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SUMMARY:Generation of Geometric Digital Twins of Rail Infrastructure - Mah
 endrini Fernando Ariyachandra\, PhD Candidate\, CUED
DTSTART:20190315T150000Z
DTEND:20190315T160000Z
UID:TALK121063@talks.cam.ac.uk
CONTACT:Karen Mitchell
DESCRIPTION:The need to create and maintain up to date digital copies of i
 nfrastructure assets has been well established in literature. These copies
  are often labelled Digital Twins. Their most basic form includes only the
 ir geometry (Geometric Digital Twin-GDT). Yet\, very few assets today have
  a usable digital twin. This occurs because the perceived cost of the crea
 ting and maintaining the digital twin greatly counteracts the perceived be
 nefits of the twin. This happens in part because of the labour cost needed
  to manually build/maintain the digital model. This cost is substantive be
 cause state-of-the-art digitisation technologies necessary for automated d
 elivery of the GDT require substantial labour hours to build even a simple
 \, geometry only model. We will tackle this challenge by proposing a digit
 isation framework\, focused on delivering an automated way to create AI-GD
 Ts of rail infrastructure. It starts with registered PCDs and ends with GD
 Ts of railways. The proposed framework combines the strength of the ‘dat
 a-driven’ strategy scenarios with very high point densities and ‘model
 -based’ strategy in scenarios with very low point densities. 
LOCATION: Cambridge University Engineering Department\, LT6
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