Joint Work with Emanuele Della Valle
emanuele.dellavalle@polimi.it.
Presentation of the results of the Urban Computing use case of the LarKC project. Speech at the ITN Expo event (http://www.itnexpo.it/) on October 16th, 2009.
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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
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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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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
It was too much text (original below)
It means the systems allow for multiple reasoning paradigms; e.g.
precise and consistent inference for telling that at a given junction all vehicles, but public transportation ones, must go straight
approximate reasoning when calculating the probability of a traffic jam given the current traffic conditions and the past history.
I dropped the second level sentence which was:
While for the an entire city we cannot assume complete knowledge, for a time table of a bus station we can
Change the first image with something else???
I dropped the second level sentence which was:
A square with several station for buses and subway can be considered a unique point for multimodal travel planning, but not when the problem is giving direction in that square to a pedestrian
I completely changed the text which was:
Periodically changing data change according to a temporal law that can be
Pure periodic law, e.g. every night at 10pm Milano overpasses close.
Probabilistic law, e.g. traffic jam appear in the west side of Milano due to bad weather or when San Siro stadium hosts a soccer match.
Event driven changing data are updated as a consequence of some external event. They can be further characterized by the mean time between changes:
Slow, e.g. roads closed for scheduled works
Medium, e.g. roads closed for accidents or congestion due to traffic
Fast, e.g. the intensity of traffic for each street in a city
Change the image with something else???
I changed the text which was:
Although we encounter large scale data which are not manageable, it does not necessary mean that we have to deal with all of the data simultaneously.
Usually, only very limited amount data are relevant for a single query/processing at a specific application.