Our PhD student Mahnoor Yaqoob has got a paper accepted at the ICC’23 workshop, as part of the work from the EPSRC project “Digital Twin for OpenRAN” through the UK-India Future Networks Initiative (UKI-FNI). The paper focuses on the DT approach for end-to-end network slicing solution which address both RAN and Core parts to improve automation and efficiency of the Beyond 5G network.
Panel Discussion at AMRC Workshop “Engineering Digital Twins in Practice”
On 2nd February 2023, Professor Huan Nguyen was invited to join a panel discussion at the Workshop “Engineering Digital Twins in Practice” hosted at Factory 2050 in AMRC Sheffield. The panel, chaired by Professor David Wagg (University of Sheffield), included other panelists John Patsavellas (Cranfield University), Jan Wolber (GE Healthcare), and Ali Nicholl (IOTICS). The benefits, challenges and specific use cases on Digital Twin technology were discussed and shared with 100+ in-person and online audiences. Prof. Nguyen presented some examples of the DT work at LDTRC for applications on smart factory and 6G mobile networks. The event also featured several other talks on DT and was ended with a tour of fantastic facilities at AMRC’s Factory 2050.Continue reading “Panel Discussion at AMRC Workshop “Engineering Digital Twins in Practice””
Publication News: Smart manufacturing with Industrial IoTs and machine learning
As part of the work from Project “Digital twin for Industry 4”, the project team have developed deep learning techniques and advanced/timely solutions of Industrial IoTs, communication (e.g., Reconfigurable Intelligent Surface) to address the automation and smart processes in manufacturing and factory settings. The outcomes were accepted for publications in two journal papers on the highly reputed IEEE Journal of Internets of Things.
Paper 1: RIS-aided Smart Manufacturing: Information Transmission and Machine Health Monitoring
Paper 2: Unsupervised Deep Learning-based Reconfigurable Intelligent Surface Aided Broadcasting Communications in Industrial IoTs
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Structural Health Monitoring
Structural health monitoring and digital twin modelling are the timely research areas in structures that attract interests worldwide. The Newton Fund project teams from the London Digital Twin Research Centre and the University of Transport and Communications (Vietnam) continue to extend the impact beyond the project by organising the 2nd International Conference on Structural Health Monitoring and Engineering Structures (SHM&ES 2021) during 13th-14th December 2021.
Formula 1 is Leading the Digital Twin Technology
By Huan Nguyen, William Davis, and Ciaran Sinclair
Formula 1 (F1) is a billion-pound sport that blends between entertainment (a show) and competition. It is arguably the most advanced, high-tech sport in the world. Each F1 team’s factory consists of 1000+ employees who works day and night to just produce two cars that only two drivers can drive them. It costs millions of pounds to produce a racing F1 car and the costs of development and operations throughout the year add up to further hundreds of millions. As many as 3000+ car parts are produced each week by each team. Teams invest heavily to just happily outpace other teams’ cars by a tenth of a second a lap when racing in a circuit of over 5km.
The two key things for a winning team: i) produce a very good racing car; and ii) be slick and efficient in operation as a team. Both of these can be decisively supported by one key technology: Digital Twin, because of its largely data-driven environment and the decision making is often made in real-time manner (in pressurised racing conditions).
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