Smart cities utilize digital technologies and data to improve city operations and services for residents. A smart city requires measuring various city data through sensors and IoT devices. This data helps optimize areas like transportation, infrastructure, and public services. However, collecting and sharing large amounts of citizen data also raises privacy and security issues. Creating an open yet secure city data platform that many stakeholders can access presents technological and coordination challenges. Overall, smart cities aim to enhance life for residents through data-driven improvements, but achieving this vision requires addressing numerous technical, social, and governance complexities.

1. Smart Cities and Measurable Cities – a
technological perspective
Roberto Minerva
IEEE IoT Initiative Chairman, Telecom Italia Lab

2. Introduction
What a (Smart) City is
– What a Smart City is
– How large a “Smart City” is
– Networks of Smart Cities
Before Smartness … comes Measurability
– The Quest for Data
– What, How, When to measure
Technological Transformation Examples
– Past
– ICT technologies impact
– Vertical vs Horizontal Applications
Need for a Purpose and Integration
12/09/20162

3. What a City is
3
Cities are defined as a cluster of contiguous grid cells of 1 km² with a population density of at least 1 500 inhabitants per km².
a functional urban area: which consists of a city and its commuting zone; the latter is defined in relation to commuting
patterns, on the basis of those municipalities with at least 15 % of their employed residents working in a city (see Map 2);
a greater city: in some cases, the urban centre stretches far beyond the administrative boundaries and so to better capture the
entire centre, a ‘greater city’ has been defined (generally applicable only to capital cities and other relatively large cities);
a city: the most basic level, a local administrative unit (LAU), defined by its urban centre that has a minimum population of
50 thousand inhabitants, consisting of a cluster of contiguous grid cells of 1 km² with a population density of at least 1 500
inhabitants per km²;
subcity districts: a subdivision of the city according to population criteria (generally between a minimum of 5 thousand and a
maximum of 40 thousand inhabitants); they should be defined for all capital cities and for non-capital cities with more than
250 thousand inhabitants.
Source: Urban Europe — statistics on cities, towns and suburbs — introduction available at
http://ec.europa.eu/eurostat/statistics-
explained/index.php/Urban_Europe_%E2%80%94_statistics_on_cities,_towns_and_suburbs_%E2%80%94_introdu
ction#Background_information_outlining_key_methodological_concepts_for_EU_statistics_on_territorial_typologies

4. What a Smart City is
For policy purposes, the EU defines a smart city as ‘a place where
traditional networks and services are made more efficient with the
use of digital and telecommunication technologies, for the benefit
of its inhabitants and businesses’.
Smart cities are innovative, making traditional networks and
services more efficient through the use of digital technologies,
creating more inclusive, sustainable and connected cities for the
benefit of inhabitants, public administrations and businesses.
Smart cities have the potential to improve the quality of life, while
ensuring the needs of present and future generations with respect
to economic, social and environmental challenges.
The concept of smart cities covers a broad range of areas such as:
the economy, the environment, mobility, or governance.
4
Source: Urban Europe — statistics on cities, towns and suburbs — smart
cities available at http://ec.europa.eu/eurostat/statistics-
explained/index.php/Urban_Europe_%E2%80%94_statistics_on_cities,_towns
_and_suburbs_%E2%80%94_smart_cities

5. What a Smart City is (2)
5 http://www.slideshare.net/srujanirulzzworld/smart-cities-54021321

6. How to understand a City: First
Law of Geography
6
This is also expressed as an
inverse Power Law:
1/d2
http://geohealthinnovations.org/wp-
content/uploads/2013/01/toblerquote.png

7. Gravity Model …
7
Take Newton’s second law of motion – force is
proportional to mass times acceleration as F12
~ M 1 M 2 / (d 2)12 – and apply to Cities.
What is the Mass of the City?  its population!
What we get? The GRAVITATION MODEL
Tij = k Pi Pj / (cij)2
Where k is a gravitational costant
Cij is a measure of costs for traveling from i to j
Excepts from http://www.spatialcomplexity.info/files/2011/10/Spatial-Complexity-Lecture-6.pdf

8. Rome was by far the
largest City of the Empire
(and in the world)
All the economy was built
around it.
It was a kind of magnet,
attracting business from
every part of the empire
The city developed huge
logistics, transportation
and water systems to
support itself
The City and Its Ecosystem –
Ancient Rome
8
Do you want to see more ?
http://www.slideshare.net/mfresnillo/roman-architecture-398210
Big City > 1 M inhabitants
Good construction technologies
A Large Transport System

9. Il Porto di Ostia Antica e la Citta Ideale
9 10/3/2015
L'autrice dell'opera di ricostruzione del porto antico è
Viviana Meucci (Viviana Meucci: www.focemicina.it)
La citta ideale

10. Turin – Milan < 50 min
Milan – Rome < 3
hours
1/d2 is substituted by
1/t2
Cities have now
comparable «Mass»
And are well spread in
the territory and are
within acceptable
parameter of
connectedness
But what is happening now
between Cities ?
10 10/3/2015
Who is actracting whom?

11. From the Gravity to the Radiation
Model
11
Simini, F., González, M. C., Maritan, A., & Barabási, A. L. (2012). A universal model for
mobility and migration patterns. Nature, 484(7392), 96-100.Available at
https://arxiv.org/ftp/arxiv/papers/1111/1111.0586.pdf

12. Networks of Smart Cities (and
Teritories)
12
Each City has to be a hub for
connectedness and services
available over a large covered
and interconnected territory
http://chorally.com/learn-impact-smartcity-using-social-networks-analysis/

13. Actually a (Smart) City is a Complex
System [interacting with other Complex
Systems]
Michael Batty in “Cities as Complex Systems: Scaling,
Interactions, Networks, Dynamics and Urban
Morphologies” available at
http://discovery.ucl.ac.uk/15183/1/15183.pdf
Luis Bettencourt: Cities as Complex Systems available
at https://www.youtube.com/watch?v=JTZ6onbPjWk
– Heterogeneity: diversity of people and Organizations
– Interconnectivity: Everything is connected in Networks
– Scaling: Cities of different sizes have different problems
– Circular - Causality: Cause and Effect are mixed
– Development: Cities change in open-ended ways
10/3/201513

14. The impact of technologies on the City:
The Freedom Bridge example
14
Every day in Venice almost 200 K people are in
the city, even if only less than 60Kof Venice live in
here
It is more than 140K transits: it is not only tourists,
it is commuters: students and workers.
A lot of people have left the city for the mainland.
And the city has lost not only citizens, but also a
part of its identity.
How this happened ? Because of a Bridge!!!
The Liberty Bridge has introduced a «Semiotic
breakdown»: instead of bringing in modernization,
it has brought to the «simbolization» of Venice
(i.e., it is a postcard)
http://www.linkiesta.it/blogs/cultura-rete-il-blog-di-venezia-2019-salone-
europeo-della-cultura/l-alba-di-una-nuova-venezia-
Ponte della Libertà, i.e., the Freedom Bridge
Wikipedia: Ponte della Libertà is a road bridge connecting the historical center of the city of Venice to
the mainland.
Designed in 1932 by engineer Eugenio Miozzi, and opened by Benito Mussolini in 1933 as Ponte
Littorio, the bridge is the only access for road vehicles to the historical center. It is built alongside the
Venice Railroad Bridge, which was constructed in 1846 by Austrian, with two tracks each way, and is
still in use.

15. The Quest For Data
15
https://datavisualization.ch/wp-
content/uploads/2010/05/cph_wheel_04.png

16. How do we understand and reason
about Cities ?
16
https://www.jstor.org/stable/2573850?seq=1#
page_scan_tab_contents

17. How do we get Data ? Open Data
17

18. On Open Data
It’s a first step … but we need other data to really
«measure» a city
A Measurable City is made out of thousands of
information coming from Databases, or generated
in Real-Time typically by Sensors that provide
millions of data per second
Data may be:
– Events
– Continuous flows of simple data
– Update to existing data bases
– …
18

19. How do we get the data then?
19
Sensors
Internet of Things + BigData

20. What Internet of Things is
Aggregator/Gateway
Internet
Service Service Service
Events
Aggregator/Gateway
Events
Interworking
InterworkingComm.
Comm.
Usage
Vertical
Interoperability
Sensors Sensors
Commands
Commands
& Actuators & Actuators

21. Need for data – Seoul Garbage
21

22. Need for data – Counting people
without infringing Privacy in Venice
22
The Future Centre in Venice worked at the
monitoring in quasi real-time on the pedestrian
flows in the city center. The goal was to measure
the pedestrian traffic and keeping the anonymity
and privacy of users. The project has been using
low-cost sensors and devices (50-100 euros)
with a small size (two cigarette packs) in order to
acquire video flows of passing-by people and to
process it locally without any leak or privacy
violation. These devices will provide their Id, the
time and the number of people that have been
detected Ideally these objects could be
scattered in many places of the city and freely
transit their data (e.g., through twitter). In such a
way, interested developers could crate new
applications based on these data..
person-counter: simulation based on real data
Is it a person
or a shadow ?

23. Need for Data - SF Parking system
23
Managing in a
dynamic ways the
tariffs can change
the traffic
patterns!!!
http://sfpark.org/how-it-works/

24. Some Issues
24 10/3/2015

25. Open Up Is Dangerous
25
https://www.theguardian.com/technology/2014/jun/27/new-york-
taxi-details-anonymised-data-researchers-warn

26. Source: Beecham Research
Smart City: Application Domains
and Fragmentation!!!
The Vertical vs. Horizontal
platform challenge
SMART CITY

27. What Internet of Things really is
Service Service ServiceUsage
Different Administrative Domains
Networking
Virtualization
Data harmonization
Data Distribution
Networking
Virtualization
Data
harmonization
Data
Distribution
Interworking
Networking
Virtualization
Data
harmonization
Data
Distribution
Networking
Virtualization
Data
harmonization
Data
Distribution
Interworking
Horizontal
Interoperability

28. The Open Factory
– Immagine a Chemical
plant close to a city
– Who are the people more
keen to check the
security of the plant?
 Citizen
– Why don’t open up some
VALUES to people ?
Data is power!
And nobody wants to share power
28

29. Social Sensor: but users didn’t
want to share!
29
People have more and more the possibility to monitor important parameters of their home or of the
surrounding environment. Taking as an example the web site http://bwired.nl/, each user could have a
number of sensors monitoring and measuring parameters related to the functioning of the home or its
surroundings (e.g., the local outside temperature, the humidity, or even some parameters related to
pollution, noise and others).
The service is intended for collecting the wealth of user generated data, to anonymize them, and to
elaborate them for benefits of an entire community or for describing its own behavior (e.g., to calculate
a medium or average value for some parameters and allow each citizen to compare his own set of
parameters with the “average set of values” - for instance those that describe virtuous citizen
behavior with respect to a proper power consumption footprint). The availability of these data could
ignite a sort of game towards particularly good behaviors (power consumption is a good example).
Another possible usage is related to the integration of user generated data in such a way to compare
data and parameter directly collected by citizen versus official data provided by the public
administration. One important case could be the one of control of local pollution vs. the official data
monitored in particular area of big cities (http://www.scientificamerican.com/article.cfm?id=air-
pollution-monitoring-sensor-asthma-black-carbon).

30. (Social) Cooperation is very
important
A fundamental aspect of all adaptive systems is cooperation.
Natural selection favors cooperation, if the benefit of the altruistic act, b,
divided by the cost, c, exceeds the average number of neighbors, k, which
means b/c > k.
It is necessary enforcing altruistic behaviors in IoT networks (social
aspects on it)
Hisashi Ohtsuki, “A simple rule for the evolution of cooperation
on graphs and social networks”, Nature, Letters, Vol 441|25 May 2006|doi:10.1038/nature04605
The Socialization Challenge of IoT

31. Communications Technologies for IoT
(some)
Requirements associated with M2M and IoT:
• low cost,
• low power,
• compact form factors,
• rapid connection setup times,
• massively scalable deployments
See more at: http://www.wi-fi.org/beacon/craig-mathias/wi-fi-and-the-internet-
of-things-much-more-than-you-think#sthash.rzxKXMiJ.dpuf
M2M
WSN
http://d3uifzcxlzuvqz.cloudfront.net/images/stories/content/handbooks/iot-handbook/communication-iot1.jpg
TSP/MSC Communication Networks and Services
(ComNETS)
Deploying IoT System is
complex and expensive

32. IoT Data and … Identity of Things
Things have Identities (and Owners) People have Identities and use Things
Me
“My” Smart Thing
Identity Relation
Functional Relations
(events and commands)
Personal
Profiling
Who, Where, When, What, Why, …
Sensors
Identity Relation
Service Provider

33. Aggregating Data per Identity …
“OUR”SmartThings
Raw data to be
transformed into
Info
Personal
Profiling
Functional
Profiling
Who, Where, When, What, Why, …
+
Events and commands
* = Bigger
DATA
• Who is the Owner
of all these Data ?
• Who has the right
to extract info ?
50 B Devices *
(Average Aggregated Traffic of M2M Devices)
~ 2MB/day = ~ 88.81 petabytes
/day

34. A long value chain opens up
opportunities for many Actors
Source: Nokia Siemens Networks
«New»
Markets
Traditional
Markets
The Ecosystem Challenge
If money is in the
Platform, Many want
to have a platform

35. But IoT is technically Complex
API
Always Best
Connected Comm.
Sensors
Things
T
a
g
Tags Others
App Ecosystem
Platform Value
Ecosystem Value
Service/Apps
Value
Programmability
Value
Processing
Storage
Communications
Comm
Value
Communication Engine
(e.g., event based)
Autonomics and Self
Organization
Brokering of Virtual
Objects
Data Management
Objects
Registry
Objects
management
Extensive Objects Virtualization
API
Telco
Building
Blocks
MobileDevicePlatform
Native
Operating
System
Middleware
Functions
Terminal
to Cloud
Relationship
Terminal
to Capillary
Relationship
API
API

36. And there is the need to create a
City platform …
Open
Accessible
Secure
Interoperable
Rich of services for all people «involved» with the
city
With Shared goals and purposes (because a city is
a complexsystem that we need to control for the
good of everyone)
36

37. Stuff
37 10/3/2015

38. Where a Smart City ends ?
38
High Speed
Trains have
an impact on
two far away
cities
Journey < 2.5 h

39. Tag the City
39
The service allows a person or a service provider to tag places. Tagging
here means a virtual placemarker that describes a particular feature of a
place and pinpoint to a description available in the WWW. Tags can be
public (i.e., available to all) or private. Private tags are visible to a closed
user group and sometimes they can be viewed only if the user is paying
for a service or a single tag. Tags can be organized in such a way to
define a trail in the city. The preferred device category for dealing with
placemarkers are smartphones.

40. See What I See
40
An Object (being a person, a car, a truck
or other mobile objects) is moving in a
specific (e.g., an insecure area, a touristic
city, or others). The “See what I see
service” allows the object to be monitored
by means of the cooperation of available
objects along its route. Objects enforcing
some level of tracking could be simple
objects (e.g., proximity objects, RFID tags
or sensors that just record that the object
has just passed by) or more complex ones
(such as cameras that can record the
object passing by or even be able to
accompany that object for a short period –
movable cameras).
If the route is known in advance, objects
could be ready for the object passing by
without the need to guess where the object
is moving next. However for particularly
casual routes, a more dynamic allocation
of resources could be provided based on
prediction of possible movements and pre-
allocation of resources.