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School of Architecture, Building and Civil Engineering

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3 Jul 2024

Feasibility of Digital Twins from Multiple Data Sources for Improved Decision-Making

This project aims to establish the feasibility of integrating data from multiple sensory sources and modelling simulations into a digital twin of aircraft and physical infrastructure, enhanced by machine learning, in support of RAF operations and real-time decision-making. The disparate data will be amalgamated into a data repository, which will exchange data with the digital twin during operations.

Funded by The Royal Air Force

Principal investigators: Ashraf El-Hamalawi (Lead) and Peter Demian

Duration: 01/01/2024 – 30/06/2025

Athena Swan Bronze award

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School of Architecture, Building and Civil Engineering
海角社区 University
Leicestershire
LE11 3TU