Smart City and Digital Twin
Sanghee Shin(shshin@gaia3d.com)
Gaia3D, Inc
15th December 2020
Digital Twins
2<Source: https://www.youtube.com/watch?v=iVS-AuSjpOQ>
Digital Twins
<Source: https://www.pbctoday.co.uk/news/bim-news/digital-twin-4-0/64519/>
Digital Twin
A realistic digital representation of assets, processes or systems in the built or natural
environment. The complexity of that representation, and degree of connectedness, varies
depending on maturity.
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Concept: Digital Informational Construct
Vision: Create, Test, Build
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Industries
Source: AIDAN FULLER et al, Digital Twin: Enabling Technologies, Challenges and Open Research
Urban Management using Digital Twin
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CPS(Cyber Physical System) and Smart City
6
Source: Ministry of Land, Infrastructure and Transport, Korea
The Rise of Digital Twins in Smart Cities
<Source: https://www.smartcitiesworld.net/special-reports/special-reports/the-rise-of-digital-twins-in-smart-cities>
Digital Twin Market Forecast
8<Source: Managing change and culture to enable the shift towards smart built environment, Jakub Wachocki>
<Source: https://csengineermag.com/crucial-geospatial-technology-trends-in-future/>
1. Miniaturization of Sensors
2. Consistent Accessibility of EO Information
3. Geospatial AI or Geo.AI
4. BIM
5. Autonomous Vehicles
6. Mapping as a Service
7. Smart Cities
8. Drones
Recent Trends of Geospatial Industry
<Source: https://www.gov.uk/government/publications/unlocking-the-power-of-locationthe-uks-geospatial-strategy>
<Source: https://www.gov.uk/government/publications/unlocking-the-power-of-locationthe-uks-geospatial-strategy>
Self-Healing High-Definition Map
12<Source: https://newsroom.intel.com/articles/why-how-making-hd-maps-automated-vehicles/#gs.7zi2a4>
<Source: “Key Trends that Shapes Location Intelligence”, INSPIRE Workshop 2020, Gartner>
Live(Real-Time)
Geospatial
AEC(CAD/BIM)
+
Geospatial
Expansion of
Geospatial Coverage
(Indoor, Underground, Space,
Seafloor…)
Analytics, Simulation,
&
Visualization
Digital
Twin
Level 1
3D Modeling &
Visualization
Level 2
Real-time
Monitoring
Level 3
Analysis, Prediction
Optimization
Level of Digital Twins
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Element Defining principle Outline usage
0 Reality capture As-built survey
1 2D map/system or
3D model
Design/asset
optimisation and
coordination
2 Static data,
metadata and BIM
Stage 2
4D/5D simulation
3 Real-time data Operational
efficiency
4 Two-way data
integration and
interaction
Remote and
immersive operations
5 Autonomous
operations and
maintenance
Self-governance,
oversight and
transparency
<Source: https://theiet.org/digital-twins>
<Source: Use the IoT Platform Reference Model to Plan Your IoT Business Solutions, Gartner>
GeoBIM
GIS
CityGML
GeospatialInformation
GISStandards
IFC
BIM
OutdoorModel
IndoorModel
BIMStandards
Construction
DrawingsInfo.
In/Outdoor
GIModel
(GeospatialInformation
Model)
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IDBE(Integrated Digital Built Environment)
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“… to increase interoperability between the
geospatial and built environment domains,
specifically through coordination of standards
development… “
EuroSDR
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<Source : http://www.eurosdr.net/research/current>
<Source : https://3d.bk.tudelft.nl/projects/eurosdr-geobim/>
The spatial data research interests of European
countries are represented through the membership
in EuroSDR of national organisations from their
production and research sectors.
National Digital Twin Programme
Building Locale Neighborhood City Region Nation
<Source: https://www.cdbb.cam.ac.uk/national-digital-twin-programme, and Jeremy Morley>
National Digital Twin Programme(U.K.)
20<Source: https://www.youtube.com/watch?v=ChCNcLY6tKA>
UK National Digital Twin Programme Gemini Principles
<Source: The approach to delivering a National Digital Twin for the United Kingdom>
Information Value Chain
<Source: https://www.cdbb.cam.ac.uk/system/files/documents/TheGeminiPrinciples.pdf>
Digital Twin based Smart City Project
<Source: 2019년 스마트시티 시범도시(세종, 부산) 디지털트윈 마스터플랜 수립 및 시범시스템 구축용역 제안요청서, LX공사>
Digital Twin based Smart City Facility Management
<Source: Hwasoo Yeo, KAIST>
Digital Twin based Smart City
<Source: Helsinki 3D+ Digital Twins of a City>
Smart City Platform
<Source: ITU Focus Group on Smart Sustainable Cities>
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디지털 트윈 기반 스마트 시티 플랫폼
<Source: ISO/IEC JTC1/WG11>
Stakeholders
Vision & Outcomes
Business Process Framework
Knowledge Management Framework
Engineering Framework
Real Cases – BIM Visualization
Real Cases – As_Is vs To-Be
Real Cases – Autonomous Vehicle Tracking & Visualization
Real Cases – Wind Field Visualization
Real Cases – Urban Planning Simulation
Real Cases – Building Shadow Analysis
Wrapping Up – Benefits and Risks
Benefits Risks
• Reduced construction &
operating costs
• Cyber security
• Improved safety • Over selling &
expectations
• Increased productivity &
efficiency
• Increased complexity
and cost to implement
digital twins
• Optimised asset
performance &
sustainability
• Lack of standards
• Reduced conflict among
stakeholders
• Lack of professionals
• Increased collaboration • Lack of common
terminology and
knowledge
<Source: IET, Digital twins for the built environment>
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Criticism
<Source: https://www.ordnancesurvey.co.uk/business-government/innovation/happens/articles-ehs/smart-cities-digital-technologies>
“Despite the futuristic images the term conjures, a “smart city”
is merely a well-managed city aided by digital technologies.
One of the primary challenges in achieving success for smart
cities, and the reason many initiatives have failed to make it
past the pilot stage, is that they have been driven by a focus
on implementing the technology rather than achieving the
end policy goal, such as improving access to education, or
better transport links.”
<Source: https://placesjournal.org/article/a-city-is-not-a-computer/?cn-reloaded=1>
Thank you!
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Sanghee Shin shshin@gaia3d.com

Smart City and Digital Twin