internet of things and data analytics for smart cities

Post on 27-Jun-2015

424 Views

Category:

Documents

3 Downloads

Preview:

Click to see full reader

DESCRIPTION

Invited talk, Internet of Things and Data Analytics for Smart Cities, 12th European Week of Regions and Cities, 6-9 October 2014, Brussels.

TRANSCRIPT

Internet of Things and Data Analytics for Smart Cities

1

Payam Barnaghi

Institute for Communication Systems (ICS)

University of Surrey

Guildford, United Kingdom

2

CityPulse: Large-scale data analytics for smart cities

What type of problems we expect to solve in

“smart” cities

4Source LAT Times, http://documents.latimes.com/la-2013/

Future cities: A view from 1998

5

Source: http://robertluisrabello.com/denial/traffic-in-la/#gallery[default]/0/

Source: wikipedia

Smart City Data Analysis

− Analysis of thousands of traffic, pollution, weather, congestion, public transport, waste and event sensory data to provide better transport and city management.

− Converting smart meter readings to information that can help prediction and balance of power consumption in a city.

− Monitoring elderly homes, personal and public healthcare applications.

− Event and incident analysis and prediction using (near) real-time data collected by citizen and device sensors.

− Turning social media data (e.g. Tweets) related to city issues into event and sentiment analysis.

− Any many more…

6

Designing for City Problems

101 Smart City Use-case Scenarios

http://www.ict-citypulse.eu/page/content/smart-city-use-cases-and-requirements

Big (IoT) Data Analytics

.

.

.

Real World Data

Smart City Framework

Smart City Scenarios

Data Processing and Information Extraction

Analysis of traffic data in City of AarhusAnalysis of traffic data in City of Aarhus

University of Surrey Smart Campus data analysisUniversity of Surrey Smart Campus data analysis

Twitter data analysis for detecting city eventsTwitter data analysis for detecting city events

In Conclusion

− Combining 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 able to handle dynamic, multi-modal, heterogeneous and noisy and incomplete data.

− Smart cities are complex social systems and no technological and data- analytics-driven solution alone can solve the problems.

11

− Thank you.

− EU FP7 CityPulse Project:

http://www.ict-citypulse.eu/

@pbarnaghi

p.barnaghi@surrey.ac.uk

top related