IoT + AR: pervasive and augmented environments for “Digi-log” shopping experience View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2019-12

AUTHORS

Dongsik Jo, Gerard Jounghyun Kim

ABSTRACT

The current bare Internet of Things (IoT) infrastructure has recently been extended to include smarter and more effective user interactions. Individual or meaningful sets and groups of IoT objects can be imbued with data and/or content in a distributed manner and efficiently utilized by the client. This distribution makes it possible to scale and customize interaction techniques such as augmented reality (AR). This paper proposes an architecture for combining the AR interface with IoT for an improved shopping experience. The proposed architecture is distributed and therefore scalable such that any IoT product can be accessed on the spot locally without any server restriction and provide intuitive AR-based visualization and interaction for a flexible product trial in the showroom. We identify three key architectural components required to support such a seamless and scalable AR service and experience for IoT-ready products: (1) object-centric data management and visualization, (2) mechanism for accessing, controlling, and interacting with the object, and (3) content exchange interoperability. We illustrate the possible scenarios of shopping in the future with the interactive and smart digital information combined with the analog, that is, the real world. A proof-of-concept implementation is presented as applied to such a “digital–analog” style of shopping. In addition, its usability is experimentally assessed as compared to using the conventional control interface. Our experimental study shows that the subjects clearly experience higher usability and greater satisfaction with AR-interactive shopping, thereby demonstrating the potential of the proposed approach. More... »

PAGES

1

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URI

http://scigraph.springernature.com/pub.10.1186/s13673-018-0162-5

DOI

http://dx.doi.org/10.1186/s13673-018-0162-5

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1111064129


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