What makes smart cities “Smart”?

1

Payam BarnaghiInstitute for Communication Systems (ICS)/5G Innovation Centre University of SurreyGuildford, United Kingdom

November 5, Galway, Ireland

Desire for innovation

2Driverless Car of the Future (1957)

Image: Courtesy of http://paleofuture.com

“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

4P. 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.

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 1.3GHzand 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

Computing Power

6

−Smaller size−More Powerful−More memory and more storage

−"Moore's law" over the history of computing, the number of transistors in a dense integrated circuit has doubled approximately every two years.

Internet of Things: The story so far

RFID based solutions Wireless Sensor and

Actuator networks, solutions for

communication technologies,

energy efficiency, routing, …

Smart Devices/Web-enabled

Apps/Services, initial products,

vertical applications, early concepts and

demos, …

Motion sensor

Motion sensor

ECG sensor

Physical-Cyber-Social Systems, Linked-data,

semantics,More products, more

heterogeneity, solutions for control and

monitoring, …

Future: Cloud, Big (IoT) Data Analytics, Interoperability, Enhanced Cellular/Wireless

Com. for IoT, Real-world operational use-cases and

Industry and B2B services/applications,

more Standards… P. Barnaghi, A. Sheth, "Internet of Things: the story so far", IEEE IoT Newsletter, September

2014.

7

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]

8

Is this a good definition?

Cities of the future

9http://www.globalnerdy.com/2007/08/28/home-electronics-of-the-future-as-predicted-28-years-ago/

10Source: BBC News

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

What are smart cities?

12

“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.”

Source: Frost and Sullivan via http://raconteur.net/

What does makes smart cities “smart”?

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”?

How do cities get smarter?

How do cities get smarter?

17

Continuous (near-) real-time sensing/monitoringand data collection

Linked/integrated data and linked/integrated services

Real-time intelligence and actionable-informationfor different situations/services

Smart interaction and actuation

Creating awareness and effective participation

How can technology help to make cities smarter?

The role of data

19Source: 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

20

“Each single data item can be important.”

“Relying merely on data from sources that are unevenly distributed, without considering background information or social context, can lead to imbalanced interpretations and decisions.”?

Smart city data

21

Data- Challenges

− Multi-modal and heterogeneous− Noisy and incomplete− Time and location dependent − Dynamic and varies in quality − Crowed sourced data can be unreliable − Requires (near-) real-time analysis− Privacy and security are important issues− Data can be biased- we need to know our data!

22

Smart data collection

− Smart data collection

− Intelligent data pProcessing (selective attention and information-extraction)

− Region Beta Paradox

23

(image source: KRISTEN NICOLE, siliconangle.com)

24

“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.

25

“Data will come from various source and from different platforms and various systems.”

This requires an ecosystem of IoT systems with several backend support components (e.g. pub/sub, storage, discovery, and access services). Semantic interoperability is also a key requirement.

Device/Data interoperability

26The slide adapted from the IoT talk given by Jan Holler of Ericsson at IoT Week 2015 in Lisbon.

IoT environments are usually dynamic and (near-) real-time

27

Off-line Data analytics

Data analytics in dynamic environments

Image sources: ABC Australia and 2dolphins.com

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

29Source LAT Times, http://documents.latimes.com/la-2013/

A smart City exampleFuture cities: A view from 1998

30Source: http://robertluisrabello.com/denial/traffic-in-la/#gallery[default]/0/

Source: wikipedia

Back to the Future: 2013

Common problems

31

Guildford, Surrey

32

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…

33

EU FP7 CityPulse Project

34

Big (IoT) Data Analytics

...

Real World Data

Smart City Framework

Smart City Scenarios

Designing for real world problems

101 Smart City scenarios

37http://www.ict-citypulse.eu/scenarios/

Dr Mirko PresserAlexandra Institute Denmark

38

Data Visualisation

39

Event Visualisation

CityPulse demo

40

Creating Patterns- Adaptive sensor SAX

41F. Ganz, P. Barnaghi, F. Carrez, "Information Abstraction for Heterogeneous Real World Internet Data”, IEEE Sensors Journal, 2013.

Data abstraction

42F. Ganz, P. Barnaghi, F. Carrez, "Information Abstraction for Heterogeneous Real World Internet Data", IEEE Sensors Journal, 2013.

Adaptable and dynamic learning methods

http://kat.ee.surrey.ac.uk/

44

https://github.com/UniSurreyIoT/KAT

Website: http://kat.ee.surrey.ac.uk

Real world data

45

Analysing social streams

46With

City event extraction from social streams

47

Tweets from a city POS Tagging

Hybrid NER+ Event term extraction

Geohashing

Temporal Estimation

Impact Assessment

Event Aggregatio

nOSM

LocationsSCRIBE

ontology

511.org hierarchy

City Event ExtractionCity Event Annotation

P. Anantharam, P. Barnaghi, K. Thirunarayan, A.P. Sheth, "Extracting City Traffic Events from Social Streams", ACM Trans. on Intelligent Systems and Technology, 2015.

Collaboration with Kno.e.sis, Wright State University

Geohashing

48

0.6 miles

Max-lat

Min-lat

Min-long

Max-long

0.38 miles

37.7545166015625, -122.40966796875

37.7490234375, -122.40966796875

37.7545166015625, -122.420654296875

37.7490234375, -122.420654296875

437.74933, -122.4106711

Hierarchical spatial structure of geohash for representing locations with variable precision.

Here the location string is 5H34

0 1 2 3 4 5 67 8 9 B C D EF G H I J K L

0 172 3 4

5 6 8 9

0 1 2 3 4

5 6 7

0 1 23 4 5

6 7 8

Social media analysis

49

City Infrastructure

Tweets from a city

P. Anantharam, P. Barnaghi, K. Thirunarayan, A. Sheth, "Extracting city events from social streams,“, ACM Transactions on TICS, 2014.

Social media analysis (deep learning – under construction)

50

http://iot.ee.surrey.ac.uk/citypulse-social/

Accumulated and connected knowledge?

51Image courtesy: IEEE Spectrum

Reference Datasets

52http://iot.ee.surrey.ac.uk:8080/datasets.html

Importance of Complementary Data

53

Users in control or losing control?

54

Image source: Julian Walker, Flicker

Avoiding failures

55Source: IEEE Spectrum, Lessons From a Decade of IT Failures

Things to avoid: Over-complexifying, Under-delivering

56Source: IEEE Spectrum, Lessons From a Decade of IT Failures

Data Analytics solutions for smart cities

− Great opportunities and many applications;− Enhanced and (near-) real-time insights;− Supporting more automated decision making and

in-depth analysis of events and occurrences by combining various sources of data;

− Providing more and better information to citizens;− …

57

However…

− We need to know our data and its context (density, quality, reliability, …)

− Open Data (there needs to be more real-time data)

− Complementary data − Citizens in control − Transparency and data management issues

(privacy, security, trust, …)− Reliability and dependability of the systems

58

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. 59

IET sector briefing report

60

Available at: http://www.theiet.org/sectors/built-environment/resources/digital-technology.cfm

CityPulse stakeholder report

61http://www.ict-citypulse.eu/page/sites/default/files/citypulse_annual_report.pdf

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

62

Thank you

http://personal.ee.surrey.ac.uk/Personal/P.Barnaghi/

@pbarnaghi

p.barnaghi@surrey.ac.uk

Acknowledgement: CityPulse Consortium http://www.ict-citypulse.eu