Digital twin systems: latest research from the University of Cambridge

Overview

Digital twinning methods can produce a reliable digital record of the built environment and enable owners to reliably protect, monitor and maintain the condition of their asset.

The built environment is comprised of large assets that need significant resource investments to design, construct, maintain and operate them. Improving productivity, i.e., efficiency and effectiveness, and creating new, disruptive ways to address existing problems throughout their lifecycle can generate significant performance improvements in cost, time, quality, safety, sustainability, and resilience metrics for all involved parties.

Creating and maintaining an up-to-date electronic record of built environment assets in the form of rich Digital Twins can help generate such improvements. 

This talk introduces research conducted at the University of Cambridge on inexpensive AI methods for generating object-oriented infrastructure geometry, detecting, and mapping visible defects on the resulting digital twin, automatically extracting defect spatial measurements, and sensor and sensor data modelling.

The results of these methods are further exploited through their application in design for manufacturing and assembly (DfMA), mixed-reality-enabled mobile inspection, and proactive asset protection from accidental damage.

This event is hosted by the ICE East of England Early Careers Network (ECNet).