Foundational and Methodological Areas

• Real-time data integration and synchronization in Digital Twins

• AI-enhanced modeling, prediction, and control in DT environments

• High-fidelity simulation techniques for Digital Twins

• Edge, fog, and cloud-based architectures for scalable DT implementations

• Security, privacy, and trust management in Digital Twin ecosystems

• Standardization and interoperability frameworks for Digital Twins

• Digital Twin lifecycle management and sustainability considerations

• Networking and communication challenges in distributed DT systems

Healthcare and Biomedical Engineering

• • Patient-specific Digital Twins for diagnosis, treatment, and monitoring

  • Digital Twins for biomedical devices and systems

Construction and Civil Engineering

• • 1. Digital Twins of buildings, bridges, and infrastructure assets

    2. Structural health monitoring and disaster response planning

Smart Cities and Urban Infrastructure

• • Urban mobility and traffic management

  • Energy systems, water management, and utilities optimization

Telecommunications and Network Management

• • Network Digital Twins for 5G/6G optimization and failure prediction

  • Virtual testing environments for network services

Environmental Monitoring and Sustainability

• • Climate modeling and ecosystem management

  • Wildland and urban fire management

  • Digital Twins for renewable energy systems

Aerospace, Defense, and Autonomous Systems

• • Real-time monitoring of autonomous drones and vehicles

  • Mission planning and risk assessment

Technical Program Committee

The Venue