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The City Knowledge Platform Intelligent Urban Agents for Smart Cities Center for Advanced Spatial Analysis October 19, 2012 University College London Fabio Carrera

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The City Knowledge Platform Intelligent Urban Agents for Smart Cities

Center for Advanced Spatial Analysis October 19, 2012 University College London Fabio Carrera

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Fabio Carrera •  Associate Professor at WPI •  BSEE, MSCS (WPI) •  PhD in Urban Information Systems and Planning (MIT) •  Venice, Boston and Santa Fe Project Centers (WPI) •  Chair of Spencer Planning Board •  100’s of City Projects for past 25 years

Key CK Papers: •  Scholar.google.com (Fabio Carrera) •  Carrera 2004 (MIT Dissertation) •  Carrera & Ferreira (2007) •  Carrera & Hewitt (2006)

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TODAY

Part I: Cities and City Knowledge Part II: Cities as Complex Adaptive Systems

Part III: Demonstrations of CK Platform

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TODAY

Part I: Cities and City Knowledge Part II: Cities as Complex Adaptive Systems

Part III: Demonstrations of CK Platform

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PART I: CITIES AND CITY KNOWLEDGE

Urban Data Management City Knowledge Concepts

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URBAN DATA MANAGEMENT 1.0

Documentation (vs. Information) Silos and Stovepipes

Redundancy and Discrepancies Staff, Vendors and Consultants

Complicated Cross-Coordination

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CITY KNOWLEDGE CONCEPTS

Foundations Premises

Tenets Implementation

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DISSERTATION (MIT) - 2004

City Knowledge: An Emergent Information Infrastructure for Sustainable Urban Maintenance, Management and Planning

http://hdl.handle.net/1721.1/28790 (google: ”City Knowledge MIT”)

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DISSERTATION (MIT) - 2004

Information

An Emergent Information Infrastructure for Sustainable Urban Maintenance, Management and Planning

“As the variety of geospatial information and data resources increases each year, the demand for understanding and building sustainable information and knowledge structures remains a critical research challenge for the geo-spatial information community.” Shuler, 2003. Research Priority of the University Consortium of Geographic Information Science.

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DISSERTATION (MIT) - 2004

Information Infrastructure

An Emergent Information Infrastructure for Sustainable Urban Maintenance, Management and Planning

Like the water distribution system, the road network, the sewage system… (connected, efficient, maintained, funded, pervasive)

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DISSERTATION (MIT) - 2004

Information Infrastructure Emergent

An Emergent Information Infrastructure for Sustainable Urban Maintenance, Management and Planning

Not centrally designed or imposed from the top, but gradually constructed from self-serving departmental modules

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DISSERTATION (MIT) - 2004

Information Infrastructure Emergent Sustainable

An Emergent Information Infrastructure for Sustainable Urban Maintenance, Management and Planning

Not a single-purpose do-it-all system doomed for obsolescence, but continually fed with perpetual update mechanisms

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DISSERTATION (MIT) - 2004

Information Infrastructure Emergent Sustainable Maintenance, Management & Planning

An Emergent Information Infrastructure for Sustainable Urban Maintenance, Management and Planning

Useful in multiple contexts, serving the operational (maintenance) needs of the town first, while also feeding higher-order management and planning functions of the municipality.

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EVOLUTION OF CITY KNOWLEDGE

Plan Demanded Data Plan Ready Information

Plan Demanding Knowledge

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EVOLUTION OF CITY KNOWLEDGE

Plan Demanded Data Plan Ready Information

Plan Demanding Knowledge •  Data is collected for a “specific” reason when a plan or a process demands it. •  It is typically acquired as documentation to support a decision/plan. •  It is not used for anything else. •  It is often discarded (archived) after it is used once.

Status Quo in Most Cities

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EVOLUTION OF CITY KNOWLEDGE

Plan Demanded Data Plan Ready Information

Plan Demanding Knowledge •  Plan-demanded data is acquired as information •  Where possible, richer data is collected to serve multiple purposes •  Data is preserved beyond its immediate use •  Up-to-date information is always available for plans/processes

CK = Information at your fingertips (efficiency)

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EVOLUTION OF CITY KNOWLEDGE

Plan Demanded Data Plan Ready Information

Plan Demanding Knowledge •  Over time, patterns/issues emerge from an analysis of plan-ready information •  This knowledge triggers the demand for a plan to address issues

CK+ = Unforeseen Benefits Emerge (Value-added bonus)

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GOAL OF CITY KNOWLEDGE

To promote the transformation of Municipalities from Hunter-gatherers of urban data to Farmers of municipal information

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PHILOSOPHY OF CITY KNOWLEDGE

treated as any other City Infrastructure farmed not hunted

atomized by urban element re-combined and re-used

Urban Information should be:

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PREMISES OF CITY KNOWLEDGE

Cities are “finite” City = Structures & Activities

Municipal gov. controls urban change Past can be reconstructed (once) Future can be intercepted (daily)

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PREMISES OF CITY KNOWLEDGE

Cities are “finite” City = Structures & Activities

Municipal gov. controls urban change Past is capturable (once)

Future is also capturable (daily)

•  Spatially (boundaries) •  Temporally (past and future)

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PREMISES OF CITY KNOWLEDGE

Cities are “finite” City = Structures & Activities

Municipal gov. controls urban change Past is capturable (once)

Future is also capturable (daily)

“The Fundamental problem is to decide what the form of a human settlement consists of […] […] the chosen ground is the spatiotemporal distribution of human actions and the physical things which are the context of those actions […]”. Kevin Lynch, Good City Form

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PREMISES OF CITY KNOWLEDGE

Cities are “finite” City = Structures & Activities

Municipal gov. controls urban change Past is capturable (once)

Future is also capturable (daily) •  Like politics, “all change is local” •  Change is brought about (primarily) by private sector •  Change is filtered by municipalities

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PREMISES OF CITY KNOWLEDGE

Cities are “finite” City = Structures & Activities

Municipal gov. controls urban change Past can be reconstructed (once)

Future can be intercepted (daily) •  There is a lot of “stuff” already out there •  But the amount is finite •  And it only needs to be captured once

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PREMISES OF CITY KNOWLEDGE

Cities are “finite” City = Structures & Activities

Municipal gov. controls urban change Past can be reconstructed (once)

Future can be intercepted (daily)

•  Structures change slowly yet daily •  But Change is filtered by government

•  Activities change rapidly •  But can be frozen periodically •  And not that frequently

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TENETS OF CITY KNOWLEDGE

Space is “the glue” Activities are localizable

Data stays where it is created Self-interest guides adoption

Middle-out = bottom-up + top-down

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PRINCIPLES OF CITY KNOWLEDGE

Espouse a Middle-out Approach Demarcate Informational Jurisdictions

Relentlessly Accrue Fine-grained Data Implement Sustainable Update Mechanisms

Share Information Selectively Coordinate Across Departments and Agencies

Treat Information as an Infrastructure!

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ADOPTING CITY KNOWLEDGE

Adopt an information-aware m.o. Extract informational returns systematically

Connect datasets through “space” Develop department-level solutions

Start with “low-hanging” fruits

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n  Atomize

n  Codify and Index through Space n  Represent “literally” n  Capture permanently n  Acquire at the finest practical grain n  Parameterize teleologically n  Spatialize dynamic activities n  Maximize informational returns

The Lessons

Treat Information as an Infrastructure

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n  Fine-grain is now achievable inexpensively

n  Backlog is finite n  Change is interceptable n  Technologies can automate data collection n  Application of the 6 tools can do the rest n  Internet-based information facilitates sharing n  Departments are in charge n  Regional patterns will emerge

The Essence of CK

Treat Information as an Infrastructure

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IMPLEMENTING CITY KNOWLEDGE

Connecting Legacy Systems Collecting Backlog Data

Capturing Future Change Facilitating Interagency Coordination Identifying Self-funding Mechanisms

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TODAY

Part I: Cities and City Knowledge Part II: Cities as Complex Adaptive Systems

Part III: Demonstrations of CK Platform

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PART II: COMPLEXITY AND CITIES

Complexity Principles Urban Agents

The City Knowledge Platform

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PART II: COMPLEXITY AND CITIES

Complexity Principles CK + ABM = Urban Agents

The City Knowledge Platform

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COMPLEXITY PRINCIPLES

Santa Fe Complex Adaptive Systems

Agents Models

Complexity and Cities

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COMPLEXITY AND SANTA FE

Santa Fe Institute Redfish

Santa Fe Complex WPI Santa Fe Project Center

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Santa Fe Institute

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COMPLEX ADAPTIVE SYSTEMS

Self-Organizing Structures Lightning, Tornadoes and Whirlpools

Complex Animal Behaviors Swarming & Foraging

Attraction/Repulsion & Stigmergy

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[email protected]

Swarm Behavior

Boids

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A Simple Agent

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Repel

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Attract

Repel

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dual gradients in ant foraging algorithm Antz

Stigmergic Behavior

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AGENTS

Simple Autonomous Behavior Not guided by overarching control

Find & Remove Gradients Monitor & Change Space

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AGENT BASED MODELING

Modeling of Activities Thin Agents

Complex Distributed Behavior No Central “Brain”

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2D Crowd Evacuations (90’s)

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2.5D Evacuation w/ Interaction

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Multi-model Applications

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Pedestrians and Changing Space (‘06)

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COMPLEXITY AND CITIES

Cities are Self-Organizing Structures City Government softens Gradients

USA: Life, Liberty and the Pursuit of Happiness Rome: Humanitas, Libertas et Felicitas

The CK Platform as applied Complexity (1)  Agents and Stigmergy

(2)  City Gradients and City Processes

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PART II: COMPLEXITY AND CITIES

Complexity Principles CK + ABM = Urban Agents

The City Knowledge Platform

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URBAN AGENTS

Urban Agents (for Structures and Activities) Birth Certificates

Intelligent Urban Assets

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Coats of Arms Confraternity Symbols

Crosses Fragments

Sculptures Inscriptions Patere Street Altars Reliefs

Bells Church Floors

Fountains Wellheads

Lunette

Decorations

Keystones Portals

Monuments • Flagstaff Pedestals

Example: Venice Public Art

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UNESCO Public Art App

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PART II: COMPLEXITY AND CITIES

Complexity Principles Urban Agents

The City Knowledge Platform

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THE CITY KNOWLEDGE PLATFORM

Urban Data Farming Interagency Coordination

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URBAN DATA FARMING

Legacy Data Automatic sensors

Mobile Apps

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LEGACY DATA

Integrated, not supplanted Instant updates

Bi-directional synchronization The CK Console

The CK Chrome Extension

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CK Console

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CK Chrome Extension

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AUTOMATIC SENSORS

Data Loggers Surveillance Cameras

Existing underutilized sensor networks

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Energence

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Boston Street Lights

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Subscribing to Camera Pixels

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MOBILE APPS

InputApp.com VeniceNoise.org StreetBump.org

PreserVenice.org

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InputApp

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Venicenoise.org

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StreetBump.org

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PreserVenice.org

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INTERAGENCY COORDINATION

Privacy and Security Private and/or Public Data

Sharing with Groups Interactive collaborative Environments

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[email protected] fabiocarrera.com [email protected]

THANKS!