Long uglytestingdeck

Challenging the Internet of the
Future with Urban Computing
Lecturer:

Emanuele Della Valle
emanuele.dellavalle@cefriel.it
http://swa.cefriel.it
http://emanueledellavalle.org
Authors:

Emanuele Della Valle, Irene Celino, Kono Kim, Zhisheng Huang,
Volker Tresp, Werner Hauptmann, and Yi Huang

Cities are alive




Cities born, grow,
evolve like living
beings.
The state of a city
changes
continuously,
influenced by a lot of
factors,




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human ones: people
moving in the city or
extending it
natural ones:
precipitations or
climate changes

[source http://www.citysense.com]

For more information visit http://wiki.larkc.eu/UrbanComputing

Seven Framework Programme
Information Society Technologies (IST)
Specific Targeted Research Project

Urban Computing as a Way to Address them

[source IEEE Pervasive Computing,July-September 2007 (Vol. 6, No. 3)]
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Availability of Data




Some years ago, due to the lack of data, solving
Urban Computing problems with ICT 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 (please contribute), see



4

maps with the commercial activities and meeting places,
events scheduled in the city and their locations,
average speed in highways, but also normal streets
positions and speed of public transportation vehicles
parking availabilities in specific parking areas,
and so on.

OneSpace

http://wiki.larkc.eu/UrbanComputing/ShowUsABetterWay
http://wiki.larkc.eu/UrbanComputing/OtherDataSources


The LarKC project

c.eu !!
/ ww.lark u
::/www.larkc.e
Visit http /w
Visit http /
[Source: Fensel, D., van Harmelen, F.: Unifying reasoning and search to web scale. IEEE Internet Computing 11(2) (2007)]
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A Challenging Use Case 1/5
Actors:

Varese

Carlo: a citizen
living in Varese.
The day after, he
has to go to
Lombardy Region
premises in
Milano at 11.00.

UCS: a fictitious
Urban Computing
System of Milano
area
Ways to Milano
Private Car
FS railways
Le Nord railways


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Milano



Vision for Urban Computing

Mobility
Tourism

City Planning

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Culture



Thank you for paying attention

Any Questions?

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OneSpace



Insights – Analysis – Content Engineering

When Big Data and Predictive
Analytics Collide:
Visual Magic Happens


The Problem:
Massive data explosion (mobile, social,
wearable, cloud, m2m etc.) and brands are
struggling to make use of this data.



Predictive Analytics

Predictive Analytics enables decision makers
to predict future events and proactively act on that
insight to drive better business.


Predictive Analytics



Then, Now & Where We’re going



Most Common Predictive Models

• Clustering – finding groups and predicting themes
• Classification – most popular “Decision tree”
• Association – multi assurance connected buckets
• Link Analysis – relationships
• Text Mining – unstructured data to meaning
• Time Series – predicting a continuous value
• Graph Structure – structure predicts behavior



Where We’re Going – Pattern prediction



Where to go



KDD-Nuggets http://kdnuggets.com
RapidMiner http://rapid-i.com
R Statistical Computing http://www.r-project.org
Revolution Analytics http://www.revolutionanalytics.com
Teradata http://www.teradata.com
Tableau http://tableausoftware.com
Spotfire http://spotfire.tibco.com
SAS http://www.sas.com
IBM SPSS http://www.ib.com/software/analytics/spss
Mahout
https://cwiki.apahce.org/confluence/display/MAHOUT/Algoriths
Weka Open Source Data mining
http://www.cs.waikato.ac.nz/ml/weka
Pajek and (large) network analysis and visualization.
http://webdatacommons.org/hyperlinkgraph



 Tableau Demo
http://public.tableausoftware.com/views/Predictive

DataVisualizationwithSSASDataMining/Classificati
on#1



Content Marketing Flow = data



Visual Content Hub



We’re Here to Help You
Great
Social Engagement
Is About
Knowing what
drives engagement

@chasemcmichael sales@infinigraph.com
@infinigraph
http://smo.infinigraph.com
http://www.infinigraph.com
YouTube /infinigraph
Slideshare /infinigraph


Degree






The degree of vertex in an undirected graph is the
number of
edges incident to that vertex.
A vertex with degree one is called pendent vertex or
end
vertex.
A vertex with degree zero and hence has no incident
A
edges is
V1
called an isolated vertex.
B

Pendent vertex

Isolated vertex

In the undirected graph vertex v3 has the degree 3
And vertex v2 has the degree 2



Verifying Isomorphic graph

Graph B

Graph A

Vertices(A) :

a

b

c

d

e

Vertices(B):

q

p

r

s

t

Degree of
vertices:

2

3

3

3

1

Edges(A):

e1

e2

e3

e4

e5

e6

Edges(B):

e’1

e’4

e’3

e’2

e’5

e’6



Do you think that only one
specie can live in a habitat?
NO - many species can
live in the same habitat

What are species ?
Species are often defined as
a group of organisms capable
of interbreeding and
producing fertile offspring.



What is a population?
Group of organisms
of the same specie



C o m m u n i t y
It is a group of populations living together and
interacting with each other - sharing the same
food, places, shelter, water resources, etc, etc . . .
ReeF

Fores
t



> That is an Ecosystem <

YEAH
!


Limiting Factors


A factor or limiting resource is a factor that controls a process, such
as organism growth or species population, size or distribution. The
availability of food, predation pressure, hard temperatures or
availability of shelter are examples of factors that could be limiting
for an organism. An example of a limiting factor is sunlight, which is
crucial in rainforests.



Another example is rain, which can bust an ecosystem in two ways.
One way is rain can destroy an ecosystem is flood. Flooding can wash
away shelter, food, and even parts of the life-form's population itself.
The other way rain can destroy an ecosystem is drought. The main way
it can destroy an ecosystem is the depletion of food sources.



LIVING THINGS AND THE
ENVIRONMENT

In this unit we
will study the different rolls
and impact that the living
things have on the
environment. There will be a
strong focus in the
interaction that organisms
OBJECTIVE :



How is a cat similar and different from a
fish besides the physical appearance ?

Organisms that live in
different habitats

el “ Gato volador ”



What is an
Organism ?

It’s a Living thing that has (or can develop)
the ability to act or function independently



Where do organisms
live?

They live in their habitats

What is a
habitat?

It is the physical space that has all the
propped conditions for an organism to live,
and reproduce. It has to provide the
necessary food and water needed to
survive


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