News Release

Empowering digital twins with eXtended reality collaborations

Peer-Reviewed Publication

Beijing Zhongke Journal Publising Co. Ltd.

HCLINT-DT framework adapted to the Elettrotecnica Imolese use case: physical components of electrical switchboards are recognized giving the chance to read or write annotation that are mirrored in its DT in the virtual space, that also provides the same possibilities.

image: Firstly, the AR interface would run on an AR device like the Hololens, so the assemblers could keep going with their work without moving from the electrical board to the personal computer. Secondly, object recognition would prevent wasting time searching for the instruction/annotations regarding a particular component by immediately visualizing all the info in the shared document. The adaptation of the HCLINT-DT framework for this use case is visually reported in the Figure. In addition, thanks to the adoption of the HCLINT-DT framework, the workers’ Empowerment is provided with the use of state of the art tools and XR devices (e.g., HoloLens 2 and Htc-Vive), as confirmed by the assemblers, engineers, and testers which were interviewed during our analysis. The Communication improvement is given by the natural working mechanism of HCLINT-DT shared annotations. Finally, Training is a natural consequence of the same HCLINT-DT shared annotation mechanism since workers could analyze previously annotated documents to learn from others’ experiences. view more 

Credit: Beijing Zhongke Journal Publising Co. Ltd.

We introduced the HCLINT-DT framework to support the spread of human collaborative intelligence by leveraging DT and XR paradigms. To validate such an approach, we assessed a use case involving family photo albums through an online survey. The results show a general agreement on the ease of use of the AR interface and the overall experience, even if there was only a partial agreement in preferring AR. We also explored the adaptability of the proposed approach considering a use case drawn from a local industrial electrical engineering context. Here, the HCLINT-DT showed a good adaptability level. Further investigations could involve: (a) improving annotations retrieval, (b) analyzing how this annotation system could support machines (learning), and, (c) understanding more deeply the impact of such systems on human activities. Finally, instances of this framework could be created for additional areas and domains, other than the considered ones (e.g., education, marketing).

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