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Model-driven engineering city spaces via bidirectional model transformations.

Ennio Visconti1, Christos Tsigkanos1, Zhenjiang Hu2

  • 1Technische Universität Wien, Vienna, Austria.

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Summary
This summary is machine-generated.

This study introduces a method to enrich CityGML data with semantic information for urban cyber-physical systems. Bidirectional transformations ensure synchronized digital twins of cities for robust analysis.

Keywords:
Bidirectional model transformationsCityGMLDigital twinsModel-driven engineering

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Area of Science:

  • Computer Science
  • Urban Informatics
  • Software Engineering

Background:

  • Cyber-physical systems in urban environments require robust software engineering support.
  • Current CityGML models lack semantic richness for advanced analysis.
  • Bridging the gap between geometric city models and analyzable data is crucial.

Purpose of the Study:

  • To develop a technique for deriving analyzable models from CityGML descriptions.
  • To ensure consistent bidirectional synchronization between domain and analyzable models.
  • To facilitate model-based development for urban digital twins.

Main Methods:

  • Leveraging the theory of bidirectional transformations.
  • Developing a formal programming technique and technical framework.
  • Applying the method to real-world city models.

Main Results:

  • Successfully derived analyzable models from CityGML data.
  • Achieved automatic and coherent synchronization between domain and analyzable models.
  • Demonstrated the practical feasibility of bidirectional transformations for urban data.

Conclusions:

  • Bidirectional transformations provide a consistent and well-behaved approach for synchronizing urban models.
  • The developed technique enables richer semantic analysis of urban cyber-physical systems.
  • This work supports the creation and maintenance of accurate, synchronized digital twins of cities.