An Innovative Big Data Framework for Supporting Multidimensional Risk Analysis and Prediction over Digital Twins

Focusing on the innovative context that predicates the integration between digital twin technologies and big data paradigms, including management and analytics, this paper proposes models, principles and implementations of a framework for supporting multidimensional risk analysis and prediction over digital twins. We complement our research contributions by means of a comprehensive experimental campaign over real-life datasets that focus on the emerging digital twin healthcare setting.

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Publication Details

Published
2024-12-15
DOI
https://doi.org/10.1109/bigdata62323.2024.10825260
Citations
1
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
0.53
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article

An Innovative Big Data Framework for Supporting Multidimensional Risk Analysis and Prediction over Digital Twins

Alfredo Cuzzocrea, Ismail Benlaredj
1 citations
Big Data and Business Intelligence
0.53
article

An Innovative Big Data Framework for Supporting Multidimensional Risk Analysis and Prediction over Digital Twins

Alfredo Cuzzocrea, Ismail Benlaredj
article en
1 citations

Abstract

Focusing on the innovative context that predicates the integration between digital twin technologies and big data paradigms, including management and analytics, this paper proposes models, principles and implementations of a framework for supporting multidimensional risk analysis and prediction over digital twins. We complement our research contributions by means of a comprehensive experimental campaign over real-life datasets that focus on the emerging digital twin healthcare setting.

University of Calabria (IT)
Openalex Percentile: Top 22%
Big Data and Business Intelligence
0.53
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