An Urban Intelligence Architecture for Heterogeneous Data and Application Integration, Deployment and Orchestration

Area of Science:

• Computer Science
• Urban Planning
• Information Technology

Background:

• Complex urban intelligence systems require integrated digital twin subsystems.
• Existing IT platforms often struggle with heterogeneous data and subsystem interoperability.

Purpose of the Study:

• To propose a novel IT architecture for smart city digital twin systems.
• To facilitate cloud deployment, data management, and workflow execution for urban intelligence.

Main Methods:

• Development of a novel IT architecture template.
• Implementation of a prototype using open-source frameworks.
• Testing in real-world settings to evaluate functionalities and performance.

Main Results:

• The architecture efficiently supports deployment and integration of heterogeneous subsystems.
• It enables seamless data sharing, integration, and visualization.
• The system facilitates integration with external systems and workflow orchestration.

Conclusions:

• The proposed IT architecture provides a scalable and efficient template for smart city digital twin implementation.
• It addresses key challenges in data management, integration, and process automation for urban intelligence.