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Open Access

UbiMeta: A Ubiquitous Operating System Model for Metaverse

Yiqiang Chen1,2( ), Wuliang Huang1,2,3, Xinlong Jiang1,2, Teng Zhang1,2, Yi Wang1,2, Bingjie Yan1,2, Zhirui Wang1,2, Qian Chen1,2, Yunbing Xing1,2,3, Dong Li1,2, Guodong Long4
Beijing Key Laboratory of Mobile Computing and Pervasive Device, Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China
University of Chinese Academy of Sciences, Beijing 100190, China
AIER Eye Hospital Group Co., Ltd., Changsha 410015, China
Faculty of Engineering and IT, University of Technology Sydney, Sydney 2007, Australia
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Abstract

The metaverse signifies the amalgamation of virtual and tangible realms through human-computer interaction. The seamless integration of human, cyber, and environments within ubiquitous computing plays a pivotal role in fully harnessing the metaverse’s capabilities. Nevertheless, metaverse operating systems face substantial hurdles in terms of accessing ubiquitous resources, processing information while safeguarding privacy and security, and furnishing artificial intelligence capabilities to downstream applications. To tackle these challenges, this paper introduces the UbiMeta model, a specialized ubiquitous operating system designed specifically for the metaverse. It extends the capabilities of traditional ubiquitous operating systems and focuses on adapting downstream models and operational capacity to effectively function within the metaverse. UbiMeta comprises four layers: the Ubiquitous Resource Management Layer (URML), the Autonomous Information Mastery Layer (AIML), the General Intelligence Mechanism Layer (GIML), and the Metaverse Ecological Model Layer (MEML). The URML facilitates the seamless incorporation and management of various external devices and resources. It provides a framework for integrating and controlling these resources, including virtualization, abstraction, and reuse. The AIML is responsible for perceiving information and safeguarding privacy and security during storage and processing. The GIML leverages large-scale pre-trained deep-learning feature extractors to obtain effective features for processing information. The MEML focuses on constructing metaverse applications using the principles of Model-as-a-Service (MaaS) and the OODA loop (Observation, Orientation, Decision, Action). It leverages the vast amount of information collected by the URML and AIML layers to build a robust metaverse ecosystem. Furthermore, this study explores how UbiMeta enhances user experiences and fosters innovation in various metaverse domains. It highlights the potential of UbiMeta in revolutionizing medical healthcare, industrial practices, education, and agriculture within the metaverse.

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International Journal of Crowd Science
Pages 180-189

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Cite this article:
Chen Y, Huang W, Jiang X, et al. UbiMeta: A Ubiquitous Operating System Model for Metaverse. International Journal of Crowd Science, 2023, 7(4): 180-189. https://doi.org/10.26599/IJCS.2023.9100028

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Received: 09 July 2023
Revised: 08 November 2023
Accepted: 09 November 2023
Published: 22 December 2023
© The author(s) 2024.

The articles published in this open access journal are distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).