@inproceedings{670abf8fc90d4e1a9d5cc89ff5f3f964,
title = "A Edge-computing Framework with AR Applications for Telehealth",
abstract = "Telehealth has the potential to bring high-quality medical care to patients outside hospitals, and Augmented Reality (AR) applications can further promote real-time healthcare delivery and immersive experience while imposing stringent requirements on network infrastructure. This study presents an end-to-end AR-based application empowered by nextG infrastructure. It leverages Multi-Access Edge Computing (MEC) and tackles communication requirements based on use scenarios for connected health. Unlike the majority of large-scale, commercially available platforms that support AR devices relying on upper protocols of networks such as IPv4 or IPv6, this study uses protocols in the lower layer stacks to provide a light-weighted solution in device and data management. We further consider the AR application requirements and satisfaction to achieve system-level sustainability and scalability.",
keywords = "5G, AR, Augmented Reality, Causal Inference, Telehealth, edge computing, nextG",
author = "Ying Wang and Ting Liao",
note = "Publisher Copyright: {\textcopyright} 2022 ACM.; 7th IEEE/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies, CHASE 2022 ; Conference date: 17-11-2022 Through 19-11-2022",
year = "2022",
doi = "10.1145/3551455.3566161",
language = "English",
series = "Proceedings - 2022 IEEE/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies, CHASE 2022",
pages = "193--197",
booktitle = "Proceedings - 2022 IEEE/ACM International Conference on Connected Health",
}