Dr. Payam Barnaghi discusses how cities can become smarter through the use of digital technologies and data. He defines a smart city as one that uses information and communication technologies to improve services, reduce costs and engage citizens. Barnaghi explains that smart cities are made possible by collecting data from sensors, integrating and analyzing that data, and using the insights to provide real-time information and automated services. He provides examples of applications including traffic management, power usage prediction, and healthcare monitoring. Barnaghi emphasizes that technology alone does not make a city smart and that open data, interoperability, and informed citizen participation are also important.

1. How to make cities “smarter”?
1
Dr Payam Barnaghi
Institute for Communication Systems (ICS)/
5G Innovation Centre
University of Surrey
Guildford, United Kingdom
UKTI Workshop at Mobile World Congress 2016

2. “A hundred years hence people will be so
avid of every moment of life, life will be so
full of busy delight, that time-saving
inventions will be at a huge premium…”
“…It is not because we shall be hurried in
nerve-shattering anxiety, but because we
shall value at its true worth the refining and
restful influence of leisure, that we shall be
impatient of the minor tasks of every day….”
The March 26, 1906, New Zealand Star :
Source: http://paleofuture.com

3. 3P. Barnaghi et al., "Digital Technology Adoption in the Smart Built Environment", IET Sector Technical Briefing, The Institution of Engineering and Technology
(IET), I. Borthwick (editor), March 2015.

4. Apollo 11 Command Module (1965) had
64 kilobytes of memory
operated at 0.043MHz.
An iPhone 5s has a CPU running at speeds
of up to 1.3GHz
and has 512MB to 1GB of memory
Cray-1 (1975) produced 80 million Floating
point operations per second (FLOPS)
10 years later, Cray-2 produced 1.9G FLOPS
An iPhone 5s produces 76.8 GFLOPS – nearly
a thousand times more
Cray-2 used 200-kilowatt power
Source: Nick T., PhoneArena.com, 2014
image source: http://blog.opower.com/

5. Smart City
“A smart city uses digital technologies or information and
communication technologies (ICT) to enhance quality and
performance of urban services, to reduce costs and resource
consumption, and to engage more effectively and actively with
its citizens.” [Wikipedia]
5
Is this a good definition?

6. Cities of the future
6
http://www.globalnerdy.com/2007/08/28/home-electronics-of-the-future-as-predicted-28-years-ago/

7. 7
Source: BBC News

8. Source: The dailymail, http://helenography.net/, http://edwud.com/

9. What are smart cities?
9
“An ecosystem of systems enabled by the
Internet of Things and information
communication technologies.”
“People, resources, and information coming
together, operating in an ad-hoc and/or
coordinated way to improve city operations
and everyday activities.”

10. What does makes smart cities “smart”?

11. Smart Citizens (more informed and more in control)
Smart Governance (better services and informed decisions)
Smart Environment
Providing more equality and wider reach
Context-aware and situation-aware services
Cost efficacy and supporting innovation
What does makes smart cities “smart”?

12. How do cities get smarter?

13. How do cities get smarter?
13
Continuous (near-) real-time sensing/monitoring
and data collection
Linked/integrated data
and linked/integrated services
Real-time intelligence and actionable-information
for different situations/services
Smart interaction and actuation
Creating awareness and effective participation

14. How can technology help to make
cities smarter?

15. The role of data
15
Source: The IET Technical Report, Digital Technology Adoption in the Smart Built Environment: Challenges and opportunities of
data driven systems for building, community and city-scale applications,
http://www.theiet.org/sectors/built-environment/resources/digital-technology.cfm

16. 16
“The ultimate goal is transforming the raw data
to insights and actionable information and/or
creating effective representation forms for
machines and also human users, and providing
automated services.”
This usually requires data from multiple sources,
(near-) real time analytics and visualisation
and/or semantic representations.

17. What type of problems we expect to solve
using the IoT and data analytics solutions?

18. 18Source LAT Times, http://documents.latimes.com/la-2013/
A smart City example
Future cities: A view from 1998

19. 19
Source: http://robertluisrabello.com/denial/traffic-in-la/#gallery[default]/0/
Source: wikipedia
Back to the Future: 2013

20. Common problems
20
Guildford, Surrey

21. 21

22. Applications and potentials
− 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…
22

23. EU FP7 CityPulse Project
23

24. Designing for real world problems

25. 101 Smart City scenarios
25http://www.ict-citypulse.eu/scenarios/
Dr Mirko Presser
Alexandra Institute
Denmark

26. 26
Event Visualisation

27. CityPulse demo
27

28. Real world data
28

29. Extracting traffic events from social media
29In collaboration with Wright State University

30. Extracting city events
30
City Infrastructure
Yes it is police @hasselager
… there directing traffic
CRF-
based
NER
Tagging Multi-view
Event
Extraction
Loc. Est. =
“hasselager,
aarhus”
Loc. Est. =
“hasselager,
aarhus”
Temp. Est. =
“2015-2-19
21:07:17”
Temp. Est. =
“2015-2-19
21:07:17”
Level = 2Level = 2
Event = TrafficEvent = Traffic
OSM
Loc.
OSM
Loc.
CrimeCrimeTransp.Transp.
City Event Extraction
CNN
POS+NER
Event term
extraction
CulturalCultural SocialSocial Enviro.Enviro. SportSport HealthHealth
DataData
Transp.Transp.
Yes <O> it <O> is <O> police <B-CRIME>
@hasselager <B-LOCATION>… <O> there <O>
directing <O> traffic <B-TRAFFIC>
Yes <S-NP/O> it <S-NP/O> is <S-VP/O> police
<S-NP/O> @hasselager <S-LOC> ... <O/O> there
<S-NP/O> directing <S-VP/O> traffic <S-NP/O>
Nazli FarajiDavar, Payam Barnaghi, "A Deep Multi-View Learning Framework for City Event Extraction from Twitter Data Streams", submitted to ACM Transactions
on Intelligent Systems and Technology (TIST), Nov. 2015.

31. Extracting city events
31
http://iot.ee.surrey.ac.uk/citypulse-social/
Nazli FarajiDavar, Payam Barnaghi, "A Deep Multi-View Learning Framework for City Event Extraction from Twitter Data Streams", submitted to ACM
Transactions on Intelligent Systems and Technology (TIST), Nov. 2015.

32. Accumulated and connected knowledge?
32
Image courtesy: IEEE Spectrum

33. Users in control or losing control?
33
Image source: Julian Walker, Flicker

34. Gateway
Gatewa
y
Data Analytics
Engine
IoT Test Bed Cloud
External NHS, GP IT systems
Possible links to
Other Test Beds
HyperCat
Gateway
HyperCat
HyperCat
HyperCat
Data-driven and patient
centered Healthcare
Applications
NHS - IoT Test-bed for healthcare

35. In conclusion
−Smart cities are made of informed citizens, smart
environments and informed and intelligent decision
making and governance.
−Smart cities should promote innovation, equality and
wider reach of services to all citizens.
−IoT plays a key role in making cities smarter;
openness of data and interconnection and
interoperability between different data sources and
services is a key requirement.
−Technology alone won’t make cities smart.
35

36. IET sector briefing report
36
Available at: http://www.theiet.org/sectors/built-environment/resources/digital-technology.cfm

37. 37
Useful information:
http://www.raeng.org.uk/publications/reports/connecting-data-driving-productivity

38. Other challenges and topics that I didn't talk about
Security
Privacy
Trust, resilience and
reliability
Noise and
incomplete data
Cloud and
distributed computing
Networks, test-beds and
mobility
Mobile computing
Applications and use-case
scenarios
38

39. Q&A
− Thank you.
http://personal.ee.surrey.ac.uk/Personal/P.Barnaghi/
@pbarnaghi
p.barnaghi@surrey.ac.uk
http://iot.ee.surrey.ac.uk
Acknowledgement: CityPulse Consortium
http://www.ict-citypulse.eu