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    Use cases for network applications to enable connected intelligence

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    Authors
    Qiu, Renxi
    Li, Dayou
    Liu, Enjie
    Lessi, Christina C.
    Agapiou, George
    Gavrielides, Andreas
    Affiliation
    University of Bedfordshire
    Hellenic Telecommunications Organization (OTE) S.A.
    WINGS ICT Solutions
    eBOS Technologies Ltd.
    Issue Date
    2023-06-02
    Subjects
    connected robotics
    connected intelligence
    Quality of Experience
    Quality of Service
    Subject Categories::H671 Robotics
    
    Metadata
    Show full item record
    Other Titles
    Artificial Intelligence Applications and Innovations. AIAI 2023 IFIP WG 12.5 International Workshops MHDW 2023, 5G-PINE 2023, ΑΙBMG 2023, and VAA-CP-EB 2023, León, Spain, June 14–17, 2023, Proceedings
    Abstract
    Robots are expected to be more intelligent in consuming digital infrastructures during the process of continual learning. The future of connected Robotics should be skillful in maximizing Quality of Experience (QoE) for its vertical users rather than solely reacting to Quality of Service (QoS). The paper provides a detailed use case specification and a network softwarization paradigm for realizing the 6G vision of connected intelligence. It serves as a guidance for developing future network applications to ground the idea of the connected intelligence.
    Citation
    Qiu R, Li D, Liu E, Lessi CC, Agapiou G, Gavrielides A (2023) 'Use cases for network applications to enable connected intelligence', Artificial Intelligence Applications and Innovations. AIAI 2023 IFIP WG 12.5 International Workshops - León, Springer.
    Publisher
    Springer
    Journal
    ARTIFICIAL INTELLIGENCE APPLICATIONS AND INNOVATIONS. AIAI 2023 IFIP WG 12.5 INTERNATIONAL WORKSHOPS
    URI
    http://hdl.handle.net/10547/626373
    DOI
    10.1007/978-3-031-34171-7_13
    Additional Links
    https://link.springer.com/chapter/10.1007/978-3-031-34171-7_13
    Type
    Conference papers, meetings and proceedings
    Language
    en
    ISSN
    1868-4238
    EISSN
    1868-422X
    ISBN
    9783031341731
    Sponsors
    The work in this paper is sponsored by the EU H2020 project “5G Enhance Robot Autonomy” under grant agreement number 101016681.
    ae974a485f413a2113503eed53cd6c53
    10.1007/978-3-031-34171-7_13
    Scopus Count
    Collections
    Computing

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