Research into Digital Twins for AEC - Revision history

Giuliapattini: /* Abstract */

2023-04-24T21:28:04Z

‎Abstract

Abel Maciel at 21:21, 18 April 2023

2023-04-18T21:21:12Z

Giuliapattini: /* Keywords */

2023-04-12T09:37:01Z

‎Keywords

Giuliapattini at 09:36, 12 April 2023

2023-04-12T09:36:28Z

Giuliapattini at 14:04, 21 March 2023

2023-03-21T14:04:29Z

Abel Maciel: /* Keywords */

2022-11-16T21:39:08Z

‎Keywords

Abel Maciel: /* Conference Presentation */

2022-11-16T21:37:46Z

‎Conference Presentation

Abel Maciel: /* Keywords */

2022-11-16T21:34:29Z

‎Keywords

Abel Maciel at 21:33, 16 November 2022

2022-11-16T21:33:44Z

Abel Maciel: /* Bibliography */

2022-11-16T21:33:15Z

‎Bibliography

← Older revision		Revision as of 21:28, 24 April 2023
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	=Abstract=		=Abstract=
		+	Autodesk Research started exploring applications for Digital Twins in the Architecture, Engineering and Construction (AEC) industry in late 2009, when it started Project Dasher, a tool for visualizing data captured from Internet of Things (IoT) sensors and Building Management Systems (BMS) inside a 3D context. It was initiated with a view to make the built environment more efficient: with 40% of global CO2 emissions coming from buildings, anything that could be done to impact this number would be worthwhile. It was built on a couple of important industry trends: the increasing availability and ubiquity of low-cost sensors and the decreasing cost of cloud storage. The Dasher team asked themselves the research question “what can we achieve if we place sensors everywhere and store all the data we can for a building over an extended period?” During the decade or more that Project Dasher was running, it went from being a desktop application to being cloud-based – testing the possibility of using Autodesk’s Forge platform (now called Autodesk Platform Services) to implement digital twins – and broadened to not only work with buildings (and Building Information Modeling – or BIM – data) but to work with smart infrastructure. In this session we explore the features we were able to build into Project Dasher – looking at projects related to both buildings and bridges – and how the project has influenced Autodesk’s new platform for digital twin creation, Autodesk Tandem.

	=Keywords=		=Keywords=

← Older revision		Revision as of 21:21, 18 April 2023
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 =Keywords=
-[[AEC]], [[Digital Transformation]], [[Digital Twins]], [[Machine Learning]], [[Digital Fabrication]], [[3D Printing]]
+[[AEC]], [[Digital Transformation]], [[Digital Twins]], [[Machine Learning]], [[Digital Fabrication]], [[3D Printing]].
 =Bibliography=

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 [[Category:Conferences]]
 [[Category:Book]]
-[[DC I/O 2022]] Presentation by [[Kean Walmsley]]. https://doi.org/10.47330/DCIO.2022.OTJU4338 | Watch [[File:VideoRecord-Icon.png |Left|22px|link=https://youtu.be/mIYyW5uh-Ww]] | [[File:Slides-Icon.png |Left|30px|link=https://www.dropbox.com/s/7rnl4ode4s4cn1t/DCIO2022_S4-3_OTJU4338.pdf?dl=0]]
+[[DC I/O 2022]] Slides by [[Kean Walmsley]]. https://doi.org/10.47330/DCIO.2022.OTJU4338 | Watch [[File:VideoRecord-Icon.png |Left|22px|link=https://youtu.be/mIYyW5uh-Ww]] | [[File:Slides-Icon.png |Left|30px|link=https://www.dropbox.com/s/7rnl4ode4s4cn1t/DCIO2022_S4-3_OTJU4338.pdf?dl=0]]

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 [[Category:Conferences]]
 [[Category:Book]]
-[[DC I/O 2022]] Presentation by [[Kean Walmsley]]. https://doi.org/10.47330/DCIO.2022.OTJU4338
+[[DC I/O 2022]] Presentation by [[Kean Walmsley]]. https://doi.org/10.47330/DCIO.2022.OTJU4338 | Watch [[File:VideoRecord-Icon.png |Left|22px|link=https://youtu.be/mIYyW5uh-Ww]] | [[File:Slides-Icon.png |Left|30px|link=https://www.dropbox.com/s/7rnl4ode4s4cn1t/DCIO2022_S4-3_OTJU4338.pdf?dl=0]]
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 =Abstract=
 =Keywords=
 [[AEC]], [[Digital Transformation]], [[Digital Twins]], [[Machine Learning]], [[Digital Fabrication]], [[3D Printing]]
 =Bibliography=

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 =Conference Presentation=
-[[File:PDF-Icon.png |Left|50px|link=]] Conference Presentation Slides.
+[[File:PDF-Icon.png |Left|50px|link=https://www.dropbox.com/s/7rnl4ode4s4cn1t/DCIO2022_S4-3_OTJU4338.pdf?dl=0]] Conference Presentation Slides.
 =Keywords=

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 =Keywords=
-[[Digital Twins]], [[Machine Learning]], [[Digital Fabrication]], [[Design Theory]]
+[[Digital Twins]], [[Machine Learning]], [[Digital Fabrication]], [[3D Printing]]
 =Reference=

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 *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
+*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).