The Digital Twins and Cyber-Physical Systems (CPS) Division focuses on developing and applying virtual models that enhance the control, optimization, and resilience of physical systems. By integrating sensor data, machine learning, and real-time analytics, the division creates digital twins that allow for continuous monitoring and predictive maintenance in complex environments, such as manufacturing and urban infrastructure.

• Digital Twin Technology: Creating virtual representations of physical systems that simulate real-world processes and inform decision-making.
• Sensor and IoT Integration: Using IoT devices to acquire real-time data that enhances the capabilities of digital twins.
• Advanced Control and Optimization: Developing algorithms to improve the control and adaptability of cyber-physical systems, enhancing efficiency and resilience.
• Cybersecurity in CPS: Ensuring data integrity and protection against cyber threats in digital twin and CPS implementations.

• High-Fidelity Modeling and Simulation: Building virtual models that accurately replicate the behavior of complex systems, supporting optimized operations.
• Real-Time Data Acquisition and Monitoring: Implementing sensor networks and IoT solutions to gather real-time data for system management.
• Machine Learning for CPS: Enhancing CPS adaptability and predictive capabilities with machine learning techniques.
• Cybersecurity for Digital Twins: Developing methods to protect digital twins and CPS from cyber threats, ensuring data security and system reliability.
• Manufacturing and Process Optimization: Applying digital twins to improve product quality, reduce downtime, and streamline manufacturing processes.