=Paper=
{{Paper
|id=Vol-1156/paper4
|storemode=property
|title=Cooperation of Smart Objects and Urban Operators for Smart City Applications
|pdfUrl=https://ceur-ws.org/Vol-1156/paper4.pdf
|volume=Vol-1156
|dblpUrl=https://dblp.org/rec/conf/ipsn/CitrignoGS14
}}
==Cooperation of Smart Objects and Urban Operators for Smart City Applications==
https://ceur-ws.org/Vol-1156/paper4.pdf
Cooperation of Smart Objects and Urban Operators for
Smart City Applications
Simona Citrigno
Centro di Competenza ICT-SUD, Rende (CS), Italy
simona.citrigno@cc-ict-sud.it
Sabrina Graziano
OKT Srl, Rende (CS), Italy
sabrina.graziano@okt-srl.com
Domenico Saccà
Università della Calabria and ICT-SUD, Rende (CS), Italy
sacca@unical.it
Abstract This paper illustrates main research activities and results of the pro-
ject “TETRis – TETRA Innovative Open Source Services” concerned with en-
abling innovative services for Smart City/Smart Territory by means of techno-
logical tools and intelligent platforms for collecting, representing, managing
and exploiting data and information gathered from sensors and devices de-
ployed in the territory. Technological tools and intelligent platforms are inte-
grated into a complex smart environment that provides advanced services to cit-
izen and operators for environmental monitoring, urban mobility and emergen-
cy management. Although the project is mainly based on the utilization of the
communication protocol TETRA, the application scenarios may work with oth-
er network protocols as well.
Keywords: Smart Objects, Urban Monitoring, Urban Mobility, Intelligent Plat-
forms, Wireless Sensor Networks.
1 Introduction
The concept of smart city is used all over the world with different nomenclatures,
context and meanings [10,13,16]. The concept adopted in this paper is: a city is smart
if it acts in a forward-looking way in economy, people, governance, mobility, envi-
ronment, and living, using a suitable combination of endowments and activities of
self-decisive, independent and aware citizens. Therefore, a smart city monitors and
integrates conditions of all of its critical infrastructures, optimizes its resources, plans
its preventive maintenance activities, and monitors security aspects while maximizing
services to its citizens [11]. To be smart, a city must interconnect the physical infra-
structure, the ICT infrastructure, the social infrastructure, and the business infrastruc-
ture to leverage the collective intelligence of the city [3,12]. The use of advanced ICT
technologies is crucial to make its infrastructure components and services (including
41
city administration, education, healthcare, public safety, real estate, transportation,
and utilities) more intelligent, interconnected, and efficient and to identify new, inno-
vative solutions to city management complexity, in order to improve sustainability
and livability [15]. In sum, a smart city must strive to make itself “smarter” (more
efficient, sustainable, equitable, and livable) [14].
The activities described in this paper are related to the design and prototypal im-
plementation of innovative services aimed at an intelligent management of an urban
territory for novel smart city application scenarios. Within these activities, a number
of solutions and advanced technology platforms have been identified that enable the
various entities operating in the area of interest (municipalities, provinces, regions,
universities, etc.), as well as citizens and urban operators, to effectively cooperate for
an efficient usage of urban resources. In fact, the wealth of information acquired on
the territory through the use of sensors and devices interconnected by local and re-
mote communication systems are suitably stored and processed to support high add-
ed-value services to improve the quality of the territory itself in terms of livability and
sustainability. A crucial aspect is the involvement of citizens and urban operators who
become the main tutors of the territory, the so-called "social sensors", for the detec-
tion of critical situations in the urban territory.
The innovation scenarios and solutions described in this paper have been realized
within the project PON 2007 2013 - Research and Competitiveness "TETRis -
TETRA Innovative Open Source Services" according to reference general frame of
"Internet of Things" for supporting Smart City/Smart Territory [2], in which the ac-
quisition of data by objects is applied to large territorial areas by exploiting the wide-
spread availability of communication networks [9, 21]. The collected data, properly
enhanced and enriched, foster innovative services oriented to the production and ex-
change of knowledge among the different actors interconnected in urban and regional
networks. The development of these services has been realized through the coopera-
tion of smart devices and objects as well as of operators and users of the services
themselves.
A key role in Internet of Things, as well as in smart city scenarios and services, is
played by the concept of smart object, first introduced in [17], which is a physi-
cal/digital object having a unique identifier that is used to digitally manage physical
things (e.g., sensors), to track them throughout their lifespan and to annotate them
(e.g., with descriptions, opinions, instructions, warranties, tutorials, photographs,
connections to other objects, and any other kind of contextual information imagina-
ble), and to consciously handle its relationships with other smart objects and with
remote systems. In sum, a smart object is a physical/digital object augmented with
sensing/actuating, processing, and networking capabilities that may embed human
behavioral logic [18].
Smart objects are typically part of a Smart Environment, which is "a physical
world that is richly and invisibly interwoven with sensors, actuators, displays, and
computational elements, embedded seamlessly in the everyday objects of our lives,
and connected through a continuous network" [20]. Smart Environments are often
based on a suitable middleware that enables communication and management of
smart objects in distributed applications [19, 22, 23].
42
The activities described in this paper refer to two main application scenarios identi-
fied within a Smart City context: (A) Urban Mobility (B) Territory Monitoring, Con-
trol and Maintenance.
The remainder of the paper is organized as follows: Section 2 presents an over-
view of the TETRis project and describes its main goal, Section 3 illustrates two
meaningful innovative application scenarios for smart city/territory, Sections 4 and 5
focus on the scenario respectively of urban mobility and of urban monitoring and risk
analysis and Section 6 withdraws the conclusion and discusses further work.
2 Project Objectives of TETRis
The TETRis project main goal is to create high value-added services by exploiting
and possibly extending the functionalities of the TETRA communication system. The
Terrestrial Trunked Radio (TETRA) is an open standard for mobile radio communica-
tions developed by the European Telecommunications Standards Institute (ETSI) and
specifically designed to support Professional Mobile Radio communications (PMRs)
in a number of market segments such as public safety, transportation, utilities gov-
ernment, military, commerce, industry. TETRA is deployed in over 88 countries
worldwide, and the main market is by far that of national public safety organizations.
The primary goal of public safety is to carry out all the necessary actions for the pre-
vention and protection from events, such as dangers, injuries, or damages, that could
threaten the safety of the general public.
TETRA system is particularly suitable to meet the needs of professional users of
emergency care organizations dealing with public utilities, public security forces,
transport companies, and it represents also the answer to solve the growing needs of
private mobile radio systems (PMR) users, both in terms of radio traffic decongestion
and in enhancing voice and data services. TETRA is designed to provide operational
and service communications between land mobile units, naval and air and their related
control centers, in either voice and data modes, and it integrates with existing radio
communication frameworks and commercial communication systems, thus ensuring
maximum efficiency both in terms of transmission resources and in management and
use.
TETRA provides a common and standard infrastructure for secure and reliable
communications and also supports unique features such as group conversations, dis-
patcher centers, and direct communications. While the initial focus of TETRA has
been on voice communications, data communications have been supported since the
beginning and nowadays are gaining more importance. The prevention and manage-
ment of critical situations related to public safety, requires the real-time acquisition of
data from the field in order to react more consciously, faster and better.
The project acts along three main axes in order to enhance TETRA functionalities and
to extend its usage to novel application domains:
1. The evolution and the opening of novel application fields for TETRA in order
to define new information services for operators, exploiting new models and
open source tools for the interconnection of TETRA with other networks and
the identification of new type of TETRA-based devices suitably interoperated
with existing sensors and sensor networks;
43
2. The modeling and prototyping of an Open Source framework implementing a
Smart Objects cooperation model and enacting their management by means of
so-called Smart Environments;
3. The identification of novel scenarios and application models in the perspective
of Smart City/Smart territory services applied to territory monitoring, emer-
gency management and intelligent support to urban mobility.
The specific objectives of TETRis project can be read as follows:
Bringing economic and social benefits to the community through more target-
ed and effective actions by Public Administration and Public Security opera-
tors in application scenarios such as emergency management, environmental
protection, mobility and services to citizens, with the contribution of the citi-
zens themselves through the sharing of information and the use of innovative
tools for social networking;
Extending the pervasiveness and effectiveness of public administration ser-
vices, instrumental bodies, local police, health operators, transport companies
in the reference areas; Improving the quality of life and the sense of safety of
citizens through the spreading of safe and reliable technology infrastructure
"always on".
The project activities are organized in a number of work packages, each of them
consisting of a number of Industrial Research and Experimental Development activi-
ties.
This paper describes the experimental activities conducted by the project in the fol-
lowing two application areas:
"TETRis Smart Environments for mobility" - it concerns the implementation
of a model for the detection of mobility problems in urban areas through the
use of specific Smart Objects located in the territory and the use of a network
of sensors connected to them. These data are collected and aggregated into a
data warehouse feeding a Mobility Intelligence platform defined through the
design of innovative techniques of space-temporal data analysis and mining of
complex data, including trajectories.
"TETRis Smart Environments for territory monitoring and delivery of services
to citizens" - it defines a Smart Environment managing a network of physical
sensors connected to Smart Objects that is enriched by "social" sensors which
detect in real time the status of the territory. These so-collected data are stored
and aggregated into a data warehouse feeding a Territory Intelligence plat-
form, which enables the extraction and processing of knowledge for monitor-
ing the territory.
Within the project two collaboration agreements have been signed with the munic-
ipalities of two towns in Southern Italy: (i) Cosenza as for the Urban Mobility area,
and (ii) Rende as for Urban Monitoring area. The two municipalities have shown a
high interest in the experimentation of innovative IT solutions and techniques in their
view of pursuing the realization of a new model of a city, seen as an intelligent system
that supervises on the compliance and control of the environment, and effectively
manages resources through the use of technological ICT infrastructure and innovative
tools in order to deliver high added-value services for citizens.
44
3 Design of the Applications Scenarios for Smart City
The two scenarios that have been identified for a typical application in support of a
Smart City share the same basic architecture that includes the following elements:
Actors - divided into three categories:
o Government Body, which is responsible for managing the Smart Envi-
ronment and the Smart Object network distributed throughout the area;
o External Local Authorities, which are interested in the services of the
Smart Environment and Smart Objects with which they interact;
o Individuals, who can be either citizens or workers (operators) performing
their duties in the area under the directions of the managing body;
Government central systems, which are responsible for the overall application
functioning and for the control of the Smart Object networks distributed on the
territory;
External Local Authorities systems, which interact with the Government cen-
tral systems and the Smart Objects on the basis of operating protocols agreed
with the central systems and that can also interact with other external authori-
ties systems;
Smart phones APPs, used by individuals;
Smart Objects, which are distributed on a territory under the management of
the central system, and perform two types of communication:
o Remote communication: (i) with the Government central system through
TETRA, (ii) with External Local Authorities systems through commer-
cial telecommunications protocols (GSM, UMTS, etc.) and possibly also
with TETRA;
o Local communication: (i) with operators through WiFi and NFC technol-
ogy for instant activation and personalization of the interaction, (ii) with
citizens through WiFi, (iii) with physical objects, that are related to a
Smart Object and are distributed over the territory, typically using
ZigBee protocol or RFID.
Sensors, which can be:
o classical traffic detection sensors, related to a Smart Object, connected
together with ZigBee network protocol or RFID;
o classical sensors for environmental conditions detection (temperature,
humidity, sound, CO, dust, etc.) connected together with an ad hoc net-
work;
o social sensors, that means citizens and operators having a mobile device
provided with applications for signaling and/or monitoring events that
occur in the territory of interest;
o devices, sensors/actuators of urbotic (i.e., automation at urban level) that
can either directly interact with Smart Objects using low power protocols
but with high performance, such as Cliffside and Wibree, or through a
dedicated control kit using WiFi connection.
45
Fig. 1. A Smart Object Usage Scenario
Figure 1 shows the overall picture of a typical scenario of Smart Objects usage
within a Smart City with an indication of the various components and their interac-
tions. Smart Objects use remote communication protocols, such as GSM, TETRA
and/or Internet, for information exchange with Government Body and External Local
Authorities concerning urban monitoring and emergencies management. Smart Ob-
jects may also exchange data with citizen and operators using local communication
protocols, such as: WiFi, Bluetooth and NFC, when interfacing with citizen
smartphone applications; WiFi, NFC, TETRA, when communicating with operators
devices; RFID, for bus mobility detection; WIFi, ZigBee, Cliffside for sharing infor-
mation with sensors networks.
Figure 2 shows a general architecture of a Smart Object where some relevant
components are identified: the Smart Object software intelligence, which collects data
coming from sensors networks, citizens and operators apps, processes them on the
basis of some alerting and control criteria, and delivers the results to external entities
using local and/or remote communication protocols and specific interfaces, depending
on the target users. The Smart Object architecture can vary depending on the scenario
taken into consideration and it can be seen as a three level architecture with the fol-
lowing tiers: (1) a basic level, where social sensors communicate information through
the usage of smartphone apps and physical sensors can detect some specific deter-
mined measures and continuously transmit data to the government central system; (2)
a middleware level, which is able to collect data transmitted by sensors and which is
provided with an alerting system - data collected at this stage feed operational and
informational dashboards that are used by citizens and operators; (3) a business intel-
ligence system which integrates data coming from different internal and external
sources and provides territory, mobility and security intelligence services to Govern-
ment Bodies and External Local Authorities by means of decision support dash-
boards.
46
Fig. 2. Smart Object Architecture
4 Urban Mobility
The Urban Mobility scenario implements a model based on a network of smart ob-
jects and connected sensors network providing in real time data related to the mobility
in a urban area. The model also includes amenities to deliver services to operators and
citizens through the use of mobile devices.
Data collected from sensors and smart objects geographically distributed are col-
lected and aggregated into a data warehouse feeding a Mobility Intelligence platform
that performs on-line knowledge-based analysis in order to deliver real-time infor-
mation about the smart management and usage of mobility systems to both urban
operators and citizens.
The experiment has been carried out on the territory of the municipality of Cosenza
along two main macro areas of development:
Urban traffic detection and management by means of stationary smart objects,
placed at critical points in the city of Cosenza, which collect frames and vide-
os from webcams and traffic detection sensors;
Detection and management of any violation made by cars on bus corridors by
means of moving smart objects installed on buses of the public city transporta-
tion company.
The Mobility Intelligence platform processes data in real time, according to the
most recent lines of research in OLAP systems analysis and data mining, and per-
forms as a decision support system supporting operators to extract, quickly and in a
flexible way, all the information needed to meet citizens mobility needs [8]. A dash-
board offers the possibility to the interested authorities to take strategic/operational
decisions and to better plan interventions on road infrastructure, public transport
routes, available parking spaces and multimodal communication infrastructure with
citizens. The analysis of data through the intelligence platform can also offer a valid
47
support for the definition of the urban traffic plan through a calibration activity of the
model in order to update the plan and to adapt it to the observed actual reality.
Thanks to an effective integration of data mining tools and geo-referenced data
analysis, the platform is also able to depict spatial data, models and results on a geo-
graphical map.
Within the urban mobility scenario, the following classes of applications for citi-
zens and operators have been also implemented available:
1. APPs for citizens, providing information on
bus tracking: arrival times, their timetable, the positions of the nearest
bus stops;
available parking places: their location on the map, the number of vacan-
cies and the way to reach them;
real-time traffic updates and traffic jam reports;
the city life: places of interest, restaurants, hotels and clubs.
All information is contextualized according to the geo-localization of citi-
zens.
2. APPs for operators enabling them to monitor the traffic and public transport
status, to analyze alerts about traffic jams, parking in double row, other dis-
ruptions;
3. App for issuing fines, by recording the violation of the rule with its geo-
localization and by possibly attaching a photo as a proof.
The same services delivered by the apps are also made available using a Web por-
tal.
The following further analysis tasks were conducted to define the model for urban
mobility [1,4,7]:
1. Assessment to check the actual possibility to replace part of private mobility in
the urban area of Cosenza by public transport together with highlighting of de-
ficiencies, waste of resources and with suggesting for improvements / up-
grades;
2. Discovery of public bus frequent moving patterns in their routes from the min-
ing of bus logs and trajectories;
3. Reachability evaluation of the city and surrounding areas, using data on both
public transport routes and bus logs to compute the actual time distances
among the various areas of Cosenza during the day;
4. Profiling of Population Mobility, using data from a mobile phone company to
detect how phone callers move among the various city areas and to classify
them on the basis of their behaviors.
5 Urban Monitoring and Risk Analysis
The Urban Monitoring and Risk Analysis application scenario activities concerns the
definition of a Smart Environment integrated with a network of smart objects located
throughout the territory for the management and maintenance of the urban environ-
ment and for the delivery of timely and innovative services to citizens. During the
48
experimentations, a number of physical and "social" sensors have been deployed in
the territory to detect in real time the status of the territory itself and the associated
risks. The scenario includes a Territory Intelligence platform that first collects data
supplied by smart objects and social sensors and, then, as a result of the appropriate
phases of integration and data processing using advanced techniques of data ware-
housing, it makes the information available to various parties with which the platform
interacts in order to properly monitor urban areas.
Within this scenario a number of contextual applications have been made available
to citizens and operators working for territory maintenance through their mobile de-
vices. These applications allow them to immediately communicate with the public
administrations and utilities to report critical situations, malfunctioning in urban net-
works, road failures and intervention requests for restoring the conditions of good
livability of the territory. Events to be reported are classified into the following cate-
gories: dangers on the road, stray animals, services and networks, urban refurnish and
green, waste depot. The collected data and reports can also be inquired via a Web
portal that can be seen of as a managing console in order to: assign the requests to an
operator or a group of operators for the appropriate intervention activities; monitor the
status of the actions; check the status of the smart objects distributed in the area of
interest; implement an overall urban safety system by the immediate involvement of
urban operators.
The experiments were carried out on the territory of the Municipality of Rende
with focus on the monitoring of urban and extra-urban areas through real-time infor-
mation coming from sensor networks connected to smart objects suitably distributed
in the urban territory.
Real-time information from smart objects and social sensors feed the model used to
draw up new plans of action, or to update/modify the current ones so that a local gov-
ernment can better relate resource planning to the needs in a dynamic and timely way.
Sensors distributed throughout the territory have been also designed to detect the
exceeding of prefixed "thresholds", which require contingent changes to maintenance
plans by the government bodies.
Within the Urban Monitoring scenario, a Risk Analysis model has been also im-
plemented for road traffic monitoring in urban areas in order to identify and assess the
risks hanging over the system under observation and to take the necessary counter-
measures. The identification of the possible risk events and the activities for monitor-
ing them enable, in a more easy and rational way, local authorities to implement ac-
tion plans to prevent the occurrence of risks or to reduce their impact, to promptly
detect ongoing risks and to alert urban operators for their immediate intervention,
possibly involving also citizens both in the detection of critical situations and in the
immediate assistance.
The experiments within Urban Monitoring scenario have also made usage of wire-
less sensor networks for monitoring the surrounding environment [5], forwarding the
acquired information to a collection center (a sort of a gateway smart object) through
the construction of a multi-hop ad-hoc network. This converge-cast communication
schema is particularly suitable for collating data on a territory and for communicating
them to a central sink (a smart object), in order to make data available for other pro-
49
cessing. The adopted protocol is CTP - Collection Tree Protocol [6]. Every sensor
periodically communicates data to its parent (selected on the basis of the communica-
tion protocol policy) going up to the sink in order to forward data to the Territory
Intelligence platform.
Two main experimental domains have been identified:
1. Indoor working environment monitoring;
2. Buildings monitoring.
In the first domain, a wireless sensor network have been installed to monitor the
quantity of CO2, CO and dust, the temperature and humidity levels in a specific area.
Collected data cover a period of several weeks and they are made accessible in real-
time and, later on, summarized in a report. At the end of the monitoring process in the
specific site, the network can be dismantled and used in a new place (building, urban
area) in order to reduce costs and to repeat the same analysis in a different site.
Finally, a further wireless sensor network has been used for the monitoring of the
statics of buildings in order to provide evidence of whether the situation is to be con-
sidered "under control" or is instead critical and, therefore, a prompt intervention is
needed or some alarm signal has to be sent.
6 Conclusion
We have illustrated some of the activities and results of the TETRis project concerned
with the study and experimentation of innovative solutions for the regeneration of
urban contexts according to the emerging integrated strategic vision of the Smart City.
Experiments were made possible thanks to collaboration agreements with two South-
ern-Italy municipalities and to the proactive involvement of their representatives in
the design and implementation of novel smart city application scenarios in order to
provide more effective and efficient services to citizens. A crucial role in the applica-
tion scenarios is played by the so-called 'social sensors', i.e. the citizens themselves
and operators (municipality and utility employees) who are supposed to communicate
in real time with all the institutions to report all critical situations such as traffic jams,
vandalism and neglect, presence of waste, road holes, various inefficiencies.
The paper has described two relevant smart city application scenarios: (1) Urban Mo-
bility and (2) Territory Monitoring, Control and Maintenance. The two scenarios
share the same architecture based on a network of stationary and moving smart ob-
jects located in the urban areas and on Intelligent Software platforms supporting the
delivery of innovative services to both urban operators and citizens. Thanks to the
pervasive usage of advanced ICT tools, the two scenarios enhance the direct line citi-
zens - Public Administration, thus enabling the citizens to become an integral compo-
nent of good administrative practices.
Acknowledgments
This work was developed within the three-year project TETRis - "TETRA Innovative
Open Source Services", started on January 2010 and partially granted by MIUR (Min-
50
istry of Education, Universities and Research) under the program PON 2007 - 2013 -
Research and Competitiveness.
The project industrial partners are: Orangee (coordinator) and SelexElsag (two
Finmeccanica companies), the Competence Centre ICT SUD (along with four member
companies: Methodi, Kaleidos, SIRFIN, SCAI LAB), and four local SMEs: H2i, Ex-
eura, Sinapsys and TSC Consulting. The academic partners are: University of Ca-
labria, Mediterranean University of Reggio Calabria, the CNR institute ICAR and
two Italian inter-university ICT consortia: CNIT and CINI.
The authors would like to thank the following colleagues and collaborators for
their important contribution:
Andrea Vitaletti and Ugo Colesanti (Department of Computer, Control, and Manage-
ment Engineering Antonio Ruberti at Sapienza University of Rome), Fosca Giannot-
ti, Dino Pedreschi, Barbara Furletti, Lorenzo Gabrielli and Roberto Trasarti (KDD
Lab ISTI CNR - Pisa), Rosario Curia and Loredana Sisca (H2i Srl - Italy), Michele
De Buono (SCAI LAB Srl), Raffaele Bianco and Salvatore Pirruccio (Sinapsys Srl -
Soverato, CZ), Roberto De Donato (SIRFIN SpA - Italy), Sergio Scrivano (Methodi
Srl - Italy), Giuseppe Musso, Francesco Scarpelli and Luigi Leonetti (Kaleidos Srl -
Cosenza), Geppino De Rose, Leonardo Acri, Maria Rosaria Mossuto and Roberto
Caruso (Municipality of Cosenza), Luigi Mamone, Corrado Zoccali and Vincenzo
Settino (Municipality of Rende).
References
1. F. Giannotti, M. Nanni, D. Pedreschi, F. Pinelli, C. Renso, S. Rinzivillo, R. Trasarti: Un-
veiling the complexity of human mobility by querying and mining massive trajectory data.
VLDB Journal Special issue on Data Management for Mobile Services (2011).
2. N. Komninos, H. Schaffers, M. Pallot, “Developing a Policy Roadmap for Smart Cities
and the Future Internet”, eChallenges e-2011 Conference
3. R. Moss Kanter, S.S. Litow,“Informed and Interconnected: A Manifesto for Smarter Cit-
ies”, Working Progress, 09-141, 2009
4. PHC09: F. Pinelli, A. Hou, F. Calabrese, M. Nanni, C. Zegras, C. Ratti, Space and time-
dependant bus accessibility: a case study in Rome. Proceedings of the 12th International
IEEE Conference on Intelligent Transportation Systems, 2009
5. A. Rosi, M. Berti, N. Bicocchi, G. Castelli, M. Mamei, A. Corsini, F. Zambonelli, "Land-
slide Monitoring with Sensor Networks: Experiences and Lessons Learnt from a Real-
world Deployment", International Journal of Wireless Sensor Networks, Seattle, 2011, to
appear.
6. O. Gnawali, R. Fonseca, K. Jamieson, D. Moss, P. Levis (2009). "Collection tree proto-
col". SenSys: 1–14
7. R. Trasarti, F. Giannotti, M. Nanni, D. Pedreschi, C. Renso: A Query Language for Mobi-
lity Data Mining. International Journal of Data Warehousing and Mining (IJDWM) 2010
8. European Commission, “Intelligent Transport Systems in Action, action plan and legal
framework for the deployment of intelligent transport systems (ITS) in Europe” 2011,
Bookmark: http://trove.nla.gov.au/version/166764828
9. European Commission, “Smart Cities and Communities – Support for a better future”,
2013: http://ec.europa.eu/eip/smartcities/
51
10. A. Boulton, S.D. Brunn, & L. Devriendt (2011). Cyberinfrastructures and “smart” world
cities: Physical, human, and soft infrastructures. In P. Taylor, B. Derudder, M. Hoyler & F.
Witlox (Eds.), International Handbook of Globalization and World Cities. Cheltenham,
UK: Edward Elgar. Available from:
http://www.neogeographies.com/documents/cyberinfrastructure_smart_world_cities.pdf.
11. R.E. Hall (2000). The vision of a smart city. In Proceedings of the 2nd International Life
Extension Technology Workshop, Paris, France, September 28, Available from:
http://www.osti.gov/bridge/servlets/purl/773961-oyxp82/webviewable/773961.pdf.
12. C. Harrison, B. Eckman, R. Hamilton, P. Hartswick, J. Kalagnanam, J. Paraszczak & P.
Williams (2010). Foundations for Smarter Cities. IBM Journal of Research and Develop-
ment, 54 (4).
13. R.G. Hollands (2008). Will the real smart city please stand up? City, 12 (3), 303-320.
14. Natural Resources Defense Council. What are smarter cities?, Available from:
http://smartercities.nrdc.org/about.
15. D. Toppeta (2010). The Smart City Vision: How Innovation and ICT Can Build Smart,
“Livable”, Sustainable Cities. The Innovation Knowledge Foundation. Available from:
http://www.thinkinnovation.org/file/research/23/en/Toppeta_Report_005_2010.pdf.
16. H. Chourabi, T. Nam, S. Walker, J. Ramón Gil-García, S. Mellouli, K. Nahon, T.A. Pardo,
H. Jochen Scholl: Understanding Smart Cities: An Integrative Framework. Proceedings of
45th Hawaii International International Conference on Systems Science, HICSS-45 2012,
4-7 January 2012, Maui, HI, USA, 2289-2297
17. M. Kallman, D. Thalmann: "Modeling Objects for Interaction Tasks", Proc. Eurographics
Workshop on Animation and Simulation, Springer, 1998, pp.73-86.
18. G. Kortuem, F. Kawsar, V. Sundramoorthy, D. Fitton, "Smart Objects as Building Blocks
for the Internet of Things," IEEE Internet Computing, 14 (1), pp. 44 - 51, Janu-
ary/February, 2010.
19. G. Fortino, A. Guerrieri, W. Russo, "Middleware for Smart Objects and Smart Environ-
ments: Overview and Comparison", in Internet of Things based on Smart Objects: tech-
nology, middleware and applications, Springer Series on the Internet of Things: Technolo-
gy, Communications and Computing. 2014.
20. S. Poslad (2009). Ubiquitous Computing Smart Devices, Smart Environments and Smart
Interaction. Wiley 2009.
21. IERC Documents and Publications on the Internet of Things Vision in Europe:
http://www.internet-of-things-research.eu/documents.htm
22. G. Fortino, A. Guerrieri, W. Russo, “Agent-oriented Smart Objects Development,” Proc.
of 2012 16th IEEE International Conference on Computer Supported Cooperative Work in
Design (CSCWD 2012), Wuhan (China), May 22-25, 2012.
23. G. Fortino, A. Guerrieri, M. Lacopo, M. Lucia, and W. Russo, "An Agent-based Middle-
ware for Cooperating Smart Objects", in Highlights on Practical Applications of Agents
and Multi-Agent Systems (J.M. Corchado, J. Bajo, J. Kozlak, P. Pawlewski, J.M. Molina,
V. Julian, R.A. Silveira, R. Unland, S. Giroux, eds.), Communications in Computer and In-
formation Science (CCIS), Vol. 365, pp. 387-398, Springer Berlin Heidelberg, 2013.
52