Human-Computer Interaction and Human-Building Interaction

Integrating ESG with Digital Twins and the Metaverse: A Data-Driven Framework for Smart Building Sustainability

Magaletti Nicola, Chiara Tognon, Mauro Di Molfetta, Angelo Zerega, Valeria Notarnicola, Ettore Zini, Angelo Leogrande

Published 2025

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📄 Paper
This article proposes a complex solution to improve sustainable intelligent building management based on the principles of Environmental, Social, and Governance (ESG) factors. The ESG KPI Framework–Metaverse-Enabled Operations incorporates the latest digital twin solutions, IoT sensor systems, and metaverse platforms to deliver real-time management and optimization of ESG factors. A hybrid solution strategy has been used in this framework, focusing on auto-acquisition of information and multiple validations at different levels through correlation analysis, Principal Component Analysis (PCA), Ordinary Least Squares (OLS) regression, and Machine Learning. The designed prototype links all the solutions together in a multi-level dashboard to represent key performance factors such as carbon footprint, energy consumption, renewable energy use, and occupant wellness. Experiments conducted validate the effectiveness of the proposed solution in improving prediction efficiency and user interaction experience during metaverse simulations.

Abstract

This article proposes a complex solution to improve sustainable intelligent building management based on the principles of Environmental, Social, and Governance (ESG) factors. The ESG KPI Framework–Metaverse-Enabled Operations incorporates the latest digital twin solutions, IoT sensor systems, and metaverse platforms to deliver real-time management and optimization of ESG factors. A hybrid solution strategy has been used in this framework, focusing on auto-acquisition of information and multiple validations at different levels through correlation analysis, Principal Component Analysis (PCA), Ordinary Least Squares (OLS) regression, and Machine Learning. The designed prototype links all the solutions together in a multi-level dashboard to represent key performance factors such as carbon footprint, energy consumption, renewable energy use, and occupant wellness. Experiments conducted validate the effectiveness of the proposed solution in improving prediction efficiency and user interaction experience during metaverse simulations.

Topics

AI for Energy Performance OptimizationAR/VR/XR visualizationCross-Modal Intelligence and Multimodal IntegrationHCI-HBIInteractive VisualizationOccupant Behavior Analysis and Spatial OptimizationSmart Building Systems and IoT IntegrationSustainable BuildingsXRAI for AECbuilding performance dashboard

Cite this paper

@Article{98925fe3,
AUTHOR = {Magaletti, Nicola and Tognon, Chiara and Di Molfetta, Mauro and Zerega, Angelo and Notarnicola, Valeria and Zini, Ettore and Leogrande, Angelo},
TITLE = {Integrating ESG with Digital Twins and the Metaverse: A Data-Driven Framework for Smart Building Sustainability},
JOURNAL = {Systems},
VOLUME = {13},
YEAR = {2025},
NUMBER = {12},
ARTICLE-NUMBER = {1083},
URL = {https://www.mdpi.com/2079-8954/13/12/1083},
ISSN = {2079-8954},
ABSTRACT = {This article proposes a complex solution to improve sustainable intelligent building management based on the principles of Environmental, Social, and Governance (ESG) factors. The ESG KPI Framework–Metaverse-Enabled Operations incorporates the latest digital twin solutions, IoT sensor systems, and metaverse platforms to deliver real-time management and optimization of ESG factors. A hybrid solution strategy has been used in this framework, focusing on auto-acquisition of information and multiple validations at different levels through correlation analysis, Principal Component Analysis (PCA), Ordinary Least Squares (OLS) regression, and Machine Learning. The designed prototype links all the solutions together in a multi-level dashboard to represent key performance factors such as carbon footprint, energy consumption, renewable energy use, and occupant wellness. Experiments conducted validate the effectiveness of the proposed solution in improving prediction efficiency and user interaction experience during metaverse simulations.},
DOI = {10.3390/systems13121083}
}