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Digital Twin Modeling of Smart Cities

  • Dessislava Petrova-AntonovaEmail author
  • Sylvia Ilieva
Conference paper
  • 307 Downloads
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1253)

Abstract

Smart cities utilize the Big Data and IoT to provide better life for citizens. Since, they are the most complicated human artifact, the adoption of such technologies become a complex task, requiring continuous data collection, aggregation and analysis. In order to transform city problems into concrete actions a systematic approach aimed at digital transition needs to be followed. There are huge efforts to build city information models for encoding city objects, their relations and supporting the decision-making. This requires a common knowledge base, supported by rich vocabularies and ontologies that are capable to handle the information diversity and overload.

In this paper a methodological framework and an upper-level ontology for building digital city models are presented. The process of digital city modelling follows the concept of digital twin by providing a data-driven decision making. The proposed upper-level ontology aims to overcome city modeling problems due to data silos and lack of semantic interoperability.

Keywords

Data-driven decision making Digital twin Methodological framework Smart city Upper-level city ontology 

Notes

Acknowledgments

This research work has been supported by GATE project, funded by the Horizon 2020 WIDESPREAD-2018-2020 TEAMING Phase 2 programme under grant agreement no. 857155 and Big4Smart project, funded by the Bulgarian National Science fund, under agreement no. DN12/9.

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Copyright information

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021

Authors and Affiliations

  1. 1.GATE InstituteSofia University, “St. Kl. Ohridski”SofiaBulgaria

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