developed, in which the knowledge relevant for the AR system configuration is consolidated and formalized. Four aspects of knowledge are considered: The AR system structure including technical and functional components; Potential influences through ambient factors; Experience and application knowledge; The specification of specific AR devices. The knowledge base is realized based on the Web Ontology Language (OWL) and thus enables a digital and partially automated processing of the knowledge using software tools and algorithms. In combination with Artificial Intelligence solutions, the developed knowledge base can be transferred to other systems in the future and provide a powerful tool for system configuration.