Digital Twins (DT) models are gaining special attention in the management and maintenance of facilities. The quality of data contained in these models may be enhanced by the use of processed information coming from long-term Structural Health Monitoring (SHM). In this case real time processing and updating in systems using sensor networks for SHM need low latency and reliable communication. This paper presents a solution for exploiting DT models for SHM and early warning solutions improvement. The case study scenario resides within the 5G experimentation in the city of L’Aquila and it exploits a highly adaptable sensor board and a 5G Multi-Access Edge Computing architecture.

Design and evaluation of 5G-based architecture supporting data-driven digital twins updating and matching in seismic monitoring

Gattulli V.;Franchi F.;Graziosi F.;Marotta A.;Rinaldi C.;Potenza F.;
2022

Abstract

Digital Twins (DT) models are gaining special attention in the management and maintenance of facilities. The quality of data contained in these models may be enhanced by the use of processed information coming from long-term Structural Health Monitoring (SHM). In this case real time processing and updating in systems using sensor networks for SHM need low latency and reliable communication. This paper presents a solution for exploiting DT models for SHM and early warning solutions improvement. The case study scenario resides within the 5G experimentation in the city of L’Aquila and it exploits a highly adaptable sensor board and a 5G Multi-Access Edge Computing architecture.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11697/182569
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