Datasets: Programmable content and a pattern-matching algorithm for automatic adaptive authoring in Augmented Reality for maintenance
datasetposted on 01.06.2020 by Iñigo Fernández del amo blanco, John ahmet Erkoyuncu, Maryam Farsi
Datasets usually provide raw data for analysis. This raw data often comes in spreadsheet form, but can be any collection of data, on which analysis can be performed.
This repository includes datasets on experimental cases of study and analysis regarding the research called "Programmable content and a pattern-matching algorithm for automatic adaptive authoring in Augmented Reality for maintenance".
Abstract: "Augmented Reality (AR) can increase efficiency and safety of maintenance operations, but costs of augmented content creation (authoring) are hindering its industrial deployment. A relevant research gap involves the ability of authoring solutions to automatically generate content for multiple operations. Hence, this paper offers programmable content formats and a pattern-matching algorithm for automatic adaptive authoring of ontology -based maintenance data. The proposed solution is validated against common authoring tools for repair and remote diagnosis AR applications in terms of operational efficiency gains achieved with the content they produce. Experimental results show that content from all authoring solutions attain same time reductions (42%) in comparison with non-AR information delivery tools. Surveys results suggest alike perceived usability of all authoring solutions and better content adaptiveness and user’s performance tracking of this authoring proposal."