The article explores the integration of the Digital Twin concept with Federated Learning techniques for monitoring critical infrastructure. This approach allows for local data processing and knowledge transfer between different infrastructures, minimizing the amount of data sent to the cloud. Benefits include enhanced data security, operational efficiency, and more proactive maintenance. Through practical examples, it demonstrates how these technologies can revolutionize the management of critical infrastructure.

De Carlo, N., Romano, C., Granero, G., D'Amico, F., Cappelli, E., Fabbri, G. (2024). Digital Twin and Federated Learning: Enhancing and Securing Critical Infrastructure. GEOMEDIA, 28(3), 6-11.

Digital Twin and Federated Learning: Enhancing and Securing Critical Infrastructure

D'Amico, F;
2024-01-01

Abstract

The article explores the integration of the Digital Twin concept with Federated Learning techniques for monitoring critical infrastructure. This approach allows for local data processing and knowledge transfer between different infrastructures, minimizing the amount of data sent to the cloud. Benefits include enhanced data security, operational efficiency, and more proactive maintenance. Through practical examples, it demonstrates how these technologies can revolutionize the management of critical infrastructure.
2024
De Carlo, N., Romano, C., Granero, G., D'Amico, F., Cappelli, E., Fabbri, G. (2024). Digital Twin and Federated Learning: Enhancing and Securing Critical Infrastructure. GEOMEDIA, 28(3), 6-11.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11590/497137
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