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Critical infrastructures such as nuclear reactors, electricity installations, gas resources, transportation systems, water supply systems or communications are fundamental to modern society and are essential to ensure life in cities. However, their increasing complexity and interconnectivity make them vulnerable to various threats, including cyberattacks, natural disasters, and operational failures. Ensuring their security, resilience, and continuous operation is crucial for economic stability, public safety, and the constant delivery of essential services.
The concept of a Digital Twin involves creating a dynamic, virtual replica of a physical system or asset, enabling real-time monitoring, simulation and predictive analysis. By mirroring the physical entity, DTs facilitate predictive maintenance, performance optimization, and improve the decision-making of users. They serve as a bridge between the physical and digital areas, allowing enhanced interaction and control over complex systems.
A structured approach to integrating DTs into infrastructure management focuses on resilience, defined as a system's ability to absorb disturbances, respond effectively, learn from past events and anticipate future threats. The key contributions of the Digital Twin to resilience include:
· Anticipation: DTs enable predictive analytics, allowing operators to foresee potential failures and take preventive measures.
· Absorption: Real-time monitoring and simulation help mitigate immediate impacts of disruptions.
· Recovery: DTs support efficient decision-making during crisis management, ensuring faster recovery from failures.
· Learning and Adaptation: Historical data analysis allows continuous improvement and adaptation to evolving threats.
· Security Enhancement: DTs provide real-time monitoring and anomaly detection, strengthening cybersecurity measures.
Digital Twins can also be combined with various technologies to enhance their capabilities which make them interoperable by achieving and using real-time data to support the interaction:
· Internet of Things: Sensors collect real-time data from physical assets, feeding into the DT for analysis and monitoring.
· Artificial Intelligence: AI algorithms process data within the DT to predict outcomes and optimize performance.
· Extended Reality: this technology provides immersive interactions with the DT, improving training and operational planning.
Digital Twin technology is a transformative tool to ensure critical infrastructure resilience, security and efficiency. By enabling real-time insights, predictive analytics and a better decision-making process, Digital Twins empower infrastructure managers to anticipate, absorb and recover from disruptions efficiently. Their ability to integrate with other advanced technologies makes them a great tool in modern infrastructure management. The adoption of Digital Twins across various sectors can lead to more robust and adaptable systems, ensuring the continuous delivery of essential services in an increasingly complex and uncertain environment.
In the Digital Twin project, we provide training to face these challenges and improve efficiency and resilience of the operations by training the workforce that will be working on the critical infrastructures.
About Digital Twin project
The Digital Twin on Smart Manufacturing project is a European collaborative initiative that brings together education providers, industry partners, and SMEs from several EU countries. Its goal is to develop innovative training programmes and learning resources that support the adoption of Digital Twin technologies in smart manufacturing, helping bridge the gap between education and industry needs and contributing to the advancement of Industry 4.0 in Europe.
Brucherseifer, E., Winter, H., Mentges, A., Mühlhäuser, M. & Hellmann, M. (2021). Digital Twin conceptual framework for improving critical infrastructure resilience. at - Automatisierungstechnik, 69(12), 1062-1080. https://doi.org/10.1515/auto-2021-0104
Lampropoulos, G., Larrucea, X., & Colomo-Palacios, R. (2024). Digital Twins in Critical Infrastructure. Information, 15(8), 454. https://doi.org/10.3390/info15080454
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Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the European Education and Culture Executive Agency (EACEA). Neither the European Union nor EACEA can be held responsible for them.