University of Oulu

J. Cao, X. Liu, X. Su, S. Tarkoma and P. Hui, "Context-Aware Augmented Reality with 5G Edge," 2021 IEEE Global Communications Conference (GLOBECOM), Madrid, Spain, 2021, pp. 1-6, doi: 10.1109/GLOBECOM46510.2021.9685498

Context-aware augmented reality with 5G edge

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Author: Cao, Jacky1; Liu, Xiaoli2; Su, Xiang3,1;
Organizations: 1University of Oulu, Oulu, Finland
2University of Helsinki, Helsinki, Finland
3Norwegian University of Science and Technology, Gjøvik, Norway
4The Hong Kong University of Science and Technology, Hong Kong
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 3.6 MB)
Persistent link:
Language: English
Published: IEEE, 2022
Publish Date: 2023-03-28


Augmented Reality (AR) provides immersive user experiences by overlaying digital information on physical environments. Context-awareness is crucial for delivering relevant augmentations that best suit users’ requirements and their en-vironments. In this article, we combine context-aware reasoning with emerging AR applications to provide the most relevant information according to user and environment contexts. To support the best possible quality of experience, 5G edge computing enables the distribution of computation-intensive AR tasks to edge servers through 5G networks. We develop ConAR, a context-aware head-mounted display AR system that is deployed on the edge and cloud leveraging both environmental sensors and user profile context for navigation. ConAR is composed of a HoloLens application and a paired mobile client, which contains a context model for air quality forecasting, and rendering recommendations on holograms through a HoloLens 2 device. We evaluate our system performance by deploying our proposed air quality prediction algorithm on the edge and cloud while communicating to them using 5G and LTE connections. We measure network quality metrics and find the deployment on the edge with 5G connections significantly outperforms alternative solutions. Our results demonstrate that the 5G edge computing is suitable for supporting latency-sensitive analysis tasks for context-aware AR.

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ISBN: 978-1-7281-8104-2
ISBN Print: 978-1-7281-8105-9
Pages: 1 - 6
Host publication: 2021 IEEE Global Communications Conference (GLOBECOM)
Conference: IEEE Global Communications Conference
Type of Publication: A4 Article in conference proceedings
Field of Science: 113 Computer and information sciences
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