Ubiquitous sustainable cities, Roger Ghanem University of Southern California

Ubiquitous Sustainable Cities

Roger Ghanem1

1University of Southern CaliforniaLos Angeles, CA, USA

October 6th 2009

Ghanem (USC) Ubiquitous Sustainable Cities SoCal Smart Grid Symp 1 / 16

Outline

Essential Contributions from many colleagues at USC, CSULB,Columbia, ASU, Princeton, and RAND.



Essential Premise

Actions we take today will shape the reality of tomorrow:strong coupling between several complex systems

Accurate anticipation is conducive to effective decisions.


Essential Premise

Actions we take today will shape the reality of tomorrow:strong coupling between several complex systems

Accurate anticipation is conducive to effective decisions.


Societal DriversSUSTAINABILITY BY DESIGN:

Anticipate HealthAir qualityWater supply and qualityClimate change

Anticipate WealthLocal and global economic growthConditions of civil infrastructuresPopulation dynamics

Over long time horizons (30 years - 100 years).


Societal DriversSUSTAINABILITY BY DESIGN:

Anticipate HealthAir qualityWater supply and qualityClimate change

Anticipate WealthLocal and global economic growthConditions of civil infrastructuresPopulation dynamics

Over long time horizons (30 years - 100 years).


ChallengesComplexity, Uncertainty, Mutiple scales, Humans-in-the-loop





Quantities of interest are observed on a multitutde of scales.Strong coupling between well-understood physical processes andhighly speculative processes underlying human and socialdynamics.Significant uncertainty exists in all components of the problem.Coupling between human and physical processes is at a coarsestscale (media-bites).Stakeholders are not of voting age.


Some Hope


Some HopeSUMMARY FROM A DOE WORKSHOP:


Integrated SolutionSENSING/COMMUNICATING/MODELING/DECISION

Testbeds

POWER DEMAND PREDICTION

EARTHQUAKE IN LOS ANGELES

GPSwater usepower use

traffic

seismograms/ mech. sensors

InfoGridSTATE OF URBANUS:

(current snapshot + archive)

PRESENT (or typical update time) FUTURE

Anticipationw/ Climate

Change


trafficseismograms

InfoGridANTICIPATED STATE

OF URBANUS

POLICY

Population DensityBehavior of Agents in ABM

Economic ActivityGround Motion

Condition of Lifelines




ANTICIPATED LANDSCAPES

INFERRED LANDSCAPES

MODELING

INFERRED LANDSCAPES


FLOODING IN NEW YORK CITY

TRANSPORTATION IN

LOS ANGELES

UPSCALING DOWNSCA

LING



Vision

Use information technology and modeling to enable theengineering of policies and decisions with managedconsequences.Enable data-driven prediction science for complex coupledinfrastructure systems accounting for human dynamics.


Approach and Methodology

Create information immersion through a hierarchy of areanetworks .Develop requisite IT infrastructure.Develop validated models of population dynamics and modelresponse of humans to policies and environmental drivers.Develop models for coupling humans and infrastructure systems.Fold predictive models into decision-making environments.


Integrated SolutionSENSING/COMMUNICATING/MODELING/DECISION

Testbeds

POWER DEMAND PREDICTION

EARTHQUAKE IN LOS ANGELES


traffic


InfoGridSTATE OF URBANUS:

(current snapshot + archive)

PRESENT (or typical update time) FUTURE

Anticipationw/ Climate

Change


trafficseismograms

InfoGridANTICIPATED STATE

OF URBANUS

POLICY








INFERRED LANDSCAPES

MODELING

INFERRED LANDSCAPES


FLOODING IN NEW YORK CITY

TRANSPORTATION IN

LOS ANGELES

UPSCALING DOWNSCA

LING



Nuts and BoltsON MANY LEVELS

Info Systems Models Policies

Sys

tem

s R

esea

rch

Sys

tem

Req

uire

men

ts

Fundamental Research Knowledge Base

Info. Sciencew/ Massive Data & Networks

Validation & Updating Under Complexity

Stability & Control ofHeterogenous Dynamical Sys.

Algorithms forReal-time Inference/Decision

Decision MakingUnder Complexity

QuantitativeHuman Interactions

Fundamental Insights

Fundamental Barriers1. Massive Heterogeneous

Networks2. Massive Heterogeneous

Data3. Complex Interactions

4. Long prediction horizon5. Uncertainties

6. Complexity of Humans

Technology Elements

Enabling Technology Research Technology Base

Enabling Tech Barriers1. Heterogeneous Data

2. Knowledge Extraction3. Sensor-Model Interface

4. Uncertainty in PredictionsTestbed

MYRIAD

Testbed

ModelingSystems &

Interactions

Testbed

UD-Platform

Sys

tem

Req

uire

men

ts

Systems Research Technology Integration

Requirements

Products& Outcomes

Systems Barriers1. Analysis of coupled

system2. Feedback to

Fundamental Research3. Metrics for System

Performance Industry

Partners andInnovation

Partners

Stakeholders:Decision Makers

CitizensPrivate Sector

TransportationSystem in

Los AngelesFlooding in

New York City

Earthquakein Los Angeles

Testbed

PowerDemand

PredictionTestbed


Closing

science has advanced to the point where we can build materialsone atom at a time.humans are arguably more comple than atoms.information immersion seems like a reasonable way forward.


Ubiquitous sustainable cities, Roger Ghanem University of Southern California

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