Intelligent cities theoretical and applied research at URENIO

1. Nicos Komninos
URENIO Research, Aristotle University of Thessaloniki
Intelligent Cities: A new planning paradigm
15 years research at URENIO

2. 3. Applied Research at URENIO: Developing solutions for intel cities
2. Theoretical Research at URENIO: Models for intelligent cities
1. Introduction: Intelligent/smart cities as a new planning paradigm

3. Intelligent / smart cities: A new topic – a rising literature (2001-2015)
Data source: Google Scholar (05/03/2016) patents and citations not included

4. Intelligent / smart cities literature: turning point 2010
0
5.000
10.000
15.000
20.000
25.000
30.000
35.000
40.000
45.000
50.000
"Intelligent city" "Intelligent cities" "Smart city"
"Smart cities" Total

5. Genesis of the need for intelligent cities
URBANISATION
The smart city as a geographical space able to manage
resources and waste of rising urban population in a
sustainable way
The contemporary urban economy and society
has become knowledge-based and
innovation-led: Knowledge cities,
innovation cities, innovating cities, creative
cities. R&D, knowledge and innovation are
main drivers of city’s development. City
governance and planning are moving
towards public-private partnerships and
triple-helix alliances.
INNOVATION –LED URBAN DEVELOPMENT

6. Genesis of conditions for the creation of ICs
CONNECTED INTELLIGENCE
A new spatiality / layer (digital / intelligence)
has been added on the urban
agglomeration, activities, infrastructures,
regulation and planning. It is composed of
broadband networks, user interfaces,
content applications, and e-services. All
these artcrafts create un umbrella of
communication and cooperation over the
cities, locally and globally.
DIGITAL SPACE

7. IC: A new planning paradigm. In the log run, a new urban reality

8. 2. Theoretical Research at URENIO: Models for intelligent cities

9. 1. Evolution of systems of innovation and
rise of intelligent cities
2. Structure: City-Innovation-Digital layers
3. Functioning of ICs: Innovation circuits C1
(digital), C2 (decision), C3 (behaviour)
4. Knowledge functions on physical,
institutional, digital spaces
5. Models of spatial intelligence:
agglomeration of apps, orchestration,
empowerment, instrumentation)
6. Strategic planning. A roadmap of 3
stages and 7 step
7. Governance: Actors – Architectures of
intelligence – Activities & innovation-for-all
8. Typology of strategies
9. Ontology of intelligent city /
ontologies of smart city apps
10. Design and development of smart
city applications
11. Measurement and benchmarking for
IC performance
12. Challenges / problems to solve:
o Smart cities - smart growth
o Employment and start-ups
o Safety and security in the city
o Environment, climate change, zero
emissions
1.1. Intelligent / smart cities: theoretical research on IC models

10. MIT Smart Cities Group: “The new intelligence of cities, resides in the increasingly effective combination of
digital telecommunication networks (the nerves), ubiquitously embedded intelligence (the brains), sensors
and tags (the sensory organs), and software (the knowledge and cognitive competence)”.
URENIO Research: “The term ‘intelligent city’ describes a territory (community, district, cluster, city, and
city-region) with four main characteristics: (1) a creative population and developed knowledge-intensive
activities, (2) embedded institutions and routines for knowledge creation (3) a developed broadband
infrastructure, digital spaces, e-services, and online knowledge management tools; and (4) a proven ability
to innovate”.
European Smart Cities: “A Smart City is a city well performing in 6 characteristics, built on the ‘smart’
combination of endowments and activities of self-decisive, independent and aware citizens: (1) Smart
economy (competitiveness), (2) Smart people (social and human capital), (3) Smart governance
(participation), (4) Smart mobility (transport and ICT), (5) Smart environments (natural resources), and (6)
Smart living (quality of life)”
IBM Smart Planet Initiative: "A smarter city is one that uses technology to transform its core systems and
optimise the return from largely finite resources. By using resources in a smarter way, it will also boost
innovation, a key factor underpinning competitiveness and economic growth”.
1.1. Intelligent cities: Multiple definitions, but convergence in concept

11. Source: Wordle visualisation
1.1. Intelligent cities: Multiple definitions, but convergence in concept

12. Cloud Core
Smart City Apps
Valladolid
Agueda
Manchester
Thessaloniki
X Smart
Mirror
X Smart
Mirror
X Smart
Mirror
X Smart
Mirror
Cluster
District
Infra
All
All
Gov
Living
Perimeter
REGIONAL SYSTEM OF
INNOVATION
Innovation Financing
Banks, Business Angels,
Venture Capital, Regional
Incentives
Technology Transfer
Organisations
Tech Parks, Tech Networks,
Brokers, Consultants
Universities /
Research
Institutes
Public R&D
Laboratories
Private R&D
and Training
Centres
Technology Information System
Patents, Standards, Technical
Publications, Emerging Markets,
Foresight
CLUSTERS
Group of companies in co-
operation
Vertical / Horizontal
Industry
clustersand
sectors
Housing Districts
University
Science Parks
and Incubators
Transport
hubs
CBDPort district
City and Districts
Digital space – smart technologies level
Knowledge and innovation level
People, activities, infrastructure level
N S C A
S N P O
P A I
1.2. Structure: Three building blocks, evolutionary process

13. 1.2. Structure: (1) The urban space layer
Industry
clusters and
sectors
Housing Districts
University
Science Parks
and Incubators
Transport
hubs
CBD
City and Districts
Port
The city of users and practices
People
Practices that take place in cities
Agglomeration and clusters
 City districts and neighbourhoods
The form of the city / buildings becomes
background for augmented reality applications

14. Technologytransfer Reverseengineering R&D based NPD
Networking achitectures
Company
(ies)
Suplie
rs
Suplie
rs
Suplie
rs
Suplie
rs
Government
Regional policy; Strategic
planning; Business
associations; Stakeholders
Financing
Banks, Business Angels,
Venture Capital, Regional
Incentives, Crowdfunding
Technology and Information
Intermediaries
•Technology transfer agencies;
Consultancy; Tech Networks;
Patents; Standards; Market watch
Public R&D
Private R&D
Custo
mers
Custo
mers
Users
University
R&D
Business
sectors
Business
clusters
1.2. Structure: (2) The innovation space layer
CLOUD
INTERNETOFTHINGS
QR CODES –
AUGMENTEDREALITY
User-driven in smart environments
User-driven innovation and glocal collaboration
Evolution towards open, user-driven systems
Innovation networks merge with Internet networks
 Cyber-physical systems of innovation

15. 15
1.2. Structure: (3) Digital space layer
The digital space of
Broadband networks and access
Web / data technologies
Software applications
E-services

16. City’s digital spaces and
smartenvironments
Broadband, sensors, digital
skills, data, software
applications, e-services
City’s innovationsystem
Changing the city’s routines
Policy and city planning
Private and public investment
User-driven, bottom-up innovation
Institutions for innovation
City
A system of systems
Routines within subsystems
Needs, requests, problems Innovation circuit 1
Innovation circuit 3
Innovation circuit 2
Subsystem production
Subsystem living
Subsystem transport / utilities
Subsystem governance
1.3. Operation

17. Digital City Kyoto – 3D representation
Digital Corfu - Panoramic Taipei Street View – 3D scanning
1.3. Operation: Creation of representation intelligence (mirror cities)

18. Stockholm,Stokab
Manchester, East Serve district
Singapore, Intelligent Nation 2015
Housing
Mobility
Health
Helsinki
1.3. Operation: Creation of collective intelligence (web 2.0 cities)

19. 1.3. Operation: Creation of instrumentation intelligence (smart cities)

20. Intelligent Cities trilogy: Routledge 2002, 2008, 2014
Publications: Intelligent cities as ecosystems of innovation
Intelligent Clusters,
Communities and Cities:
Enhancing Innovation with
Virtual Environments and
Embedded Systems (2009)
Smart Applications for
Smart Cities: New
Approaches to Innovation
(2012)
Smart Cities and the Future
Internet in Europe
(2013)
Smart Cities and Cloud
Computing
(2016)
Special issues in academic journals

21. 3. Applied Research at URENIO: Developing solutions for intel cities

22. Software applications
Applied research at URENIO
Cyber-physical systems of innovation
Strategic planning for IC

23. http://apps4bcn.cat/en/
http://mashable.com/2012/12/26/urban-tech-wish-
list/?utm_source=feedburner&utm_medium=feed&utm_
campaign=Feed%3A+Mashable+%28Mashable%29
3.1. Software applications: Solutions every city should have
Innovation economy
• Investment and entrepreneurship
• Creativity, research, and innovation
• Work and labour markets
• Products and services markets
• Collaboration, clusters, districts
City infrastructure and utilities
• Mobility, transport and parking
• Energy saving, smart grid, RES
• Water management and saving
• Waste collection / reuse
• Broadband, wired and wireless
Living in the city – quality of life
• Housing
• Health and social care
• Education
• Recreation and sports
• Environment, safety and security
City governance
• Decision making / e-democracy
• Government services to citizens
• City planning / city management
• Monitoring and benchmarking
Innovation-for-all
user driven innovation / global
innovation networks
Tech : Big data / distributed
cognition / adaptive spaces
Safety into the city
Tech: Real time alert and
response / biometric
authentication
Open governance:
transparency, accountability
Tech: Open data / semantic web
Saving resources and
infrastructure
Tech: Sensor networks, smart
meters, smart grid, forecasting

24. 3.1. Software applications: A portfolio of open source applications

25. 3.1. Software applications: Innovation-led development
SMART MARKETPLACE
Aggregation of commercial shops
located in an area. Subsystems:
business directory, virtual
marketplace with e-shops, coupon
site of promotional codes, review
engine.
TECHNOLOGY OFFER
Repository of technologies.
Valorisation space for
technical, IPR, market and
funding issues. Agreement
Space for negotiation
CITY BRANDING
Points of Interest (POIs) in a city.
Monuments, streets, squares,
historical sites, recreation
facilities. POIs connected to offer
of goods and services
LIVING LAB SPACE
The LL application enables
user-driven innovation and
collaboration in the
development and
commercialisation of new
products and services
CROWD-FUNDING
Alternative investments offered to
specific goals, such as urban
renewal, social entrepreneurship,
NGOs actions, activism, social care
in the city

26. 3.1. Software applications: Transparent governance
IMPROVE MY CITY
The application gathers citizens requests, complaints and suggestions and administer the
response of authorities to reporting of non-emergency issues at any domain of the city life:
environment, mobility, safety, crime, public space, buildings and monuments, and other. ImC
allows citizens to report issues from their home using the web version, or while on the
street using the mobile app (iOS & Android). Users may add comments, suggest solutions for
improving the environment of their neighbourhood or add video and photos
PERFORMANCE BENCHMARKING
The Benchmarking application enables the comparative assessment of energy or other
resources use in public buildings. A deeper understanding is achieved through carefully
chosen indicators and metrics that allow for observing how features and properties are
distributed into a population of reference and which is the relative position of an entity into
this population.
VISUALISATION of ADMINISTRATION DATA
This application enables the visualisation of key indicators and variables included in a
dataset (budget, resources, capabilities, infrastructure, etc.). The application consists of five
components, which offer the possibility to visualize main properties of the dataset: bar
charts and pie charts that show trends and distributions; scatter-plots that reveal
correlations between indicators; a node map which plots relationships among entities of the
dataset; and a word cloud for the visual representation of content and text data.:

27. PEOPLE Smart City project, FP7, CIP-ICT-PSPPEOPLE Smart City project, FP7, CIP-ICT-PSP

28. Technology Park University of Bremen, GE City of Thermi, Thessaloniki, GR
Vitry-sur-Seine, Paris, FR Abando District, Bilbao, ES
PEOPLE: FOUR PILOTS
Thermi City Center

29. STORM CLOUDS project, FP7, CIP-ICT-PSP : Open source and cloud computing
Core
Smart City Apps
Valladolid
Agueda
Manchester
Thessaloniki
X Smart
Mirror
X Smart
Mirror
X Smart
Mirror
X Smart
Mirror
Cluster
District
Infra
All
All
Gov
Living
Perimeter

30. Source: https://www.readwriteweb.com/
cloud/2011/04/the-cloud-stratosphere-infogra.php
Cost reduction
 High fluctuation of demand
 Cloud-based economies
Zero entry cost
Scalability of costs
Pay-per-use
Costs corresponding to usage
and revenues
Quality of service increase
No need of apps installation
Central update of versions
User empowerment
Instant scalability
Security against cyber threats
and cyber crime
Trust, accountability,
transparency. Reliability of
complex infrastructure
Analytics and benchmarking
Disruptive business models:
improved quality of service at
low cost
STORM CLOUDS project: Combining open source and cloud computing

31. The city as agglomeration of
applications over districts & nets
CBD / historic center
Industrial districts
Technology districts
University campus
Transport hubs
Port area
Transportation networks
Energy networks
Broadband networks
3.2. Behind the applications: Strategic planning for intelligent cities

32. City / Community Innovation ecosystem Digital space - apps
DISTRICT of REFERENCE
Social, physical
space and
infrastructure
Activities /
production
system
Social groups,
cluster reference
Human
cooperation
networks
 Problems to solve
KNOWLEDGE PROCESSES
Intelligence
information: collecting
and distributing
information
Acquisition /
assimilation
technology
Development of new
services / products.
Optimizing existing
processes.
Dissemination of
information,
promotion services
Operated by a regional
back-office
Software platform
Data integration model
Foresight
Regional statistics
Regional performance
Sector performance
Market watch
R&D watch
TargetGroups
Information portal, reporting,
alert, newsletter
Company audits
Authors Integrator Users
Feed back
+
+
3.2. Strategic planning for intelligent cities: How the layers get connected

33. 3.2. Strategic planning for intelligent cities: A roadmap
1. The city: Physical and
social characteristics,
metrics, and challenges
2. The innovation
ecosystem: Top-down /
bottom-up change drivers
3. The digital space:
Technologies and solutions
for smart environments
Baseline conditions Strategy Development Implementation
4. Layers integration &
spatial intelligence
Knowledge functions at
physical – institutional -
digital spaces
Collective intelligence
Technology learning
Collaborative Innovation
Dissemination
5. IT solutions and e-
services development for
each district.
6. Business models for
sustainability of e-services
7. Measurement index:
Documentation of impact,
innovation, intelligence
Start of process
Multiple input
Subroutine
Subroutine
And /Or
Junction
Outcome / Export
End of cycle

34. 3.2. FIREBALL project – FP 7 programme, FIRE
A series of case
studies and white
papers on smart city
strategies and the
role of future
Internet
technologies
Connecting smart
cities – Living labs –
Future Internet
technologies
Creating a network
among these
communities

35. 3.2. Intelligent Thessaloniki: (1) district focused, and (2) sector focused
In each district. Focus on the community / innovation ecosystem of the district
Development of high speed broadband network: wired and wireless
Free internet users and businesses
Intelligent environment applications: resource saving and optimization
New e-services: digital markets, market intelligence, acquire technology, new
product development, promotion and marketing
User and business training to create, give content, and use applications

36. “There are many diverse players who make the city: Business people,
residents, commuters, elected officials, among others, that make millions of
decisions each day which add up to the evolving form, structure, and
character of cities.
These decisions are largely beyond the reach of any formal urban policy or
plan, much less of any top down regulatory strategy. Many agents in such a
system produce a self organizing strategy that effectively deals with a
complex and `out of control’ environment.
Complexity theory shows how a distributed network of agents can produce
outcomes that are coordinated and demonstrate intelligence collectively
than individually.”
Innes, J. and Booher, D. (2000) Indicators for Sustainable Communities: A Strategy Building on Complexity Theory and
Distributed Intelligence, Planning Theory & Practice, 1:2, 173-186,
3.2. Intelligent city strategy: Distributed intelligence into heterogeneous systems

37. 3.3. Going deeper into the drivers of intelligence: Smart systems of innovation
“I think of intelligence as the high-end
scenery of neurophysiology -the
outcome of many aspects of an
individual’s brain organization which
bears on doing something one has
never done before….
I like Jean Piaget’s emphasis that
intelligence is what you use when you
don’t know what to do.
This captures the element of novelty, the
coping and groping ability needed
when there is no ‘right’ answer, when
business as usual isn’t likely to suffice”.
Calvin, W. H. (1998) How Brains Think. Evolving
Intelligence, Then and Now, London: Phoenix.

38. BAHsurvey2013:
Theglobalinnovation1000.Navigatingthedigitalfuture
3.3. Smart environments for innovation

39. CROWD-R&D
CROWD-FUNDING
CROWD-DATA
CROWD-IDEAS
LANDSCAPE
Co-design paradigm
Open R&D / open
science
Collaborative ideas
generation
Collaborative new
product design
Platform-based
innovation
Crowdsourcing R&D,
data, skills, funds
3.3. Crowdsourcing platforms for innovation

40. Product design and development
Observing users into city
environments
Experimenting with users into LLs
Gaming
3.3. Living Labs (living urban laboratories) for innovation

41. Crowdfunding
Bus. Angel networks
Business planning tools
Online
R&D
networks
e-commerce
Analytics
Socialmedia
E-tech brokers
Onlinelearning
Patentdatabases
Virtual
clusters
Producers
e-suppliers
Suplie
rs
Suplie
rs
Suplie
rs
Government
Regional policy; Strategic
planning; Business
associations; Regional
stakeholders
Funding
Banks, Business Angels,
Venture Capital, Regional
Incentives
Technology and Information
Intermediaries
•Technology transfer agencies;
Consultancy; Tech Networks;
Patents; Standards; Market watch
Public R&D
PrivateR&D
Custo
mers
Users
University
R&D
Business
sectors
Business
clusters
Virtualnetworks
Benchmarking
NPD stage-gate
3.3. Creation of cyber-physical systems of innovation
City’s digital spaces and
smartenvironments
Broadband, sensors, digital
skills, data, software
applications, e-services
City’s innovationsystem
Changing the city’s routines
Policy and city planning
Private and public investment
User-driven, bottom-up innovation
Institutions for innovation
City
A system of systems
Routines within subsystems
Needs, requests, problems Innovation circuit 1
Innovation circuit 3
Innovation circuit 2
Subsystem production
Subsystem living
Subsystem transport / utilities
Subsystem governance

42. 3.3. INTERVALUE project, SEE: Digital platform & practices for R&D valorisation
GATE 1 GATE 2 GATE 3
Institutional: Deliver a detailed
valorisation plan
Facilitation by technology advisers
Cover 100% of results
Funding marketing costs
Selection by virtual markets
Cooperation with VC / Business
angel community
Online dissemination
Specialised services from R&D to
product development
IPR policy
Legal advice
Co-funding / early stage funding

43. 3.3. ONLINE S3 PROJECT: Horizon 2020, Online platform for smart specialisation
S3Applicaons
S3BigDataAnaysis&Broker
-Userauthencaon
S3DataAcquision&
Provisioning
Machine
Learning
SQL&Non
SQL queries
Social Data
Aggregator
Edge Data
Collec on
The World
Overall picture of the S3 pla orm
Develop an e-policy platform, augmented with a toolbox of
applications and online services, able to assist national and
regional authorities in the EU to elaborate their smart
specialisation agenda.
Offer guidance on implementing the strategies notably in
terms of methods for delivery through innovation platforms
and ‘multi-actor measures’ and should integrate online
evaluation and monitoring tools that enable an enhanced
‘real-time’ tracking of policy effectiveness
0
1
2
3
4
5
Driving economic changethrough smartspecialisation/RIS3
Informal assessment - region XXXΣ

44. A lesson to keep:
Intelligent cities are about people and challenges in cities
Digital solutions are as good as the underlying process or practice