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Multi-Sector Urban System Initiatives
Colin Harrison
IBM Distinguished Engineer Emeritus
Regional Approaches to Urban Sustainability
A National Academies Workshop
Portland, OR – May 28-29, 2013
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From Engineering Efficiency to a Science of Cities
• 2005-7 Life on an Instrumented Planet
• 2008-10 Integrated, sustainable urban systems
• 2011- Sustainable and resilient urban systems
• 2012- People and urban systems
A Science of Cities
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Measuring, Monitoring, Modeling and Managing
Metering Sensing
Real Time Data Integration
Real Time + Historical Data
Data Modeling + Analytics
Visualization + Decisions
Data modeling and analytics to create insights from data to feed decision support and actions
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Comparison of historical data, with newly collected data
Data collection
Improved performance derived from data and models to increase efficiency
and effectiveness
Data Integration
Source: “Instrumenting the Planet”, IBM Journal of Research & Development, March 2009
Life on an Instrumented Planet
• The world’s resources are finite
– Energy – cost, GHG emissions
– Water – “no cost”, Tragedy of the Commons
– Space – roads take 20% of space
• Technology is cheap and available
– Billions of sensors
– Pervasive networks
– Capacity to store and analyze
• Need to close the loop
– Price signals
– Social Computing
– Behavioural Economics
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Integrated, sustainable urban systems
Intelligent Transportation Systems - Integrated Fare Management - Road Usage Charging - Traffic Information
Management - Electric Vehicles
Energy Management - Network Monitoring & Stability - Smart Grid – Demand
Management - Intelligent Building Management - Automated Meter Management
Environmental Management - City-wide Measurements - KPI’s, scorecards - CO2 Management
Smart Integrated Building Management
- Integrated control systems - Property Performance
Management - Building to Grid
Enhanced Public Safety - Intelligent Surveillance - Integrated Emergency Services - “Weatherproofing” - Micro-Weather Forecasting
Water Management - Smart metering - Network instrumentation - Combined Sewage
Overflow
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Source: Economist Intelligence Unit survey
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Loss of data
Human error
System failure
Supply chain disruption
Virus, worm or other malicious attack on IT systems
Employee malfeasance, e.g. theft or fraud
Natural disasters, such as fires or floods
Unplanned downtime of online systems
Terrorism
Power outage
Pandemic
Application failure
Industrial action
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31
29
28
25
22
22
16
13
13
12
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Natural disasters, human error, cascading failures, and cyber-security attacks highlight the complexity and fragility of our global society, its businesses and infrastructure
Thailand: Flooding 2011
Loss ~$4 B, 550 Lives
Auto and HDD are hit hard
Australia: Bushfires, 2009
Loss ~$4B, 173 Lives
WW: Cloud Service
Outage , 2011
Loss ~$5600/min
USA: Cyber-attack, 2011
Loss ~$170M,
Personal information
is stolen
Japan: Quake/Tsunami/
Nuclear, 2011
Loss ~$200B, 30K Lives
Global supply chain impact
USA: Port Strikes, 2002
Loss ~$15B
Retail and supply chain
disruptions
0
20000
40000
60000
80000
100000
120000
2005 2006 2007 2008 2009 2010
Number of
incidents
reported to
US-CERT
(Source: US-CERT)
$200B
1900 2011
Estimated damage
caused by
reported natural
disasters
(Source: EM-DAT)
Types of threats
most important
for operational
risk management
planning
(% respondents)
China: + 37 countries,
SARS, 2002-2003
Loss ~$15B, 916 Lives
Major workforce
disruptions
Iceland: Volcano, 2010
Loss ~$1.7B
10M Passengers affected
Sustainable and Resilient Urban Systems
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Urban Systems
Information
Capture
Structure Integrate
Store
Typology Taxonomy
Networks Scaling
Economics
Basic
Resources
Natural
Environment
Flows &
Connections
Built
Environment
Integrated
Simulations
Engineers Complexity
Theorists
Urbanists
Transportation
Planners
Transportation
Managers
Energy/Utility
Managers
Public Safety
Managers
Public Health
Managers
Environmental Managers
Economic
Development
Leaders
Urban
Systems
Analysts
Social
Scientists
Civic Groups /
Open Data
A Science of Cities
Architects
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Closing thoughts…the City as a Design Problem
• Cities are and always have been information processing systems.
• Cities today are both the source and the solution of many of our global society’s challenges.
• Given the increasingly rich pathways between and among urban systems and people for digital information….what would Steve do?
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Global Systems Science Challenges for Urban Systems 1. Formal representation of Urban Systems
• Structures of components • Interactions (P2P, P2S, S2P, S2S) • Inter-dependencies (P<-S, S<-S)
2. Spatial, Temporal, and Domain Integration • “Single View of the Truth” • What real-world problems are we trying to solve?
3. The Need for Flower Collecting • Patterns & Principles to simplify model building
4. Scientific Modeling and Practical Modeling • Understanding and insight • Support for decision-making • Rule of one hand – tipping points
5. Resource consumption & production • Natural and Man-Made resources • By-products, waste • Economic outcomes
6. View of “what is the City trying to do?” • “Real-time” sensing of interactions, resource consumption & production • Match between intention and capabilities • City as a Design Problem – How well does it work?
7. Transformation of how the city works • Transition from Industrial Age to Information Age • Planning for One