Difference between revisions of "Research into Digital Twins for AEC"

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=Keywords=
 
=Keywords=
[[Digital Twins]], [[Machine Learning]], [[Digital Fabrication]], [[3D Printing]]
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[[AEC]], [[Digital Transformation]], [[Digital Twins]], [[Machine Learning]], [[Digital Fabrication]], [[3D Printing]]
  
 
=Reference=
 
=Reference=

Revision as of 21:39, 16 November 2022

DCIO2022-Logo.png
DC I/O 2022 Presentation by Kean Walmsley. https://doi.org/10.47330/DCIO.2022.OTJU4338



Abstract

Presentation

Left Video Recording.

Conference Presentation

Left Conference Presentation Slides.

Keywords

AEC, Digital Transformation, Digital Twins, Machine Learning, Digital Fabrication, 3D Printing

Reference

DOI: https://doi.org/10.47330/DCIO.2022.OTJU4338

Bibliography

  • Autodesk, 2022a. Autodesk Research's Project Dasher [WWW Document]. Autodesk Forge. URL https://www.autodesk.com/research/projects/project-dasher (accessed 9.30.22).
  • Attar, R., Hailemariam, E., Breslav, S., Khan, A. and Kurtenbach, G. 2011. Sensor-enabled Cubicles for Occupant-centric Capture of Building Performance Data. ASHRAE Annual Conference.
  • Attar, R. Hailemariam, E., GLUECK, M., Tessier, A., McCrae, J. and Khan, A. 2010. BIM-based Building Performance Monitor. In Proceedings of the 2010 Spring Simulation Multiconference (SpringSim '10)
  • Autodesk, 2022b. Autodesk Forge [WWW Document]. Autodesk Forge. URL https://forge.autodesk.com/ (accessed 9.30.22).
  • Autodesk, 2022c. Dasher 360 [WWW Document]. URL https://dasher360.com/ (accessed 9.30.22).
  • Autodesk, 2022d. Autodesk Tandem | Your Digital Twin Journey Starts Here [WWW Document]. Autodesk Tandem. URL https://intandem.autodesk.com/ (accessed 9.30.22).