Work

Digital Twins and Big Data in the Metaverse: Addressing Privacy, Scalability, and Interoperability with AI and Blockchain

Year: 2025

Type: article

Abstract: This paper explores the integration of digital twin technologies and big data in the metaverse to improve urban traffic management. It highlights the importance of technology in mirroring and augmenting our physical and virtual worlds. This study examines how big data and digital twin technologies merge in the metaverse to improve traffic management. Our work applies artificial intelligence (AI) and blockchain technologies to address concerns about privacy, scalability, and interoperability. In a literature review and case study on traffic management, we outline how big data analytics and digital twins can increase operational and decision-making efficiency. This study aims to elucidate the transformative potential of such technologies for urban transport and postulates future areas of social, regulatory, and environmental research gaps.

Source: ISPRS International Journal of Geo-Information

DOI: 10.3390/ijgi14080318

Authors: Ruoxuan Li, Hemn Barzan Abdalla, Mehdi Gheisari, Hamidreza Rabiei-Dastjerdi

Institutions: Wenzhou-Kean University, Kean University, Shaoxing University, Dublin City University

Language: English

Topic: Smart Cities and Technologies

Subfield: Media Technology

Field: Engineering

Domain: Physical Sciences

SDGs: Industry, innovation and infrastructure, Sustainable cities and communities

Open Access status: gold

Estimated APC paid: $2,292