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www.centreforsmartinfrastructure.com
@CSIC-IKC
The role of sensing and data in transforming the future of infrastructure
The challenge
“Productivity in manufacturing has nearly doubled, whereas in construction it has remained flat”Source: McKinsey&Company, “The construction productivity imperative”By S Changali, A Mohammad and M van Nieuwland, July 2015
“The construction industry is among the least digitized”
Smart Infrastructure:Better decisions faster and cheaper for the benefit of the ultimate customer or user
DigitalSmartPhysical
Smart infrastructure – a smart way of adding value to both existing and new strategic assets
Smart Infrastructure
The value of data
Data curation is crucial!
EMBEDDED SENSING SYSTEMS Fibre optic strain sensors Fibre-optic geogrid systems Wireless sensors for earthworks monitoring
ATTACHED SENSING SYSTEMS Autonomous, low-cost and low-power wireless sensing
technology for long-term monitoring Wireless fatigue sensor Vehicle mounted sensing Combined strain and displacement wireless sensors Temperature, tilt, etc
SOCIAL MEDIA AND OTHER DATA SOURCES Geo-tagged social media data for assessing use of infrastructure and
sentiment mapping Ticketing information Mobile phone GPS, wifi On-vehicle GPS, vehicle mounted sensors
DATA ANALYTICS APPROACHES Geospatial data analysis Data-centric engineering – AI
AUTOMATED SENSING SYSTEMS Automated visual inspection Remote controlled boat for underwater surveying Mixed reality automated solutions for construction
progress monitoring
There are many sources of data!REMOTE SENSING
Use of satellite data to monitor large-scale structural and ground movement
Drone surveys Laser scanning Photogrammetry
UK National Infrastructure Commission Report:
Data for the Public Good
• Data for the Public Good – released 14 Dec 2017
• Backed up by four technical papers:1. Data as infrastructure2. Data sharing in infrastructure3. Better asset management through smarter information4. Resilience of Digitally Connected Infrastructure Systems
• Identified key challenges around data in the UK economic infrastructures:
• Lack of integration of data between infrastructure systems / silos
• Failure to use data optimally to enable improved operation of infrastructure systems (data driven decision-making)
National Infrastructure Commission
• Data as Infrastructure• Vastly increased quantities of data• New mechanisms to collate, manage and process - >• New opportunities for society to better utilise resources,
solve problems and provide most social good
• Data Sharing in Infrastructure• Improve efficiency through better informed decisions• Better infrastructure planning• Improved resilience• Increased competition and innovation
Data for the Public Good
So what can we do with better data?
Improved designs – less resource use, better resilience
OPPORTUNITIES• Validating models• Demonstrate cost saving
and value• Design for whole life
value
OPPORTUNITY• ‘As-built’ BIM• Quality assurance• Construction progress
monitoring• 3rd party asset
monitoring
Transforming construction –reducing waste, improving quality
No shape matching(behind schedule)
Shape matching but no texture match
(in progress)
Shape matching & texture matching
(on schedule)
Structural Health Monitoring
OPPORTUNITY• Understand and
quantify asset condition and behaviour
• Assess deterioration rates
• Inform maintenance requirements
Giving an asset a ‘health passport’
OPPORTUNITY• Condition monitoring
and predictive maintenance
• Risk-based maintenance• Whole-life, value based
asset management• Futureproofing
Managing and operating infrastructure
OPPORTUNITY• Demand forecasting• Optimised network
management• Planning in 3-d• Energy assessments and
modelling
Cities and regions – understanding how infrastructure systems serve our communities
Paper 4_CSIC Big project map
Smart city systemsTRANSPORT PLANNING
Predictive models for travel, including choice and cost factors
Demand forecasting Pedestrian flow modelling and monitoring
LAND USE PLANNING Rail-led urban development Agent-based modellingModelling the influence of creative industries on
urban land use LUISA model - land-use interaction with social
accounting
CITY-SCALE ASSET CONDITION MODELLING
Network load modelling and prediction Data, modelling and management of city-
scale asset degradation
THE 3-DIMENSIONAL CITY
Integrated development of above and underground spaces
Increasing utilisation of underground spaces Environment and energy in underground spaces Integrated digital mapping and visualisation of
above and below ground spaces
ENERGY NEEDS AND PLANNING Integrated modelling of people, energy & housing Distributed energy networks Innovative, synergistic energy solutions at the district
scale Urban food production
Image: Tim Hillel
DIGITIAL CITIES FOR CHANGE (DC2) Digital tools for policy, governance and management of a city and infrastructureModelling and data analysis to inform policy
Digital Cities for Change – DC2
Project objectives• Build knowledge on how currently existing governance systems, (incl.
structural and cultural characteristics) influence what is consideredfeasible, appropriate and desirable when it comes to deciding aboutand implementing digital solutions - such as the city digital twin(CDT)
• Develop governance framework for CDT design and implementation
• Context-boundedness: case study (Cambridge) and (preliminary)comparative analysis
Recommendations:• A National Digital Twin – to enable
better outcomes from our built environment• A Digital Framework – to enable secure data
sharing and effective information management• A Digital Framework Task Group – to provide
coordination of key players
• Being facilitated by CDBB
Data for the Public Good
What is a digital built Britain?
BuildOperate
Design
Integrate
A digital built Britain:• understanding what
information is needed right from the start
• ensuring feedback loops are in place throughout an asset’s lifecycle
• information enabling better whole life value and optimising services to improve socio-economic outcomes for citizens
• exploit new and emerging skills and technology to increase productivity.
Digital Twins: Definitions
A Digital Twin (DT) is a realistic digital representation of something physical
The National Digital Twin (NDT) is an ecosystem of DTs connected via securely shared data
Values: the Gemini PrinciplesPublic goodMust be used to deliver genuine public benefit in perpetuity
Value creation Must enable value creation andperformance improvement
InsightMust provide determinable insight into the built environment
SecurityMust enable security and be secure itself
OpennessMust be as open as possible
QualityMust be built on data of an appropriate quality
FederationMust be based on astandard connectedenvironment
CurationMust have clear ownership, governance and regulation
EvolutionMust be able to adapt as technology and society evolve
Purpose: Must have clear purpose
Trust: Must be trustworthy
Function: Must function effectively