IoTMeetupGuildford#4: CityPulse Project Overview - Sefki Kolozali, Daniel Puschmann, Payam Barnaghi...
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Transcript of IoTMeetupGuildford#4: CityPulse Project Overview - Sefki Kolozali, Daniel Puschmann, Payam Barnaghi...
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CityPulse: Large-scale data analytics for smart cities
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Sefki Kolozali, Daniel Puschmann, and Payam BarnaghiInstitute for Communication Systems (ICS)University of SurreyGuildford, United Kingdom
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Smart City Data
− Data is multi-modal and heterogeneous− Noisy and incomplete− Time and location dependent − Dynamic and varies in quality − Crowd sourced data can be unreliable − Requires (near-) real-time analysis− Privacy and security are important issues
− Data alone may not give a clear picture
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Smart City Data
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?
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What happens if we only focus on data
− Number of burgers consumed per day.− Number of cats outside.− Number of people checking their facebook
account.
− What insight would you draw?
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What type of problems we expect to solve
in “smart” cities
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Back to the future
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7Source LAT Times, http://documents.latimes.com/la-2013/
Future cities: a view from 1998
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8Source: http://robertluisrabello.com/denial/traffic-in-la/#gallery[default]/0/
Source: wikipedia
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The IoT and its applications
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IoT
Diffusion of innovation
image source: Wikipedia
The Most Hyped Technology
image source: Forbes via Gartner
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Moving fast forward
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Source: AdamKR via Flicker, http://www.flickr.com/photos/adamkr/5045295251/in/photostream/
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We need an Integrated Approach
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CityPulse Consortium
Industrial SIE (Austria,
Romania), ERIC
SME AI
HigherEducation
UNIS, NUIG,UASO, WSU
City BR, AA
Partners:
Duration: 36 months
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City of Aarhus, Denmark
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City of Brasov, Romania
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CityPulse – what we are going to deliver
.
.
.
Data Streams
Smart City Framework
Smart City Scenarios
a) Software tools/librariesin an integrated frameworkb) Back-end support servers
a)101 scenariosb)10 will be chosen to be prototyped
a) Data portals/ real-time access interfacesb) Interoperable formatsc) Common interfaces (REST/annotated)
a) Proof-of-Concepts and demonstrators and evaluations;Applications/Apps/Demos
Link: http://www.ict-citypulse.eu/page/content/smart-city-use-cases-and-requirements
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Stream Processing
.
.
.
Data Streams
CityPulse
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Data analytics framework
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Data:Data
Domain
Knowledge
Social
systems
InteractionsOpen Interfaces
Ambient
IntelligenceQuality and
Trust
Privacy and
Security
Open Data
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Use cases
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Scenario ranking
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101 Smart City Use-case Scenarios
http://www.ict-citypulse.eu/page/content/smart-city-use-cases-and-requirements
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101 Scenarios
− http://www.ict-citypulse.eu/page/content/smart-city-use-cases-and-requirements
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Data abstraction
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F. Ganz, P. Barnaghi, F. Carrez, "Information Abstraction for Heterogeneous Real World Internet Data", IEEE Sensors Journal, 2013.
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Ontology learning from real world data
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Adaptable and dynamic learning methods
http://kat.ee.surrey.ac.uk/
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Social media analysis (collaboration with Kno.e.sis, Wright State University)
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City Infrastructure
Tweets from a city
P. Anantharam, P. Barnaghi, K. Thirunarayan, A. Sheth, "Extracting city events from social streams,“, under review, 2014.
https://osf.io/b4q2t/
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In Conclusion
− Smart cities are complex social systems and no technological and data- analytics-driven solution alone can solve the problems.
− Combination of data from Physical, Cyber and Social sources can give more complete, complementary data and contributes to better analysis and insights.
− Intelligent processing methods should be adaptable and handle dynamic, multi-modal, heterogeneous and noisy and incomplete data.
− Effective visualisation and interaction methods are also key to develop successful solutions.
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Q&A
− Thank you.
− EU FP7 CityPulse Project:
http://www.ict-citypulse.eu/
@ictcitypulse
{s.kolozali, d.puschmann, p.barnaghi}@surrey.ac.uk