Content area
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.
Details
Artificial intelligence;
Interoperability;
Datasets;
Environmental research;
User experience;
Big Data;
Traffic;
Blockchain;
Data processing;
Data analysis;
Batch processing;
Privacy;
Keywords;
Virtual reality;
Technology;
Case studies;
Literature reviews;
Machine learning;
Data integrity;
Security management;
Traffic management;
Digital twins;
Data collection;
Systematic review;
Decision making;
Urban transportation
; Gheisari Mehdi 3
; Rabiei-Dastjerdi Hamidreza 4
1 Department of Computer Science, Wenzhou-Kean University, Wenzhou 325060, China; [email protected]
2 Department of Computer Science, Wenzhou-Kean University, Wenzhou 325060, China; [email protected], Department of Computer Science and Technology, Kean University, Union, NJ 07083, USA
3 Institute of Artificial Intelligence, Shaoxing University, Shaoxing 312000, China; [email protected]
4 School of History and Geography, Faculty of Humanities and Social Sciences, Dublin City University (DCU), D09 V209 Dublin, Ireland; [email protected]