data-in-the-cloud city
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TRANSCRIPT
Data-in-the-Cloud City
Proactive Analysis of Digital Information about the city ! !
Gonzalo A. ARANDA-CORRALUniversidad de Huelva
Department of Information [email protected]
Alejandro BLANCO-ESCUDEROYaco Sistemas
Joaquín BORREGO-DÍAZUniversidad de Sevilla
Dept. of Computer Science and AI [email protected]
Manuel GOMAR-ACOSTAElelog S.L.
Index
Motivation & Goals
Data in the WWW and associated services
Simulating extreme dynamics
Multiagent Arch
Results
Conclusions and Future Work
Motivation (I): Context
Emergent concepts in complex systems. Applications to Urban environments and Cultural Complexity
Excellence Project. Junta de Andalucía. Spain
eCompleXcity
Motivation (II): Digital Information
Heterogeneity
Different nature
Goal-driven
Different information flows
¿Reusable?
Architecture Urbanism
Social Media
Med
ia A
rt
Mark
etin
g
Telecom
munica
tions
Web 2
.0
Location Based
services
Motivation (III)
Urban dynamics simulated from WWW data
Multiagent Systems (MAS) for simulating Complex Behaviour from mining WWW information
Limits of MAS simulation from Data about cities
Data in the
Cloud for
Urban
Dynamics?
!
City as a Complex System
Different views:
Data city
Social Network city
City as a ground of cyberinfrastructure
Local Interaction versus Global interaction
Emergent Research Line
Collect and process data for
new applications, services, and planning
Analysis of urban behaviour
Open Data initiatives facilitate R&D initiatives
Some questions...
How are WWW data about a city?
What about the quality?
Are they useful?
Can they be improved?
pre-Digital Cities versus Smart Cities
pre-Digital City:
¿Able to consume data?
Smart City:
To produce and consume its own data
Data Flows
I2U U2U
U2II2I
OpenData
Intero
perabi
lity
Socia
l
Networks
Urban Informatics
Data flows about cities in WWW (I): Institutions to User (I2U)
Essential to understand some urban process (dynamics)
Historical data and analisys
Main support of Opendata.
Data flows about cities in WWW (II): User to user
U2U (entre usuarios): P2P
Mobile devices and Social Web
Information quality.
Data flows about cities in WWW (III): User to Institutions
U2I
Strong Growth
Web 2.0 & Urban informatics
Data flows about cities in WWW (IV): Institutions to Institutions
Unavailable to users
Goverment (& enterprises) interoperability
Increasing
Different data sources for MAS simulation
Extreme Urban dynamics
Urban evolution under exceptional circunstances
pre-Digital city: New Orleans
Extreme dynamics: Katrina hurricane (2005)
Explore every WWW information about both the city and the event
Data comsumption by MAS
Why this event?First, Katrina is one of the most destructive hurricane suffered by a developed country, USA
The extent of damage invites for a macroscopic analysis of the incident
There exists a big amount of data source and Web services associated (or consumable by) Geographic Information Systems with public access
Bounding the scope
In order to evaluate the quality, accessibility and usefulness of I2U
It considers only I2U accessible by WWW, Internet or deep Internet ( that is, accessible via search forms)
In some cases a reparation of defficent data is necessary
Mainly, data from global information systems (or U.S. Agencies)
more specific data may limit the reusability.
Why MAS?MAS based simulation methodology allows to estimate how affect data quality to each module of the system:
I2U main flow for this simulation
Statistical results from surveys useful for agents-citizens behaviour.
!
I2U about New Orleans, Katrina and its effects (I)
U.S. Geological Survey (http://www.usgs.gov/)
National Elevation Dataset (http://ned.usgs.gov/).
Precisions ~ 3 meters
Open Street Maps (OSM, http://www.openstreetmap.org/),
Geographical Area
Main Area
Divided into 3
!
!
Agents Modelling
Agentification Process
3 kind of agents
Environment
Water
Citizens
Environment agents
Information about terrain
Discretized in hexagons
Update water information (by WaterAgent request)
Citizen Agents ask information to environment agents
Water agents (I)
Potential energy: Reactive agent
Direction
Speed
Unaffordable information
River is initial agent state
Water agents (II)
Future;
Buildings geometry
http://sketchup.google.com/
Complemented by OSM.
!!
Citizen agents
Papers about social behaviour in critical situations
Fundamental to citizen agents design
Patterns of behaviour from the surveys of survivors
Prevent riskies situations
Also design groups of agents
Based on published information
MAS level
Evacuation paths
Group behaviour in panic situations
Visualization
Based on OSM and Google Maps/Earth
Some extra data:
Disaster scope
Survivors / zone
etc...
http://www.youtube.com/watch?v=pTKhrpl9jZc
Population, demography, flooding
Conclusions
I2U information flows is used, in this work, to simulate urban phenomena
Simulation needs digital information from cities and its own feedback
Previous and exhaustive information analysis and clasification its fundamental to start any kind of urban cloud computing
Future Work
Use Complex Systems methodologies to analyse and to compare events and simulations
To detect emergent phenomena in digital cities by means of simulation and Data mining
Data-in-the-Cloud City
Proactive Analysis of Digital Information about the city ! !
Thanks for your attention