The document discusses urban computing within the context of the LARKC project, focusing on the integration of technology in urban environments to answer common mobile user inquiries regarding transportation and social gatherings. It emphasizes the challenges of data availability, variability, and the need for effective data representation and reasoning in urban settings. Additionally, it highlights potential solutions such as mashups and data pipelines to enhance user experiences in navigating cities.

1. Urban Computing in LarKC
ITN – Infrastructure, Telematics and Navigation – Turin, October 15th
-16th
2009 - © CEFRIEL 2009
Urban Computing in LarKC
http://www.larkc.eu
Irene Celino
Project Manager – Senior Consultant – “Semantic Web & Web 3.0” Practice Coordinator
CEFRIEL – ICT Institute – Politecnico di Milano

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2Urban Computing in LarKC
Cities Are AliveCities Are Alive
 Cities born, grow, evolve
like living beings.
 The state of a city
changes continuously,
influenced by a lot of
factors,
 human ones: people
moving in the city or
extending it
 natural ones:
precipitations or climate
changes
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[source http://www.citysense.com]

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Some Mobile Users’ QuestionSome Mobile Users’ Question
 “Is public transportation where I am?”
 “Is the event where I am the one that attract more people
right now?”
 “Where are all my friends meeting?”
 “Is the traffic moving where I’m going?”
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Urban Computing as an Answer to ThemUrban Computing as an Answer to Them
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[source IEEE Pervasive Computing,July-September 2007 (Vol. 6, No. 3)]
Urban ComputingUrban Computing
The integration of computing, sensing, and actuation technologies
into everyday urban settings and lifestyles.
 Urban settings include, for example, streets, squares, pubs, shops,
buses, and cafés - any space in the semipublic realms of our towns
and cities.
 Only in the last few years have researchers paid much attention to
technologies in these spaces.
 Pervasive computing has largely been applied
 either in relatively homogeneous rural areas, where researchers have
added sensors in places such as forests, vineyards, and glaciers
 or, on the other hand, in small-scale, well-defined patches of the built
environment such as smart houses or rooms.
 Urban settings are challenging for experimentation and deployment,
and they remain little explored
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Dimension of Urban ComputingDimension of Urban Computing
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Urban Computing Use Case in LarKCUrban Computing Use Case in LarKC
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Data AvailabilityData Availability
 Some years ago, due to the lack of data, Urban Computing looked
like a Sci-Fi idea.
 Nowadays, a large amount of the required information can be made
available on the Internet at almost no cost. We are running a survey
[1,2] and we have collected more than 50 sources of data:
 maps (Google, Yahoo!, Wikimapia, OpenStreetMap),
 events scheduled (Eventful, Upcoming…),
 voluntarily provided users location (Google Latitude),
 mass presence and movements
 multimedia data with information about location (Flickr…)
 relevant places (schools, bus stops, airports...)
 traffic information (accidents, problems of public transportation...)
 city life (job ads, pollution, health care...)
[1] http://wiki.larkc.eu/UrbanComputing/ShowUsABetterWay
[2] http://wiki.larkc.eu/UrbanComputing/OtherDataSources
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Are Mashups the Solution?Are Mashups the Solution?
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[source: http://www-01.ibm.com/software/lotus/products/mashups/ ]
IBM Lotus Mashups
[source: http://editor.googlemashups.com ]
[source: http://pipes.yahoo.com/pipes/ ]
[source: http://www.popfly.com/ ]
[source: http://openkapow.com/ ]

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Mashups offer powerful visualization toolsMashups offer powerful visualization tools
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Google Charts API
http://code.google.com/apis/chart/http://maps.google.it/
http://maps.yahoo.com/
MIT Simile Timeline & Timeplot
http://simile.mit.edu/timeline/ http://simile.mit.edu/timeplot/

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…… and simple programming abstractionsand simple programming abstractions
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Not Everything Boils Down to PlumbingNot Everything Boils Down to Plumbing
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Requirements for Mobile Data MashupsRequirements for Mobile Data Mashups
 Urban Computing encompass sensing, actuation and
computing requirements.
 Many previous work in the area of Pervasive and Ubiquitous
Computing investigated requirements in sensing, actuation,
and several aspects of computation (from hardware to
software, from networks to devices)
 In LarKC we focus on Knowledge Representation and
Reasoning requirements
 Hereafter we exemplify the need to cope with
 representational, reasoning, and defaults heterogeneity
 scale
 time-dependency
 noisy, uncertain and inconsistent data
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Coping with representational heterogeneityCoping with representational heterogeneity
 It is an obvious requirement
 data always come in different formats (syntactic and structural
heterogeneity)
 the problem of merging and aligning data is a structural problem of
system interoperability
 while the perfect “one-size-fit-all” solution does not exist, a
comprehensive array of partial solutions exit
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Coping with multiple reasoning paradigmsCoping with multiple reasoning paradigms
precise and vs. approximate
consistent inference reasoning
[ source http://senseable.mit.edu/ ]

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Open World vs. Closed World
Assumption Assumption
[source: http://gizmodo.com/photogallery/trafficsky/1003143552 ]
Supporting Heterogeneity 1/2Supporting Heterogeneity 1/2

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Unique Name Assumption in multiple models
representing reality at different granularities
1 2
29
30
L3L3
Supporting Heterogeneity 2/2Supporting Heterogeneity 2/2

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 Nature of changing data
 Periodically changing data
 Pure periodic law
 Probabilistic law
 Event driven changing data
 Mean time between changes
 Slow
 Medium
 Fast
Coping with Changing DataCoping with Changing Data

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Coping with Changing KnowledgeCoping with Changing Knowledge
 Invariant knowledge
 it includes obvious terminological
knowledge
 such as an address is made up by a street
name, a civic number, a city name and a
ZIP code
 less obvious nomological knowledge
that describes how the world is
expected
 to be
 e.g., given traffic lights are switched off or
certain streets are closed during the night
 to evolve
 e.g., traffic jams appears more often when it
rains or when important sport events take
place
 Invariant data
 do not change in the observation
period, e.g. the names and lengths of
the roads.
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©2009 Google – Imagery @2009 Teleatlas – Terms of Usage

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 Traffic data are a very good
example of such data.
 Different sensors observing
the same road may give
apparently inconsistent
information.
 Moreover, a single datum
coming from a sensor a
given moment may have
multiple possible meanings.
Coping with noisy, uncertainCoping with noisy, uncertain
and inconsistent dataand inconsistent data

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Coping with Data ScaleCoping with Data Scale
 The advent of Pervasive Computing and Web 2.0 technologies
led to a constantly growing amount of interconnected data
about urban environments
[source: http://senseable.mit.edu/nyte/]

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Usage Scenario of Alpha Urban LarKCUsage Scenario of Alpha Urban LarKC
 A user is in a (potentially unknown) city and would like to
organize a day/night of visiting some places, meeting friends,
attending a musical concert, etc.
 He needs to:
 Find interesting destinations:
 Monuments or relevant places in the city
 Events that take places in the city
 Understand the most suitable way to reach them
 To solve the problem today, the user would have to:
 use multiple applications, and
 manually pass intermediate results from a service to another
one

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Alpha Urban LarKC High Level ArchitectureAlpha Urban LarKC High Level Architecture
LarKC platform
Interface
Urban Computing Environment
SPARQL
query
SPARQL
result
REST
request
JSON
response
Request data Data
Pipelines
Config.
PROBLEM:
Which Milano
monuments or
events or friends
can I quickly get
to from here?
StreetsMonumentsEventsData & Index

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Alpha Urban LarKC demoAlpha Urban LarKC demo
 Demo publicly available at: http://seip.cefriel.it/alpha-Urban-LarKC/
 Explanatory video at: http://seip.cefriel.it/alpha-Urban-LarKC/alpha-
Urban-LarKC-demo.htm

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Much More to Come!Much More to Come!
Keep an eye on
http://wiki.larkc.eu/UrbanComputing

26. Urban Computing in LarKC
ITN – Infrastructure, Telematics and Navigation – Turin, October 15th
-16th
2009 - © CEFRIEL 2009
Thanks for your attention!
Irene Celino
email: irene.celino@cefriel.it
web: http://www.cefriel.it, http://swa.cefriel.it
Semantic Web Practice
CEFRIEL – ICT Institute – Politecnico di Milano