Smart City Technologies and Architectures

A Literature Review

Christiana Kyriazopoulou

University of Macedonia, Thessaloniki, Greece

Keywords: Smart Cities, Technologies, Architectures.

Abstract: The main goal of smart cities is to improve the traditional services that are provided to the citizens and also

create new and more challenging ones. This vision aims not only to citizens’ prosperity, but also to

economic progress and sustainability of the city. It is feasible to achieve this goal through the use of

technologies and architectures which purpose is to integrate the various elements of the city and help them

interact in an effective manner. In this paper, we discuss the key technologies and architectures that have

already been proposed in the literature in order to find the appropriate ones to be implemented for the

development of smart cities.

1 INTRODUCTION

Several definitions have been published over the

years about the term “Smart City (SC)”. One of the

most widely accepted is that by IBM (2010) that

assumes SC as “the use of information and

communication technology to sense, analyze and

integrate the key information of core systems in

running cities”. According to Caragliu et al. (2011)

“a city is smart when investments in human and

social capital and traditional (transport) and

modern (ICT) communication infrastructure fuel

sustainable economic growth and a high quality of

life, with a wise management of natural resources,

through participatory governance”. SC is also

considered to have a strong relationship with digital

city. A. Cocchia (2014) referred that digital city is a

subcategory of SC, because both of them include

Information and Communication Technologies

(ICT). The main difference is that SC intends to

improve citizens’ standard of living through the

development of the economy, the social and political

progress, the provision of new services and the

protection of the environment. Moreover, K. Su et

al. (2011) stated that SC generates from digital city

when it is combined with Internet of Things (IoT).

The need for SC arises due to urbanization of

modern cities and the necessity to solve various

daily problems that affect citizens’ lives. The

technological progress gives us the opportunity not

only to manage these problems but also create

services and facilities in order to improve people’s

quality of living. The main sectors that a SC aims to

improve are smart economy, smart people, smart

governance, smart mobility, smart environment and

smart living (Giffinger et al, 2007). In order to

manage these sectors and design useful applications,

SC exploits all the available resources, monitors

conditions and collects information through sensors

and critical infrastructure. Then, it analyzes and

processes them through the use of ICT so as to offer

citizens the expectable satisfaction.

The purpose of this paper is to discuss the basic

platforms and architectures that have been proposed

over the years and specify the ones that are more

useful in building SC. Section 2 presents some of the

selected technologies that should be integrated in a

SC as we find them in the literature. Section 3

includes the discussion about the usability and

implementation of the presented technologies. The

last section 4 shows the concluding results and

suggestions for future work and research.

2 BACKGROUND

Below we quote several architectures and their

including technologies. Although the literature

contains many surveys and suggestions about the

architectures that participate in the design and

Kyriazopoulou C..

Smart City Technologies and Architectures - A Literature Review.

DOI: 10.5220/0005407000050016

In Proceedings of the 4th International Conference on Smart Cities and Green ICT Systems (SMARTGREENS-2015), pages 5-16

ISBN: 978-989-758-105-2

 2015 SCITEPRESS (Science and Technology Publications, Lda.)

operation of a SC, there is not yet a standard one that

integrates all the functionalities. Furthermore, the

greatest number of these architectures is based on a

theoretical approach and non in a practical one with

real implementation. In this section, we present

some of the proposed architectures giving emphasis

in the most common technologies that we meet a lot

in the literature. We have recognized six

perspectives of architectures - the perspective of

Architectural Layers, Service Oriented Architecture,

Event Driven Architecture, Internet of Things,

Combined Architectures and finally the new

perspective of Internet of Everything. In the rest of

our paper, we cite the works of different researchers,

categorizing them chronologically and respectively

to the perspective they belong. Finally, we

summarize these works in a table for better

understanding.

2.1 Architectural Layers (AL)

AL provide a framework for developing services and

applications in SC through their fragmentation into

pieces (layers) that can be easily modified and

adjusted instead of transforming the whole system.

Each layer is physically and logically dissociated

from the others. This characteristic is the one that

makes the perspective unique and explains its choice

and great acceptance by a large number of

researchers. In this subsection, we mention some of

the most outstanding works that choose to

implement this architecture in order to create useful

facilities for SC.

Initially, T. Ishida (2000) was one of the first

researchers to present a comparative study between

the digital cities of America Online, Amsterdam,

Helsinki and Kyoto. He recognized three layers in

digital cities architecture. The first layer is the

information layer which includes all the data from

real time sensors and files from the Internet that are

combined together through geographical information

systems (GIS). The second layer is the interface

layer which creates a virtual environment of the

cities through 3D spaces and 2D maps. The last

layer is the interaction layer where people can

communicate with each other through the use of

agent systems.

L. Anthopoulos and I.A. Tsoukalas (2006)

developed the digital city of Trikala in Greece. Their

chosen architecture consisted of five layers. The first

and last layers are user layers where we can find all

the stakeholders of a SC including the designers of

the services and end users respectively. The second

layer is the infrastructure layer which contains the

technologies, platforms and networks in order to

create and offer the services. The third layer is the

information layer which consists of all the necessary

data about SC operation, such as geospatial data and

other records. The fourth layer is the service layer

which contains all the provided applications of the

city and allowed the interaction among citizens and

organizations.

Expect from the definition that we mentioned it

previously, IBM has also stated the structure of SC.

According to IBM, the structure is divided in three

layers, perception, network and application layer.

Perception layer recognizes the device and gathers

data via sensors, GPS, RFID and other technologies.

Network layer processes those data through

components related to the intelligence and

communication capabilities of the network.

Eventually, application layer examines and

evaluates the total amount of data through advanced

technologies, such as cloud computing and fuzzy

techniques.

K. Su et al. (2011) focused in the building of SC

and recognized three stages. The first stage is the

manufacture of public infrastructure. The second

stage is the manufacture of public platform, which

includes network infrastructure, cloud computing

platform and sensor networks. The third stage is the

manufacture of application systems, which includes

some basic applications like the construction of

wireless city, smart home, smart public services and

social management, smart transportation, smart

medical treatment, smart urban management, green

city and smart tourism.

J. Carretero (2012) developed an architecture

named ADAPCITY. It is about a self-adaptive

system for SC which offers heterogeneous devices

the ability to react effectively in environmental

changes and adapt their behavior according to the

new conditions. Moreover, the system is able to

recover immediately and update its operations, even

create new ones. The proposed architecture is

divided in four layers. The physical layer includes

the state and behavior of devices and objects. The

grid layer includes the process, storage and

communication among the data come from physical

layer. The management layer uses statistics, data

mining and prediction techniques to manage the

processed data from grid layer. Finally, the control

layer includes the provided services taking into

account users desires and optimization

measurements.

Finally, l. Vilajosana et al. (2013) presented a

generic architecture after observing many existing

platforms and combining their common features.

SMARTGREENS2015-4thInternationalConferenceonSmartCitiesandGreenICTSystems

The capillary network layer in the bottom of the

platform includes sensors and actuators for data

collection, data warehouses for storage of historical,

real-time and metadata, as well as database nodes

and security infrastructures for data management

and control offering. The service layer has the

responsibility to receive the incoming data from

capillary network layer and then to process, combine

and secure them. It manages different types of data,

such as big, open and streaming data and also

analytics services. The last layer is the application

layer where the data are analyzed and converted into

useful information, which is eventually provided to

people through predefined interfaces.

2.2 Service Oriented Architecture

(SOA)

SOA is an approach that aims in collection,

communication and interaction between services and

in their provision to the users taking into account

their needs and requests. The communication

between different services in a computer system is

implemented through data exchange among them

and the ability of each service to act as a whole

activity on behalf of another service. Every

interaction is considered to be unconstrained since

services are unrelated, loosely coupled and self-

sufficient. However, according to D. Sprott and L.

Wilkes from Microsoft (2004), SOA is more than

this. In fact, it is a pattern that includes all the

necessary practices and frameworks to offer people

the right services that fit to their preferences through

the interface.

One of the most underlying works was that of L.

Anthopoulos and P. Fitsilis (2010) who tried to

create a common architecture for SC called

Enterprise Architecture. Their approach is based on

SOA and contains information of urban

development and service delivery in urban

environments. Logical and physical architecture has

been combined with the enterprise architecture in

order to strengthen the evolution of SC. As authors

admitted, the case of Trikala failed to meet some of

the challenges that SC have to face (such as

information sharing and storage, connection and

access through broadband networks, simulation of

daily life and so on) with the primary architecture,

so they developed this one in an attempt to

overcome the existing problems.

2.3 Event Driven Architecture (EDA)

EDA is a framework that deals with the creation,

identification, utilization and response to events.

These events are usually uncommon, extraordinary

and related to uncertain changes and asynchronous

conditions. The result of the actions that EDA

executes, provokes the generation of event

notifications (and not of an event), which are

actually an effect of change occurrence. A change

can be detected by sensors and the outcoming events

can be processed by the system. EDA is loosely

coupled about the unknown results of a change by

the event itself but it is tightly coupled to the

semantics of an event. When the semantic

heterogeneity of events is high, it is very difficult to

implement that architecture in a SC (H. Souleiman et

al., 2012). EDA can be also combined with SOA

since an event can make a service operative.

Moving in that direction, L. Filipponi et al.

(2010) developed SOFIA project in an attempt to

monitor the public city places in order to enhance

security and detect emergency cases and abnormal

situations. This project is based on EDA that permits

sensors (and especially wireless sensors networks) to

observe unusual events. The main components of the

architecture are Semantic Information Brokers (SIB)

and Knowledge Processors (KP). All the data about

smart places are stored in SIB. In the sequel, KPs

receive these data from SIB, have access to them,

generate and use notifications for the events

described by them. The joint action between SIB and

KP, leads to the production of Interoperability Open

Platform (IOP), which gives applications the

opportunity to gain entry to data and share them.

2.4 Internet of Things (IoT)

IoT is a paradigm that combines a large amount of

heterogeneous devices, which are connected to the

Internet and can identify themselves through IP

addresses and protocols. All devices are embedded

with sensors and actuators and are usually wireless

connected to the network. IoT enables the

connectivity and communication between sensors

and deploys the incoming information in order to

provide various applications to the people. Radio-

frequency identification (RFID) is considered to be a

prerequisite of IoT since it is believed that all things

of our daily life could be identifiable with the use of

radio tags. Cloud computing, which is actually a

different term for Internet, has the duty of sharing

computational resources and offering services to

devices via the Internet without having in fact

hardware equipment to manage applications. These

technologies are commonly used together and

managed to become an inspiration source for many

researchers whose works are related to SC.

SmartCityTechnologiesandArchitectures-ALiteratureReview

To begin with H. Schaffers et al. (2011) who

considered SC as open access environments that are

designed according to users’ preferences. In order to

create innovative services, the use of Future Internet

technologies seems to be important as enabling the

development of applications based on IoT.

Furthermore, Living Labs methodologies played a

useful role in that direction since they shows the way

of organizing and coordinating innovative services

and projects. A similar approach was followed by

I.P. Chochliouros et al. (2013), who explained the

concept of Living Labs and the benefits of their

implementation in SC facilities, and also highlighted

their contribution in the evolution of Future Internet

platforms.

A. Attwood et al. (2011) developed the

framework of SC Critical Infrastructure (SCCI)

which aimed to protect critical infrastructures from

failure or help the system to continue its function if a

failure was unavoidable to happen. In order to detect

the state of critical infrastructure, to help system

recover, extract the conditions and make a change,

the use of sensor actuator networks (SAN) is

necessary, according to the researchers. SAN

connects itself to the IoT so as to collect the data that

are useful for the SC and integrate city components

that should use an information aggregation utility.

The amount of the collected data is usually so big,

that the system should process them itself without

human intervention. Semantic Web undertakes the

role to take these data, give them meaning and

specify the relationships between them, which are

widely known as linked data. Cloud computing in its

turn, used the service model of Infrastructure as a

Service (IaaS) to access the data and process them in

real-time. Based on these requirements and

technologies, researchers developed the basic

elements of SCCI, which are Smart Cities Systems

Annotation and Aggregation Service, Critical

Response Reasoning Instance, Critical Response

Visualization and Control and finally Sensor

Actuator Network Overlay State Management.

P. Ballon et al. (2011) created a European

Platform for Intelligent Cities (EPIC) with the

intention to be implemented in all European Cities.

Their goal was to evaluate the use of cloud platform,

Living Labs and e-Government in a pan-European

level and examine the satisfaction of requirements

and challenges that a SC has to face. The EPIC

integrates the technologies of cloud computing, IoT

and semantic Web. Specifically, EPIC used IBM’s

Test and Development Cloud so as to facilitate

public sector to accept the change and the innovation

of the cloud. IoT can enable geospatial positioning

and 3D display through the use of sensor and RFID.

Finally, the semantic layer of the EPIC includes the

Command and Control Lexical Grammar (CCLG)

technology to solve the problem of the multiple

spoken languages in European countries.

E. Asimakopoulou and N. Bessis (2011) focused

their research on disaster management using crowd

sourcing techniques to create smart buildings.

Through crowd sourcing technology, citizens

participate in the detection of emergency events and

hazards using APIs in their mobile phones. The role

of citizens is enhanced by sensors and critical

infrastructures in cars and buildings that explore

their environment too. Other technologies that were

proposed by the researchers were grid computing to

integrate heterogeneous resources, cloud computing

to enable access in these resources and pervasive

computing to collect and handle data from devices.

R. Wang et al. (2012) presented how to use

World Wind geographic software developed by

NASA to 3D reconstruct a city. It is about an open

source platform which allows visualization,

simulation and interaction in all sectors of living in a

SC. The two main components of this technology

are data collection and visual display. The data are

collected through IoT, network analysis and web

map services. Their visual display is feasible

through KMZ files for 3D models which are

grounded on KML patterns.

Q. Ye et al. (2012) discussed the architecture of a

Smart Sport information system giving emphasis to

the including technologies, such as body sensor

networks, IoT, cloud computing and data mining. In

more detail, the body sensors have the duty to

collect data concerned with the health and daily

routine of an athlete. Cloud computing is used as the

middleware to allow transfer and management of the

data. Data mining and other techniques, such as

mathematical models and artificial intelligence, are

used to process and analyze the data so as to get the

necessary information. Last but not least, with the

contribution of the IoT and the development of

software and hardware, that information is converted

into useful applications.

J. Jin et al. (2012) analyzed four network

architectures based on the IoT that could be

implemented in a SC. The first architecture is the

Autonomous Network Architecture, where users can

access the network with or without Internet

connection. The second is the Ubiquitous Network

Architecture, where users access the Internet to find

the expected information since radio technologies,

wireless sensors and vehicular ad hoc networks are

integrated to the Internet. The third is the

SMARTGREENS2015-4thInternationalConferenceonSmartCitiesandGreenICTSystems

Application Layer Overlay Network Architecture,

which is capable of reducing the amount of collected

data through the IoT by selecting the more useful

ones. The last is the Service Oriented Network

Architecture, where researchers presented the

example of the IDRA platform, which was

developed by E.D. Poorter et al. (2011).

N. Mitton et al. (2012) examined the

combination of cloud with sensors and actuators

empowering by the IoT. This approach is named

“Sensing and Actuation as a Service (SAaaS)

following the names of the other types of cloud

computing services. In their system, a SC is divided

in sites. Each site is considered to be an autonomous

system which contains sensors for information

gathering and clients as information consumers. The

collected information is stored in the Database

Manager of the site from where it can be published

to users after their request or can be distributed to

the other sites if there is a need. The operation of

this system is feasible via implementing the

proposed schema and modules architecture, which

consists of three elements, Hypervisor, Autonomic

Enforcer and Volunteer Cloud Manager. The

Hypervisor is used to abstract sensors from single

devices or even from networks. The Adapter

facilitates the communication between the devices.

The Autonomic Enforcer is the mediator between

the above modules and the SAaaS Cloud, exploiting

their resources and converting them into applications

using IoT capabilities. The Volunteer Cloud

Manager concentrates these resources and

applications in the cloud and develops strategies

after monitoring the connectivity among the devices.

A similar study was undertaken by S. Distefano

et al. (2013). The researchers kept the basic elements

of the above framework and went further by

distinguishing two phases in the architecture. The

first phase was SAaaS provisioning system and

infrastructure setup and the second phase was the

SAaaS application setup.

G. Suciu et al. (2013) proposed the framework

SlapOS, which combined cloud and IoT

architectures, as a mean for designing SC.

According to the researchers, the necessary features

of building a SC are sensor networks and open

source cloud platforms. Their framework integrates

these technologies and has also the ability to transfer

and offer IoT applications through the use of cloud

middleware.

M. Roscia et al. (2013) presented a model for SC

that was called Intelligent Distributed Autonomous

SC (IDASC). IDASC involves multi-agent systems

and IoT to enable observation, audit and

performance of the system. It also integrates ZEUS

framework to ensure functionality and

communication between the agents.

C. Samaras et al. (2013) developed SEN2SOC

platform to be implemented in the SmartSantander

City of Spain. Their aim was to enhance the

interaction between sensor and social networks

through the use of Natural Language Generation

(NLG) system in order to improve citizens and

visitors experience in living in a SC. The

architecture of SEN2SOC platform is component-

based and includes mobile and web applications

(IoT) to facilitate users login, support their

navigation in city routes and promote feedback,

sensor and social data monitoring to collect data

from sensor and social media networks and detect

anomalies in the environment, statistical analysis to

process the income data and export the results from

this action, and interface to allow communication

between the components. The NLG system, which is

embedded in the platform, has the ability to receive

information from sensors and convert it into

messages that can be easily understood by humans.

G-J. Horng (2014) designed a system for smart

parking in order to facilitate citizens in finding

parking spaces easily and quickly and help in

reducing fuel congestion and air pollution. The

architecture is based on an Adaptive

Recommendation Mechanism, which includes

various technologies in order to allow system’s

implementation. In more detail, it uses wireless

sensor networks so as to search the existence of

vehicles near a parking space. Then, an Internal

Recommendation Mechanism of the specific place

informs the Parking Congestion Cloud Center

(PCCC) which with its turn transmits these data to

the Cloud Server. Finally, the user receives the

desirable information through his/hers mobile

device, which in the same time acts as a sensor for

the Cloud Server.

2.5 Combined Architectures

Except from the perspectives that we analyzed above

and the presentation of the most underlying works

that have been already published in the literature,

there is also the perspective of combined

architectures, which manages to integrate

characteristics and technologies of the

abovementioned ones. It is a common phenomenon

for researchers to mix technologies and platforms in

order to create an architecture that can probably be

implemented in a SC. In this section, we cite some

of these works distinguishing them in categories.

SmartCityTechnologiesandArchitectures-ALiteratureReview

2.5.1 IoT – AL

Z. Khan and S.L. Kiani (2012) presented a cloud-

based architecture for improving services and

applications offered to citizens of SC. According to

the researchers, citizens act as providers of data

through the use of their mobile phones, and also as

consumers of the developing services after

processing the collected information. The proposed

architecture which is based on a cloud environment

is divided in seven layers (five horizontal and two

vertical) and contains the context-awareness

element. The first layer is the platform integration

layer which contains the cloud technology and

facilitates the access to all kinds of information. The

data acquisition and analysis layer enables data

collection and includes the context-awareness

element to separate useful data from non-useful ones

and synthesizes them together. The thematic layer

categorizes data in sections according to their

context. The service composition layer specifies the

origin of data and contains the context-awareness

element to state the workflows among corresponding

services. The application service layer enables

modeling and visualization of data to create

applications that meet end users requirements. The

management and integration layer manages the flow

of data so as to ensure that only useful and related

data are shifted from one layer to another. Finally,

the security layer certifies the authentication of data

and their use from authorized users.

Y. Wang and Y. Zhou (2012) presented an

abstract study about the use of cloud computing with

Near Field Communication (NFC) technology in SC.

NFC is a card embedded in mobile devices, which is

based on Internet and RFID technology. Its role is to

promote user confirmation, data transmission,

distant payments and public information. The

researchers distinguished three basic layers in the

cloud architecture of NFC application, which were

user information storage layer, device information

layer and process layer. Process layer included six

other layers, from which researchers chose to

discuss in more detail the resource scheduling layer.

R. Szabó et al. (2013) built a framework using

Extensible Messaging and Presence Protocol

(XMPP) to collect data from citizens’ mobile

devices. Their intention was to enhance participatory

sensing while creating and operating SC

applications. This knowledge is considered to be

real-time big data that are processed by the IoT. The

first scale of the framework’s architecture is based

on the publish - subscribe feature of the XMPP,

which give users the opportunity to take part in

information gathering (publish) and enjoy the

updating applications after this action (subscribe).

The second scale of the architecture is the analytics

component, which is distributed in layers in order to

anticipate citizens’ mobility. According to the

researchers, these layers are streaming, persistence,

serialization, caching, mobile data processing and

users defined functions layers and include platforms

and technologies that can facilitate data processing

and system’s recovery after a failure.

Q. Zhang et al. (2013) examined the use of IoT

in the food industry of a SC. Especially, they

focused in the creation of an IoT system, which can

observe, control and analyze the food supply chain

so as to offer citizens protection of consuming

contaminated or polluted products. The logic

architecture of IoT is divided in four layers, data

collection and management layer, intelligent

processing layer, graphic representation layer and

self-correction layer, each of which includes specific

algorithms and metrics techniques. The collection of

data from sensor networks is feasible through the

Self-adaptive Dynamic Partition Sampling (SDPS)

strategy in an attempt to eliminate the portion of

sample of products that need to be examined so as to

enhance the effectiveness of the procedure and the

accuracy of the control. Furthermore, the researchers

implemented a tracing algorithm to discover the

origin of the pollution and a backtracing algorithm

to withdraw polluted products that could not be

traced in the supply sequence.

L. Sánchez et al. (2013) presented the

architecture of SmartSantander city in Spain. Their

aim was to find the necessary technologies and

platforms based on the IoT to develop a common

context for all SC. Their proposed architecture

consists of three layers which are IoT device layer,

gateway layer and server layer. The IoT device

layer has the duty to estimate the number of the

connected devices to the network and facilitates their

heterogeneous nature through the use of mobile

phones, RFID and other technologies. The gateway

layer allows the communication and connectivity

between the devices and the network. The server

layer enables the access of users in the system by

offering high level scalability and availability to the

servers. Except from the layers, the architecture is

also divided in four subsystems, each of which

provides information about its embedded

functionalities and is accessible by specific groups

of people. Briefly, these subsystems are

Authentication, Authorization and Accounting,

Testbed Management, Experimental Support and

Application Support subsystem.

SMARTGREENS2015-4thInternationalConferenceonSmartCitiesandGreenICTSystems

2.5.2 IoT - SOA

F. Andreini et al. (2011) proposed an architecture

infused by the notion of SOA, which combined IoT

and geo-localization in order to promote access in

SC services. Researchers emphasized in the term of

scalability which could be achieved by using the

Distributed Hash Table (DHT) protocol.

M. Hu and C. Li (2012) proposed the use of 3S

and IoT for the creation and design of a SC. The 3S

technology is associated with geospatial information

(RS, GPS, GIS) for accurate positioning, with 3D

visualization for city construction, with sensor

networks for incessant observation, and with DPGrid

and GPU (Graphics Processing Unit) technologies

for real time processing of data. IoT is thought to be

associated with RFID, barcodes and 2D codes

technologies for allowing computational systems

identify things of daily life, with sensor web for

space monitoring, with SOA for managing

geospatial data, and with grid and cloud computing

for allowing access to services through the use of

Internet and wireless networks.

2.5.3 IoT - SOA - AL

Z. Xiong et al. (2014) introduced a novel

architecture of Data Vitalization (DV) in order to

indicate a more effective way of managing the

heterogeneous incoming data from sensors. DV

architecture, which is divided in cells (master, data

and special cells), mainly uses the technologies of

SOA and cloud computing. An application of DV is

the Smart Service Platform (SSP), which

architecture distinguishes into four layers-data

gathering and storage layer, supporting layer for

DV service, application layer for DV and

application Layer for development. Data gathering

and storage layer collects and stores data in

particular cells, while supporting layer for DV

service processes these data. These two layers

constitute of the data cell, which is applied by a

virtual machine and their framework is the

infrastructure as a service (IaaS) cloud computing

services type. The other two application layers for

DV and development concern both end users and

developers, since they offer users the desirable

applications, users can react as sensors and collect

data from their devices and also developers can

exploit APIs and create new services. The

implemented technologies are virtual machine

manager in the third layer and platform as a service

(PaaS) cloud computing services type in the latter.

2.5.4 IoT - EDA

Based on the EDA of the SOFIA project, J. Wan et

al. (2012) discussed the implementation of Machine

to Machine (M2M) communications in order to

improve SC’s applications. M2M technology has the

ability to facilitate the connection between people,

computers and mobile devices, and also sensors and

actuators. According to the researchers, in order to

maximize the efficiency of the SC system, M2M

communications need to be combined with Internet,

sensors, networks and cloud computing, and further

with KPs and SIBs.

2.5.5 IoT- SOA -AL - EDA

R. Wenge et al. (2014) proposed an architecture for

SC from the perspective of data management. Their

architecture is divided in six layers – data

acquisition layer, data transmitting layer, data

storage and vitalization layer, support service layer,

domain service layer and event-driven application

layer. The data acquisition layer gathers the data

coming from sensor networks and other sources, like

RFID technology and system on a chip (SoC). The

data transmitting layer integrates the technologies of

wireless networks and ultra wide band in order to

facilitate users with Internet access. The data storage

and vitalization layer focuses on clarification,

correlation, sustainment, development and storage of

data using the Internet of data technology (IoD) that

is similar to the IoT and also cloud computing. The

support service layer emphasizes in data

management and provision to the users through SOA

architecture, cloud platforms, visualization and

simulation technologies. The domain service layer

concerns every single sector of the SC and tries to

integrate them together in order to enhance citizens’

experience. Ultimately, the event-driven application

layer stresses on citizens requirements and tries to

offer them applications that satisfy their needs.

2.6 Internet of Everything (IoE)

IoE is a future perspective which is being designed

to extend, overcome and substitute the IoT. Cisco

defines the IoE for SC as the technology that

connects people, process, data and things in order to

improve the livability of cities and communities. IoE

provides not only computing devices but every

object (everything) with the capability of high

connectivity and intelligence so as to operate various

facilities. IoT based its function in the great number

of the connected objects. Nevertheless, IoE operates

SmartCityTechnologiesandArchitectures-ALiteratureReview

via the deployment of networks that have the ability

to transport all the collected and created information

by these objects and also facilitates the connection

of many more objects even if every object. In other

words, IoE flags a new and innovative era when

smart objects are connected together and everyone

Table 1: Smart City Architectures and Technologies.

Researchers Research Area Architectures Technologies

T. Ishida (2000)

Digital cities of America,

Amsterdam, Helsinki & Kyoto

Sensors, Internet files, GIS, 3D/2D

spaces and maps, agent systems

L. Anthopoulos and I.A.

Tsoukalas (2006)

Digital city of Trikala AL

Networks, geospatial data

IBM (2010) SC structure AL

Sensors, GPS, RFID, networks, cloud

computing, fuzzy techniques

K. Su et al. (2011) SC manufacture AL Network infrastructure, cloud, sensors

J. Carretero (2012) ADAPCITY AL

Data mining, statistics, prediction &

optimization measurements

I. Vilajosana et al. (2013) Generic architecture for SC AL

Sensors, actuators, data warehouses,

security infrastructures, interface

L. Anthopoulos and P. Fitsilis

(2010)

A common architecture –

Enterprise Architecture

SOA

Logical and physical architecture,

service delivery

L.Filiponi et al(2010) SOFIA Project EDA Sensors networks, SIBs, KPs, IOP

H. Schaffers et al. (2011)

SC and the Future

Internet

IoT IoT, Living Labs

I.P. Chochliouros et al. (2013) Living Labs in SC IoT IoT, Living Labs

A. Attwood et al. (2011) SC Critical Infrastructures IoT

IoT , Sensor actuator networks, Semantic

Web, IaaS

P. Ballon et al. (2011)

European Platform for

Intelligent Cities

IoT

Test &Development Cloud, Living Labs,

Semantic Web, RFID, sensors, CCLG

E.Asimakopoulou and N.Bessis

(2011)

Disaster Management and

smart buildings

IoT

Crowd sourcing, sensors, grid, cloud and

pervasive computing

R.Wang et al. (2012)

World Wind for 3D

reconstruction of SC

IoT IoT, networks, web maps, KMZ files

Q. Ye et al. (2012) Smart Sports IoT Body sensor network, cloud, data mining

J. Jin et al. (2012) SC Network Architectures IoT IoT

N. Mitton et al.(2012) Cloud and sensors in SC IoT IoT, SAaS

S. Distefano et al. (2013) SAaaS in SC IoT IoT, SAaS

G. Suciu et al. (2013) SlapOS IoT IoT, open source cloud platform, sensors

M. Roscia et al. (2013)

Intelligent Distributed

Autonomous SC

IoT

IoT, multi-agent system, ZEUS

framework

C. Samaras et al. (2013) SEN2SOC platform IoT

IoT, Natural Language Generation,

sensor and social networks

G.J. Horng (2014) Smart Parking IoT

IoT, adaptive recommendation

mechanism, wireless sensors, cloud

Z. Khan and S.L. Kiani (2012)

Cloud for citizens services in

IoT – AL

IoT, cloud, context-awareness

component

Y. Wang and Y. Zhou (2012) Cloud based on NFC in SC IoT – AL IoT, cloud computing, NFC card, RFID

R. Szabó et al. (2013) Participatory sensing IoT – AL IoT, XMPP, analytics component

Q. Zhang et al. (2013) Smart Food Supply Chain IoT – AL

IoT, sensor networs, SDPS, tracing and

backtracing algorithms

L.Sánchez et al(2013) SmartSantander IoT – AL IoT

F.Andreini et al(2011) Geo-localized services in SC IoT – SOA IoT, wireless sensors, SOA, DHT

M.Hu and C. Li (2012) SC design IoT – SOA

3S, GPS, 3D, sensors, DPGrid, GPU,

RFID, 2D code, cloud, grid computing

Z. Xiong et al. (2014) Data vitalization in SC

IoT – SOA –

IoT, SOA, sensor networks, IaaS, PaaS

J. Wan et al. (2012) M2M communications in SC IoT – EDA IoT, sensors, actuators, cloud, KPs, SIBs

R. Wenge et al. (2014)

SC architecture from data

management perspective

IoT – SOA –

EDA – AL

IoT, sensors, RFID, SoC, wireless

networks, ultra wide band, IoD, cloud,

visualization & simulation technologies

SMARTGREENS2015-4thInternationalConferenceonSmartCitiesandGreenICTSystems

from everywhere and at anytime can have access to

them. Cisco clarifies the exact procedure that IoE

follows. More specifically, IoE exploits the Internet

infrastructure and connection networks, manages in

an effective way the incoming information from

devices, creates applications that can satisfy citizens’

requirements in both public and private sectors and

makes networks less complex through the use of

APIs. Cisco plans aim to the opening of a global

innovation centre for IoE in Barcelona by the mid-

2016 like the ones that already exists in Brazil and

South Korea and those that under construction in

Germany and Canada. The purpose of those centers

is to operate as the examples of introducing a

common pattern when designing new applications

for SC that are in the initial stages of creating urban

facilities. For the time being there are not published

use cases for that perspective.

3 DISCUSSION

Above we enumerate many architectures and

technologies that have been proposed in the

literature in order to find implementation in the

whole SC system or in a SC sector. In this section,

we will discuss them and try to determine these

platforms that are more useful when designing a SC.

The AL perspective was one of the first to be

applied by researchers if we consider the

comparative study of T. Ishida between the digital

cities of America Online, Amsterdam, Helsinki and

Kyoto in 2000. The implementation of this

perspective gave researchers the opportunity to

modify features in different layers without having to

change the whole system. As we recognized from

the previous analysis, each researcher made a

different proposal of a set of layers since there was

not any specification agreed on the layer formation.

Even today there is still not a standard pattern to

follow when choosing to implement this

architecture. It is remarkable that L. Anthopoulos

and I.A. Tsoukalas who developed the digital city of

Trikala in 2006, admitted that they failed to meet

city’s challenges with the existing architecture. The

integration of more sophisticated technologies, such

as sensors, actuators, GPS, cloud and so on managed

to enhance layers’ functionality. IBM opened the

way with the definition of SC structure and its

including technologies. The contribution of J.

Carretero (2012) was also important since he added

the characteristic of self-adaptation while creating

the ADAPCITY system. Furthermore, I. Vilajosana

et al. (2013) proposed a generic layer architecture

presenting the key platforms and technologies to

support SC applications. This architecture offers lots

of benefits in designing a system since it can make it

more flexible to changes and each change can affect

only one layer and not the others. Furthermore, the

separation of the SC system into layers facilitates the

implementation of reusable components, while the

component distribution helps the system to be more

scalable and reliable. No serious technology

restrictions have been noticed while implementing

this architecture. The effectiveness of this

perspective will be improved, if it is combined with

more advanced technologies or even another

perspective. This attempt is really valuable when

building a SC since the system can better respond to

all challenges and requirements.

The SOA perspective takes into account citizens’

needs and preferences and tries to provide them with

high quality services. These services can

communicate and interact with each other while

being independent and loosely coupled. L.

Anthopoulos and P. Fitsilis (2010) used this

architecture in order to improve the city system of

Trikala and in an attempt to create a common

architecture for SC. The implementation of this

perspective fits very well with the purpose of a SC

which is to offer citizens the right services that

satisfy their needs. Service orientation seems to be

one of the most useful architectures since its

functionality offers a great number of advantages

such as flexibility, service re-use, ability to create

both new functions and combinations of functions.

However, there are still issues to be solved

concerning the complexity, performance and cost of

the designing system. SOA functionality can be

enhanced if it is combined with IoT.

The EDA perspective has the ability to identify

an uncommon situation and respond to unusual

events. This feature is very expedient in cases of

crowd sourcing and monitoring public spaces in SC.

L. Filipponi et al. (2010) developed SOFIA project

in order to ensure citizens security. A subway station

use case, facilitated by SOFIA infrastructure, was

implemented to prove the effectiveness of the

architecture in detecting abnormal events. However,

the basic disadvantage of this perspective is that it

can not respond properly when the events are

characterized with great heterogeneity (H.

Souleiman et al., 2012). One solution could be the

combination with SOA since an event can trigger the

operation of a service. Another solution could be a

combination with IoT since the existence of sensor

networks can enhance the efficiency of EDA.

The IoT perspective is the most common

SmartCityTechnologiesandArchitectures-ALiteratureReview

approach used nowadays considering the number of

published works in that domain. Internet is also

related to sensor networks and cloud computing,

technologies that are considered to be necessary

when collecting, managing and storing information

for developing SC’s applications. However, some

researchers made modifications in the features of

these technologies to fulfill the requirements of their

systems. For instance, both N. Mitton et al. (2012)

and S. Distefano et al. (2013) used the approach of

Sensing and Actuation as a Service (SAaaS). The

first researcher presented the case study of a SC and

the latter the use cases of smart traffic control and

smart surveillance systems respectively. Other

researchers added extra technologies to the

abovementioned ones for improving the functionality

of their systems. More specifically, P. Ballon et al.

(2011) incorporated the technology of Command and

Control Lexical Grammar in the EPIC framework

which is already implemented in the SC of Brussels,

Issy-les-Molineaux, Manchester and Tirgu Mures in

Romania still studying its impact and implementation

results. Furthermore, C. Samaras et al. (2013) added

the technology of Natural Language Generation in

SEN2SOC platform and illustrated two significant

scenarios including citizens and city authorities.

Another group of researchers used these technologies

for developing applications for one SC sector and not

for the whole SC system. For example, Q. Ye et al.

(2012) dealt with smart sport applications presenting

the cases of smart stadiums, smart shoes, smart

athletes and smart fitness. G-J. Horng (2014)

designed an adaptive mechanism for smart parking,

the effectiveness of which was proved via a

simulation test. R. Wang et al. (2012) dealt with 3D

city reconstruction through the use of World Wind

software showing three implementation scenarios of

Lujiazui city, weather data and subway lines. The

general idea that came out of this analysis is that this

perspective is really valuable since it can gather data

from citizens’ devices and external sensors, transfer

and process them via the Internet, create applications

that fit to citizens needs and finally store these

applications in the cloud to eliminate the waste of

resources. This architecture is suitable for SC

development considering all of the above-mentioned

features and can be implemented alone or combined

with another perspective. However, attention is

required in terms of privacy and security of citizens’

information and personal data since all of them are

stored in the internet and are vulnerable in hacking

and stealing. It is worthwhile to mention that

scientific community tries to extend IoT and enhance

its functionality with new features, creating the new

Internet of Everything.

The combined architectures perspective is

possibly the most appropriate for building SC since

the integration, communication and connectivity

between various technologies can help in the creation

and easy management of more advanced

applications. After a careful study we realized that

Internet technologies are the key components to all

architectures. Researchers combined them with AL,

SOA and EDA. Combining IoT with AL was the

primary choice of R. Szabó et al. (2013) who dealt

with participatory sensing presenting three use case

applications, concerning crowd sourcing based on

public transport, soccer events and university campus

all of which are still under development. Also, Q.

Zhang et al. (2013) dealt with the use of IoT in food

industry and highlighted two cases, one general and

one including big data, proving the efficiency of

SDPS strategy, tracing and backtracking algorithms.

However, F. Andreini et al. (2011) preferred to

combine IoT with SOA and presented a use case for

proving the effectiveness of their proposed

architecture. An extraordinary attempt was done by

Z. Xiong et al. (2014) who combined IoT with SOA

and AL to create a Data Vitalization architecture so

as to find a way of better managing the incoming

data from sensors presenting the social hotspots

sense use case. Finally, equally significant was the

work of J. Wan et al.(2012) who extended the EDA

of SOFIA project by adding the M2M

communications technology combined with IoT and

sensor networks showing a case study for vehicular

networks.

As a matter of fact, the combination of the

perspectives can help the SC system to gain the max

of its effectiveness by offering citizens the desirable

applications, avoiding failures or recovering

immediately in case of one and detecting for

abnormal events enhancing citizens’ security.

4 CONCLUSIONS AND FUTURE

WORK

In this paper we presented and discussed many

architectures and technologies that have been

proposed in the literature in order to design and build

a SC system or a SC component. We cited and

analyzed various works that belonged to different

perspectives, such as AL, SOA, EDA, IoT and

combined architectures. We also mentioned the

embedded technologies of these perspectives.

SMARTGREENS2015-4thInternationalConferenceonSmartCitiesandGreenICTSystems

Finally, we summarized these works in a table and

evaluated each perspective separately.

Based on the above analysis, we deduce that the

perspective of AL was preferred by many researchers

even though the chosen layers varied among their

works. In most cases, researchers combined them

with Internet technologies in order to enhance the

functionality of each layer. SOA was also selected to

be applied in SC since it distinguishes the city in

different components which offer all kinds of

services to the citizens. Considering the number of

published works in the literature, we can easily

determine that AL were mostly preferred for

implementation than SOA. In the sequel, EDA

implementation was only observed to one European

project. On the contrary, IoT is the new trend in SC

development and many recommendations about its

implementation have been published until today. Its

association with sensor networks and cloud

computing amplifies its acceptance and choice by

researchers. In recent years there is the tendency to

combine IoT with the other perspectives to improve

the functionality of the SC system. The most

common combination is IoT with AL in which

researchers used to add extra technologies to enhance

system’s capabilities. The combination of IoT with

SOA was chosen to facilitate geolocalization matters

and offer citizens the right services according to their

requirements. Finally, the combination of IoT with

EDA was selected for improving the functionality of

the SOFIA European project by adding Internet

technologies to the proposed architecture. There were

also remarkable attempts that tried to combine

together three or even all the abovementioned

perspectives to empower SC with the advantages that

each of them can offer to the citizens.

In the future, IoE intends to launch a new era in

SC development. Its purpose is to extend the

capabilities of IoT and create a common pattern in

designing applications for SC that are in the initial

stages of building their infrastructure and developing

their services. Even if it is not implemented yet, it is

expected to offer lots of capabilities to the citizens in

order to improve their experience in the SC. As a

matter of fact, IoE seems to be a promising

architecture since it aims to totally change the

economy, society and our way of living.

REFERENCES

Caragliu, A., Del Bo, C. and Nijkamp, P. (2011). ‘Smart

cities in Europe’. Journal of Urban Technology, vol.

18, issue 2, pp. 65–82.

Cocchia, A. (2014). ‘Smart and Digital City: A Systematic

Literature Review’. Springer, pp 13-43.

Su, K., Li, J. and Fu, H. (2011). ‘Smart City and the

Applications’. IEEE International Conference on

Electronics, Communications and Control, pp. 1028–

1031(IEEE Xplore).

Giffinger, R., Fertner, C., Kramar, H., Kalasek, R., Pichler-

Milanovic, N. and Meijers, E. (2007). ‘Smart Cities:

Ranking of European medium-sized cities’. Vienna:

University of Technology.

Ishida, T. (2000). ‘Understanding digital cities’. In T.

Ishida and K. Isbister Eds., Digital cities: Experiences,

Technologies and Future Perspectives, LNCS, vol.

1765, Springer-Verlag.

Anthopoulos, L.G. and Tsoukalas, I.A. (2006). ‘The

implementation model of a Digital City: The case study

of the Digital City of Trikala, Greece: eTrikala’.

Journal of e-Government, vol.2, issue 2, pp. 91-109.

Carretero, J. (2012). ‘ADAPCITY: A Self-adaptive,

reliable architecture for heterogeneous devices in

Smart Cities’. European Commissions-ICT Proposers.

Vilajosana, I., Llosa, J., Martinez, B., Domingo-Prieto, M.

and Angles, A. (2013). ‘Bootstrapping Smart Cities

through a Self-Sustainable Model Based on Big Data

Flows’. IEEE Communications Magazine, vol.51, issue

6, pp. 128-134 (IEEE Xplore).

Anthopoulos, L. and Fitsilis, P. (2010). ‘From digital to

ubiquitous cities: defining a common architecture for

urban development’. IEEE 6th International

conference on Intelligent Environments, pp. 301–306.

Filipponi, L., Vitaletti, A., Landi, G., Memeo, V., Laura,

G. and Pucci, P. (2010). ‘Smart City: an EDA for

Monitoring Public Spaces with Heterogeneous

Sensors’. IEEE 4th International conference on Sensor

Technologies and Applications, pp 281–286.

Schaffers, H., Komninos, N., Pallot, M., Trousse, B.,

Nilsson, M. and Oliveira, A. (2011). ‘Smart Cities and

the Future Internet: Towards Cooperation Frameworks

for Open Innovation’. J. Domingue et al. Eds.: Future

Internet Assembly, LNCS 6656, pp 431–446, Springer.

Chochliouros, I.P., Spiliopoulou, A.S., Sfakianakis, E.,

Georgiadou, E.M. and Rethimiotaki, E. (2013). ‘Living

Labs in Smart Cities as Critical Enablers for Making

Real the Modern Future Internet’. L. Iliadis, H.

Papadopoulos and C. Jayne Eds.: EANN 2013, Part II,

CCIS 384, pp 312–321, Springer.

Attwood, A., Merabti, M., Fergus, P. and Abuelmaatti, O.

(2011). ‘SCCIR: Smart cities critical infrastructure

response framework’. IEEE Developments in E-

systems Engineering, pp. 460-464.

Ballon, P., Glidden, J., Kranas, P., Menychtas, A., Ruston,

S. and Van Der Graaf, S. (2011). ‘Is there a need for a

cloud platform for European Smart Cities?’.

eChallenges e-2011 Conference Proceedings Paul

Cunningham and Miriam Cunningham (Eds) IIMC

International Information Management Corporation.

Asimakopoulou, E. and Bessis, N. (2011). ‘Buildings and

Crowds: Forming Smart Cities for more effective

disaster management’, IEEE Fifth International

Conference on Innovative Mobile and Internet Services

SmartCityTechnologiesandArchitectures-ALiteratureReview

in Ubiquitous Computing, pp. 229-234.

Wang, R., Jin, L., Xiao, R., Guo, S. and Li, S. (2012). ‘3D

Reconstruction and Interaction for Smart City based on

World Wind’, IEEE International Conference on

Audio, Language and Image Processing, pp. 953-956.

Ye, Q., Wang, Z., Qian, J., Gao, S. and Sun, Y. (2012).

‘Smart Sport-Emergence Trend of Sport Information’,

International Journal of Digital Content Technology

and its Applications, vol. 6, num 11, pp. 336-342.

Jin, J., Gubbi, J., Luo, T. and Palaniswami, M. (2012).

‘Network Architecture and QoS Issues in the IoT for a

Smart City’. IEEE International Symposium on

Communications and Information Technologies, pp.

956-961.

Mitton, N., Papavasiliou, S., Puliafito, A. and Trivedi, K.S.

(2012). ‘Combining Cloud and sensors in a smart city

environment’. EURASIP Journal on Wireless

Communications and Networking, Springer.

Distefano, S., Merlino, G. and Puliafito, A. (2013).

‘Exploiting SAaaS in Smart City Scenarios’, D-S.

Huang et al.: LNCS 7995, pp. 638–647, Springer.

Suciu, G., Vulpe, A., Todoran, G., Gropotova, J. and

Suciu, V. (2013). ‘Cloud computing and IoT for Smart

City deployments’. International Conference : CKS -

Challenges of the Knowledge Soc, pp. 1409-1416.

Roscia, M., Longo, M. and Lazaroiu, G.C. (2013). ‘Smart

City by multi-agent systems’. IEEE International

Conference on Renewable Energy Research and

Applications, pp. 371-376 (IEEE Xplore).

Samaras, C., Vakali, A., Giatsoglou, M., Chatzakou, D.

and Angelis, L. (2013). ‘Requirements and architecture

design principles for a smart city experiment with

sensor and social networks integration’. ACM

Proceedings of the 17

Panhellenic Conference on

Informatics, pp. 327-334.

Horng, G-J. (2014). ‘The adaptive recommendation

mechanism for distributed parking service in Smart

City’. Wireless Personal Communications, Springer.

Khan, Z. and Kiani, S.L. (2012). ‘A Cloud-based

architecture for citizen services in Smart Cities’.

IEEE/ACM Fifth International Conference on Utility

and Cloud Computing, pp. 315-320.

Wang, Y. and Zhou, Y. (2012). ‘Cloud architecture based

on Near Field Communication in the Smart City’.

IEEE The 7th International Conference on Computer

Science & Education, pp 231-234.

Szabó, R., Farkas, K., Ispány, M., Benczúr, A.A., Bátfai,

N., Jeszenszky, P., Laki, S., Vágner, A., Kollár, L.,

Sidló, Cs., Besenczi, R., Smajda, M., Kövér, G.,

Szincsák, T., Kádek, T., Kósa, M., Adamkó, A.,

Lendák, I., Wiandt, B., Tomás, T., Nagy, A.Zs. and

Fehér, G. (2013). ‘Framework for Smart City

applications based on participatory sensing’. 4th IEEE

International Conference on Cognitive

Infocommunications, pp. 295-300.

Zhang, Q., Huang, T., Zhu, Y. and Qiu, M. (2013). ‘A case

study of sensor data collection and analysis in Smart

City: Provenance in Smart Food Supply Chain’.

International Journal of Distributed Sensor Networks,

Vol. 2013, Article ID 382132, Hindawi Publishing.

Sanchez, L., Gutierrez, V., Galache, J.A., Sotres, P.,

Santana, J.R., Casanueva, J. and Munoz, L. (2013).

‘SmartSantander: Experimentation and Service

Provision in the Smart City’. IEEE 16

International

Symposium at Wireless Personal Multimedia

Communications, pp. 1-6.

Andreini, F., Crisciani, F., Cicconetti, C. and Mambrini, R.

(2011). ‘A scalable architecture for geo-localized

service access in Smart Cities’. Future Network and

Mobile Summit 2011 Conference Proceedings, Paul

Cunningham and Miriam Cunningham, IIMC.

Hu, M. and Li, C. (2012). ‘Design Smart City Based on 3S,

IoT, Grid Computing and Cloud Computing

Technology’. Y. Wang and X. Zhang (Eds.): IOT

Workshop 2012, CCIS 312, pp. 466–472, Springer..

Xiong, Z., Zhengand, Y. and Li, C. (2014). ‘Data

vitalization’s perspective towards smart city: a

reference model for data service oriented architecture’.

14th IEEE/ACM International Symposium on Cluster,

Cloud and Grid Computing, pp 865-874.

Wan, J., Li, D., Zou, C. and Zhou, K. (2012). ‘M2M

Communications for Smart City: An Event-Based

Architecture’. IEEE 12th International Conference on

Computer and Information Technology, pp. 895-900.

Wenge, R., Zhang, X., Dave, C., Chao, L. and Hao, S.

(2014). ‘Smart City Architecture: A Technology Guide

for Implementation and Design Challenges’. Network

Technology and Applications, IEEE China

Communications, vol.11, issue 3, pp. 56-69.

Souleiman, H., O’Riain, S. and Curry, E. (2012).

‘Approximate Semantic Matching of Heterogeneous

Events’. In 6th ACM International Conference on

Distributed Event-Based Systems, pp. 252–263, ACM.

Online Sources:

IBM (2010). Smarter thinking for a smarter planet.

Sprott, D. and Wilkes, L. (2004). ‘Understanding Service-

oriented Architecture’. Microsoft. Available online:

http://msdn.microsoft.com/enus/library/

aa480021.aspx.

Cisco, Internet of Everything. Available at:

http://internetofeverything.cisco.com.

Cisco, The Internet of Everything for Cities, Available

online:http://www.cisco.com/web/about/ac79/docs/ps/

motm/IoE-Smart-City_PoV.pdf.

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