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Maintenance-oriented Digital Twin for Underground Infrastructure with Sensing, Machine Learning, BIM and Simulation

CORDIS · observation · Publication date unknown

Maintenance-oriented Digital Twin for Underground Infrastructure with Sensing, Machine Learning, BIM and Simulation As buried pipelines face increasing maintenance challenges due to ageing, climate change, and infrastructure deterioration, failures can lead to severe economic losses and public safety risks. The M-Twin4US project aims to develop a novel, maintenance-oriented Digital Twin (DT) platform tailored for buried pipelines, with the flexibility to expand to other underground infrastructure. M-Twin4US will integrate advanced sensing technologies, Ground-Penetrating Radar (GPR) and closed-circuit television (CCTV), with state-of-the-art machine learning methods like Multi-task Transformers and Segment Anything Models (SAM). The project will address critical challenges in soil-pipe interaction analysis, GPR response prediction, and condition assessment by coupling digital modelling, machine learning, numerical modelling (hydro-mechanical and electromagnetic mod

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recordType

award

status

SIGNED

region

EU

value

260347.92

unit

EUR