Zhang, X. orcid.org/0000-0002-1882-736X, Min, G., Li, T. et al. (3 more authors) (Cover date: August 2023) AI and Blockchain Empowered Metaverse for Web 3.0: Vision, Architecture, and Future Directions. IEEE Communications Magazine, 61 (8). pp. 60-66. ISSN 0163-6804
Abstract
As one of the most prominent parts of the Internet, World Wide Web (WWW) has achieved great success and penetrated every area of our lives. However, the cu rrent WWW still suffers from inefficiency, growing concerns about user privacy and data ownership, and poor Quality of Experience. Therefore, we propose a promising architecture for the next-generation WWW, Web 3.0, which is underpinned by Artificial Intelligence (Al) and Blockchain-empowered Metaverse (AlB-Metaverse). Fueled by native Al, Web 3.0 based on AlB-Metaverse can provide users with a personalized experience and enable smart decision-making with high efficiency. Backed by Blockchain, the AIB-Metaverse-based Web 3.0 is decentralized, which can help users regain full control of data and protect the ownership of generated data while preserving privacy. Furthermore, this new architecture can provide a ubiquitous immersive experience to users during real-time interaction with digital avatars in the Metaverse. To verify the effectiveness of Al in Web 3.0, we propose an Al-based approach for Metaverse video delivery, which can significantly enhance the quality of immersive experience perceived by users in Web 3.0. In addition, we pinpoint the challenges faced by the proposed AlB-Metaverse-based Web 3.0 and highlight pertinent research directions in the future.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > SWJTU Joint School (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 30 Aug 2023 09:31 |
Last Modified: | 30 Aug 2023 09:33 |
Status: | Published |
Publisher: | Institute of Electrical and Electronics Engineers (IEEE) |
Identification Number: | 10.1109/mcom.004.2200473 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:202746 |