IDEAS home Printed from https://ideas.repec.org/p/hal/wpaper/hal-05593407.html

From Digital Twins to Adaptive Metaverse Infrastructures: A Distributed Systems Framework for Smart Buildings and Factories

Author

Listed:
  • Nicola Magaletti

    (LUM - Università LUM Giuseppe Degennaro = University Giuseppe Degennaro)

  • Ettore Zini

  • Mauro Di Molfetta

  • Maria Giovanna Trotta
  • Valeria Notarnicola

    (LUM - Università LUM Giuseppe Degennaro = University Giuseppe Degennaro)

  • Angelo Leogrande

    (LUM - Università LUM Giuseppe Degennaro = University Giuseppe Degennaro)

Abstract

The article introduces the concept of Smart Infrastructure Metaverse (SIM) and considers it from the perspective of Distributed Adaptive Systems (DAS). The approach combines technologies such as IoT, Digital Twins, AI, and XR to form an infrastructure intended to provide continuous real-time monitoring of objects, along with their prediction. The key idea behind SIM is that the infrastructure is viewed as an entity that changes continuously through data synchronization. The REMM (Real Estate Metaverse Manager) tool is provided as one way to apply the principle of distributed intelligence alongside edge and cloud computing to manage infrastructure. The experimental results demonstrate improvements in energy optimization, predictive maintenance, and situational awareness.

Suggested Citation

  • Nicola Magaletti & Ettore Zini & Mauro Di Molfetta & Maria Giovanna Trotta & Valeria Notarnicola & Angelo Leogrande, 2026. "From Digital Twins to Adaptive Metaverse Infrastructures: A Distributed Systems Framework for Smart Buildings and Factories," Working Papers hal-05593407, HAL.
  • Handle: RePEc:hal:wpaper:hal-05593407
    Note: View the original document on HAL open archive server: https://hal.science/hal-05593407v1
    as

    Download full text from publisher

    File URL: https://hal.science/hal-05593407v1/document
    Download Restriction: no
    ---><---

    Other versions of this item:

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hal:wpaper:hal-05593407. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: CCSD (email available below). General contact details of provider: https://hal.archives-ouvertes.fr/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.