An Architectural Model for Intelligent Cities using Collaborative

Spatial Data Infrastructures

Aly C. S. Rabelo

, Italo L. Oliveira

and Jugurta Lisboa-Filho

Department of Informatics, Federal University of Vic¸osa, Vic¸osa, Minas Gerais, Brazil

Department of Informatics and Statistics, Federal University of Santa Catarina, Florian

opolis, Santa Catarina, Brazil

Keywords:

SDI, VGI, RM-ODP, Enterprise Viewpoint, Smart City.

Abstract:

Smart cities make intense use of information technologies to capture data in real time in order to automate

urban management and social actions. However, the implementation of this concept is hindered by its com-

plexity and limitations in cities. Using a model that contains the basic concepts of a smart city ensures such

basic concepts will be approached during speciﬁcation, besides facilitating communication among designers

and allowing the evolution of a smart city to be followed. The International Cartographic Association (ICA)

has developed a formal model for Spatial Data Infrastructure (SDI) using the Enterprise, Information, and

Computation viewpoints of the Reference Model for Open Distributed Processing (RM-ODP) framework.

Assuming that an SDI and volunteered geographic data (VGI) are key parts of a smart city, this study adapts

ICA’s formal model for SDI with basic concepts that a smart city must have. The adapted model was applied in

the speciﬁcation of the Enterprise viewpoint of a system to reduce trafﬁc congestion. The speciﬁcation enabled

exemplifying the importance of SDI and VGI in the context of a basic architecture for the implementation of

applications aiming to turn small and medium-sized cities into smart.

1 INTRODUCTION

The urbanization process has sped up in recent years

and the World Health Organization (WHO) estimates

there are currently over 7 billion people in the world

(Organization et al., 2016). According to the United

Nations (UN), half of this population lives in urban

areas and this number is expected to reach 70% by

2050 (Seto et al., 2012).

Many urban centers are not properly prepared

to handle an expressive increase in the number of

people. The main services such as safety, water,

sewage, transportation, and education, when they do

exist, are deﬁcient. Such issues require measures to

be taken in order to ameliorate the situation.

In recent decades, governments, universities,

and businesses have increased investments to create

solutions that align technology and sustainable

development. In this context, a new concept was

developed, called smart cities (Caragliu et al., 2011);

erez-Mart

ınez et al., 2013).

Some initiatives, such as in (P

erez P

erez et al.,

2013) and (Kyriazopoulou, 2015), aim to create

smart services and applications that allow cities

to become more sustainable and citizens to have

access to better, more efﬁcient services. In Brazil,

small and medium-sized cities receive less ﬁnancial

resources than large cities. That does not prevent

these smaller cities from turning into smart cities.

Thus, more incentive and investment are required

from all involved in the creation of smart services for

the cities.

Smart cities use information and communication

technologies (ICTs) as crucial tools to “detect,

analyze, and integrate base data and information to

execute the cities” (Su et al., 2011). Developing

smart cities is a complex activity since it involves

several areas and the interest of different parties. The

identiﬁcation and collaboration of actors in a smart

city allow the basic concepts of the literature to be

contemplated during the speciﬁcation process, which

helps the city’s transformation and evolution.

The Open Geospatial Consortium (OGC) deﬁnes

a smart city as “the integration of physical, digital,

and human systems to develop urban areas aiming to

create a more prosperous, sustainable, and inclusive

future” (Percivall et al., 2015). Using this deﬁnition

as a starting point, the use of spatial data infrastruc-

242

Rabelo, A., Oliveira, I. and Lisboa-Filho, J.

An Architectural Model for Smart Cities using Collaborative Spatial Data Infrastructures.

DOI: 10.5220/0006306102420249

In Proceedings of the 6th International Conference on Smart Cities and Green ICT Systems (SMARTGREENS 2017), pages 242-249

ISBN: 978-989-758-241-7

ture (SDI) combined with volunteered geographic

information (VGI) can help transform and maintain a

smart city.

The formal model for SDI of the International

Cartographic Association (ICA), developed by (Hjel-

mager et al., 2008) and later extended by (Cooper

et al., 2011), (B

ejar et al., 2012) and (Cooper et al.,

2013), allows an SDI to be speciﬁed independently of

technologies, implementations, or policies (Oliveira

and Lisboa Filho, 2015). The positive results of those

proposals allow this study to verify which changes

are required for a new heading, namely, smart cities.

This new approach is based on the extension of the

formal model for SDI including the VGI component

proposed by (Cooper et al., 2011).

The present study proposes a collaborative archi-

tectural model that combines SDI and VGI from the

Enterprise viewpoint of ISO/IEC 10746, Reference

Model for Open Distributed Processing (RM-ODP),

in order to allow small and medium-sized cities to

start their transformation into smart cities.

The remaining of the paper is structured as

follows: Section 2 presents relevant works for the

development of the research. Section 3 presents the

theory basis of this research, such as the contextual-

ization of the RM-ODP framework, the requirements

for the development of smart systems, and which

domains and indicators the systems may comprehend

in a smart city. Section 4 contains the speciﬁcation

of the Enterprise viewpoint of RM-ODP. Section

5 discusses the results reached, while Section 6

presents some ﬁnal considerations of the study.

2 RELATED WORKS

Cooper et al. (2011) developed a formal SDI model

including VGI. This model arose from previous

works targeting only SDI considering different view-

points (Enterprise and Information) of the RM-ODP

framework (Hjelmager et al., 2008). The integration

of VGI into the model is justiﬁed by the increasing

cost of ofﬁcial mapping programs and by the large

availability of citizen-generated data.

erez P

erez et al. (2013) proposed the use of

SDI as the central axis around which smart services

can be built in a city. The proposal is based on

the experience in developing the SDI in the city of

Zaragoza, Spain (IDEZar) (Fern

andez et al., 2006).

The proposal allows a series of smart services and

products to be created for this city.

Kyriazopoulou (2015) presents a literature study

on the architectures and requirements for the devel-

opment of smart cities. Some requirements, such as

data collection, processing, and streaming, are the

most common among the 41 projects analyzed. Other

requirements, such as data security, were found in

only two projects.

This paper describes the creation of an archi-

tectural model combining SDI and VGI for the

development of smart cities. To that end, the re-

quirements must be analyzed based on different

viewpoints in order to meet the needs of the city.

3 THEORETICAL FRAMEWORK

3.1 Combining SDI with VGI for the

ISO Reference Model for Open

Distributed Processing (RM-ODP)

Architectures for smart cities can be built based

on different viewpoints. RM-ODP is a framework

that aids the development of any type of system,

preferentially large and complex ones (Da Silva

et al., 2013). The framework deﬁnes and deals with

ﬁve viewpoints: The Enterprise viewpoint (EV)

deﬁnes the system’s purpose, scope, and policy; the

Information viewpoint (IV) deﬁnes data semantics

and interaction in the system; the Computation

viewpoint (CV) “allows breaking the system down

into a set of services that interact through interfaces,”

except for distribution; the Engineering viewpoint

(NV) deﬁnes the tools and features needed for the

interaction of different services and data in the

system; and the Technology viewpoint (TV) deﬁnes

the technologies to implement the system (Hjelmager

et al., 2008). Figure 1 illustrates the ﬁve viewpoints

in RM-ODP, highlighting the EV approached in

this study. Specifying the EV is the ﬁrst step in the

creation of a model that combines SDI with VGI for

smart cities.

According to (Hjelmager et al., 2008) and

Figure 1: Viewpoints of the RM-ODP framework – adapted

from (Hjelmager et al., 2008).

(Linington et al., 2011), the EV refers to any type of

more abstract activity in the development of a system,

such as the speciﬁcation of system requirements,

policies, high-level components, etc. In the EV, the

actors (stakeholders) interested in the success of the

system are speciﬁed, whether users, contributors,

An Architectural Model for Smart Cities using Collaborative Spatial Data Infrastructures

243

or developers of the system. Moreover, the EV

must show the purpose of the system, the system

requirements, and the types of relations the actors

have with the system.

System development is subjected to some re-

strictions, which may arise from business processes,

which are interconnected tasks to provide products

or services, and organizational norms, such as agree-

ments, partnerships, security policies, etc. In order to

combine different restrictions, EV speciﬁcation con-

sists in an inter-related set of communities (Linington

et al., 2011).

The communities, working under a contract,

deﬁne the behaviors of the sets of participants to

achieve a speciﬁc goal. The contract expresses the

obligations of those involved in the system, besides

the conditions of the system itself such as security

and efﬁciency. Figure 2 illustrates the elements

involved in the speciﬁcation of a community in

relation to the “Phone Repair” event. Normally,

the behavior of this community is deﬁned by a

composition of processes. The process resulting from

this composition is represented as a UML activity for

ODP systems by the stereotype  EV

Process .

This process is also speciﬁed by community roles.

The roles deﬁne how objects (communities, actors,

etc.) must behave and interact to reach a goal. In

order to deﬁne a role in the ODP nomenclature, the

stereotype  EV Role  is used.

The EV policies are represented by rules or

Figure 2: Speciﬁcation of a community (Linington et al.,

2011).

restrictions in the system creation process. They may

be modiﬁed to ﬁt certain needs during the creation

process.

The actors identiﬁed by (Hjelmager et al., 2008)

take up different roles in the system: The Producer

is “responsible for producing data or services for the

system”; the Policy Maker is “responsible for deﬁn-

ing the policies and involvements in the system”; the

Provider is “responsible for providing data or services

to system users”; the Broker is “responsible for the

negotiations between the User and the Provider,

besides maintaining and publishing metadata records

collected from Producers and Providers, and for

creating catalogs and rendering services based on

those catalogs”; the Value Added Reseller (VAR)

is “responsible for adding new resources to the

products, making them available as new products”;

and the End User uses the system for his or her

purposes.

Cooper et al. (2011) extended the model by

(Hjelmager et al., 2008) in order to include the VGI

component since the original actors did not fulﬁll the

representation of the roles in the original proposal.

The actors were specialized into “subactors” each

of which may take up several roles simultaneously

in an SDI that uses VGI. The virtual applications

for data sharing that arose with the evolution of the

internet and the increase in mapping costs motivated

the inclusion of VGI in SDI.

The Producer was classiﬁed into four groups:

Status, Motivation, Role, and Skill. The group Status

has four actors: The Ofﬁcial Mapping Agency,

organization responsible for consistently acquiring,

mapping, and producing data; the Commercial

Mapping Agency, entity that commercializes data

and products for proﬁt; the Community Interest, a

group of contributors that greatly contribute with

small-scale data production of a delimited or global

area, particularly through the VGI; and the Crowd

Source, anyone who whishes to contribute data

according to speciﬁcations predeﬁned by the SDI.

The Motivation group is formed by three actors

according to the motivation of each one to produce

data to the SDI: The Special Interest actor will pro-

duce data or information for his or her own interest,

such as reporting the number of cases of Dengue

fever in the neighborhood or the number of potholes

in the asphalt of his or her street; The Economic actor

will produce data with ﬁnancial purpose, whether by

commercializing or using them; and the Process actor

will produce data with interest in the mode of data

capture. For instance, a teacher who transmits the

knowledge in data production to his or her pupils.

The group Role is specialized into four actors,

each one playing a role in data production or geospa-

tial services: The Captor of Raw Data, responsible for

producing, describing, and categorizing geospatial

data such as georeferenced images or vector and

matrix data; the Submitter of Revision Notice, re-

sponsible for reviewing or correcting data in an SDI.

This activity includes mainly citizen participation

through the SDI for immediate improvement of data;

the Passive Producer; responsible for producing data

through mobile devices such as cellular phones,

tablets, and automotive satellite navigation devices

that are tracked by a service provider that monitors

trafﬁc ﬂow, network congestion, etc., which may

raise privacy-related issues; and the Database Ad-

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244

ministrator, responsible for ensuring consistency,

creation, and veriﬁcation of the database rules, i.e.,

that all speciﬁcations will be respected.

The last group, Skills, was specialized into

ﬁve actors according to their skill level to produce

geospatial services and data: The Neophyte, despite

having “no formal knowledge” on the matter, has

availability and interest in contributing with data

and opinions; the Interested Amateur, interested in a

given subject who seeks knowledge in the literature

or from colleagues and specialists in producing

geospatial data; the Expert Amateur, experienced

in the matter, but whose main source of income is

not data production; the Expert Professional, who

has knowledge and theory/practical grounds in the

production and commercialization of geospatial data,

activities that are his or her main source of income;

and the Expert Authority, a renowned producer of

quality data and services with broad theoretical and

practical knowledge in the area. Any mistake may

cause him or her to be questioned (Cooper et al.,

2011).

The actors and their specializations play a key

role in combining a VGI with IDE. However, that

does not fulﬁll the needs for the development of

smart cities.

3.2 Requirements of a Smart City

The requirements are fundamental pieces for the con-

struction of systems for a smart city (Kyriazopoulou,

2015). They are primordial in order to integrate

functionalities that aim to meet the needs of the city,

particularly of the citizens.

Kyriazopoulou (2015) identiﬁed a set of require-

ments commonly found in the literature to implement

a smart model or applications for cities. Below, a

brief description of some requirements is presented:

Data Collection is a basic activity in a smart city.

This activity must handle data of different types and

dimensions to allow analyses for the identiﬁcation

of problems to enable improvements. Different

sources can be used for data collection. For example,

physical systems that capture real-time data such as

seismographs, radars, pluviometers, among others.

Another form of contribution is citizen participation

through applications with VGI support;

Data Streaming and Processing concerns the

capacity of accessing the data and analyzing trans-

mission ﬂows from the distributed data collection

sources;

Data Security is one of the most important

requirements. The systems must not allow access to

conﬁdential citizen data. To ensure the protection

of such data, encryption techniques, authentication

mechanisms, and access control can be used;

Monitoring smart cities in real time is essential

to estimate and predict situations for immediate

decision-making. Mobile technologies, radio-

frequency identiﬁcation (RFID) networks, and smart

devices are the main facilitators for this requirement;

Heterogeneity concerns the capacity of dealing

with different devices and different ﬂows of informa-

tion in a smart city;

Adaptation concerns the capacity of reaction

or change in the occurrence of a given event and

can be achieved with the use of sensors, prediction

techniques, and data-mining;

Sustainability concerns social aspects, such

as providing services in transportation, healthcare,

safety, education, etc.; ﬁnancial aspects such as

investments, job creation, etc.; and environmental

aspects related to energy efﬁciency and natural

resources management. Those aspects must be

supported by the ICTs;

Interoperability concerns the capacity of si-

multaneous “interaction” among different connected

devices. This interaction is facilitated with the use

of protocols and standards that allow information

sharing.

It is a fact that those requirements may not

represent all needs since cities have different issues,

characteristics, and resources. The fact those require-

ments were extracted from a technical standpoint and

do not consider citizen needs or preferences is also

questionable. A smart city application will hardly

ever meet all requirements needed, even because the

needs might change over time.

3.3 Domains and Indicators

According to (Gifﬁnger et al., 2007), indicators are

essential to identify deﬁcient areas in a city. Data such

as unemployment rate, carbon dioxide (CO

) levels,

number of homicides, and many others may be useful

to create smart applications and speed up the public

administration’s decision-making process.

The document “ISO/DIS 37120 Sustainable de-

velopment and resilience in cities – Indicators for

city services e quality of life” lists a series of in-

dicators along with a method to evaluate each one.

The indicators are grouped into themes or areas of

interest that may also be called domains, namely:

Economy, Education, Energy, Environment, Recre-

ation, Safety, Shelter, Solid Waste, Telecommunica-

tions and Innovation, Finance, Fire and Emergency

Response, Governance, Health, Transportation, Ur-

ban Planning, Wastewater, and Water and Sanita-

tion (ISO/DIS 37120, 2013). Each domain has two

groups of indicators: Core indicators, deﬁned as fun-

An Architectural Model for Smart Cities using Collaborative Spatial Data Infrastructures

245

damental, and supporting indicators, deﬁned as rec-

ommended. Both are used to demonstrate the perfor-

mance in rendering of services and quality of life of

the city. To exemplify, this paper approaches the do-

main Transportation.

A city’s transportation network provides a view

of vehicle trafﬁc and the ﬂexibility of transportation

systems. Although small and medium-sized cities

usually do not have as many vehicles as large ones,

the problems faced with trafﬁc may be the same.

The indicators are highly important to measure the

performance of a city. It is important to point out that

not all fundamental and functional indicators may be

relevant to a given city. Likewise, a city may have

relevant indicators that are not described in (ISO/DIS

37120, 2013).

4 PROPOSED MODEL

The key “ecosystem” for the development of this

research is smart cities, where the several domains

are found, which, in turn, are observed by means of

indicators. The model must incorporate ICTs that

detect key information that shall later be analyzed

and integrated into the system. A network of sensors

is the main instrument to detect events in a smart city.

The complexity to develop a smart city is mainly due

to the different views and perspectives that may be

taken into account, besides the different interested

persons and the city needs. According to (ISO/DIS

37120, 2013), this complexity may be represented by

models using modeling techniques and formalisms

such as the one by ISO/IEC 19505 Information

Technology – Management Group Uniﬁed Modeling

Language (OMG UML). The examples presented in

this section are based on the administrative structure

and regulation agencies of Brazil.

4.1 Purpose and Objectives

The purpose of this study is to allow small and

medium-sized cities to create smart services and

applications to provide better conditions and quality

of life to citizens. The use of SDI and VGI is very

important to obtain geospatial data and information.

These may integrate applications to create a collabo-

rative environment of mutual beneﬁt.

The model proposed is based on the Enterprise

viewpoint (EV) of RM-ODP. First, the actors and

their specializations must be reexamined based on the

EV. Among the actors already proposed by (Cooper

et al., 2011), a new physical actor was included,

called Sensor. It may be considered fundamental

for a smart city since it will be responsible for

providing real data in real time. Figure 3 shows the

inclusion of the new actor in the model with its two

specializations: The actor Citizen Sensor, specialized

in the group Status from the actor Crowd Source, and

the actor Physical Sensor, specialized in the group

Role from the actor Passive Producer.

In order to exemplify the EV speciﬁcation, one

Figure 3: Inclusion of the actor Sensor (Citizen and Physi-

cal).

of the most common current problems in cities was

chosen: trafﬁc congestion. People waste a lot of time

in congestion and often the issue can be solved or

ameliorated with smart solutions such as by creating

a System for Vehicle Congestion Reduction. The

system must support data from different sources

and provide real-time information on events on the

stretches of road the user intends to travel. This way,

the user will be able to decide which route to follow

and avoid routes with possible problems.

4.2 Actors

The actor Citizen refers to any individuals who

voluntarily contributes (VGI) information through

applications installed on or accessed by technological

devices such as smartphones, tablets, etc. The

actor Physical is a sensor or set of physical sensors

responsible for capturing real-time information on a

certain space, for example security or trafﬁc cameras.

4.3 Communities and their Behaviors

The ﬂowchart of the administrative structure of a

Brazilian city may follow the following hierarchy:

secretaries (education, healthcare, transportation,

street cleaning), management boards (planning,

maintenance, audit, personnel), department (adminis-

trative, ﬁnancial, surveillance), and sectors (property,

maintenance, health surveillance). It is important

to highlight that the structural distribution may vary

according to the municipality.

Besides those entities/organs, the cities may have

very important external entities that are not always

part of this administrative structure. For example,

unions and outsourced companies that provide

products or services (e.g., electricity, water). When

the vehicle congestion issue is considered, it may

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246

involve external entities, for cities in Brazil, such as

the National Department of Trafﬁc (Departamento

Nacional de Tr

ansito - DENATRAN), which oversees

and rules trafﬁc issues throughout the country, and the

National Land Transport Agency (Ag

encia Nacional

de Transportes Terrestres - ANTT), responsible for

providing appropriate land transport to users.

The National Trafﬁc Code (C

odigo Nacional

de Tr

ansito - CNT) attributes the responsibility of

managing trafﬁc to the municipality. Thus, the

problem vehicle congestion is the responsibility of

each municipality. That means the main community

involved with this issue is the Secretary of Trafﬁc

and its possible branches (management board, de-

partments, sectors, and divisions).

It can be considered that the following com-

munities are involved in the System for Vehicle

Congestion Reduction: municipal secretary of trafﬁc,

data analysts, moderators, trafﬁc agents, watchper-

sons, drivers, passengers, and pedestrians. The roles

each one take up are described in the next section.

4.4 Roles, Contracts and Policies

The roles, contracts, and policies presented include

activities regarding the objects and communities

involved in the system. The system may be split

into three units: Controlling Unit, Pacifying Unit,

and Passive Unit. Those involved from the three

units may have characteristics in common such as

supplying information to the system.

The Controlling Unit is responsible for control-

ling the system and the information received by the

users. Those involved in this unit are:

Secretary of Trafﬁc: Responsible for managing

and overseeing public passenger transport (e.g.,

buses, taxis), trafﬁc signs, and the city’s ﬂeet. The

sector must be able to generate data and historical

information such as the number and types of vehi-

cles, areas prone to having some sort of problem

(accidents, fallen trees, ﬂoods, gridlock, etc.), among

others, and store them in an open platform (SDI)

accessed by the system. It is the role of this secretary

to incentivize the use of the system, presenting the

beneﬁts that may be reached. It is also the attribution

of the Secretary of Trafﬁc to install and maintain

physical sensors to monitor the city;

Data Analyst: Responsible for developing analy-

ses of the data and identifying possible improvements

in the system. The analyses may combine different

sources of information such as from an SDI and VGI,

social media, or sensors, analyzing not only the data

produced by the speciﬁc application for the vehicle

congestion issue;

Moderator: Has the role of following, analyzing,

and ﬁltering information provided mainly by the

citizens. Information not related to the system’s

purpose must be withheld so as not to harm the users.

The Pacifying Unit is responsible for monitoring

the system’s working environment, i.e., the trafﬁc of

vehicles and pedestrians, the streets, etc. In addition,

the unit must contribute information to the system.

Those involved in this unit must be hired and be

identiﬁed in the system. They may be represented by:

Trafﬁc Agent: Responsible for “developing

activities to improve the quality of life of the pop-

ulation, acting as a facilitator of sustainable urban

or road mobility, being guided, among others, by

constitutional principles of legality, impersonality,

morality, publicity, and efﬁciency” (DENATRAN,

2010). The agent must report in the system informa-

tion on any event that may cause congestion (e.g.,

accidents, ﬂoods);

Watchperson: Responsible for following and

monitoring using audio/video telecommunications

devices such as cameras and microphones. The

role also includes providing information of possible

events that may impact vehicle ﬂow.

The Passive Unit is made up of the system

users that are not mandated to provide information.

However, it is essential that those users participate as

VGI contributors so that the system does not depend

only on information from physical sensors and the

pacifying unit. This unit may comprise:

Driver: Able to provide data such as speed and

geographic location through on-board systems or

satellite navigation installed in the vehicles. This

may be crucial to identify possible areas with con-

gestion by comparing the speed of vehicles with the

maximum speed allowed in that stretch of road over

a certain timeframe;

Passenger: Has the role of contributing informa-

tion on events that may impact the ﬂow of vehicles

through VGI applications installed on or accessed by

mobile devices. Situations such as accidents, fallen

trees, ﬂoods, roadworks, and several others may be

reported in the system;

Pedestrian: Has the same role as the passenger,

however, not in a vehicle.

The speciﬁcation of the EV of the System

for Vehicle Congestion Reduction is illustrated

in Figure 4. Each community is speciﬁed by

the stereotype  EV CommunityContract ,

which contains a component stereotyped as

 EV Community . Each of the components

has its dependence deﬁned by the stereotype

 EV Re finesAsCommunity , referring to the

classes stereotyped as  EV CommunityOb ject 

(Controlling Unit, Pacifying Unit, and Passive Unit).

An Architectural Model for Smart Cities using Collaborative Spatial Data Infrastructures

247

Figure 4: Enterprise speciﬁcation of the System for Vehicle Congestion Reduction.

Those classes express the community objects that

model the communities as simple objects. The

community objects are included in the package

“Enterprise Objects.” The objects Trafﬁc Agent and

Watchperson are examples of those enterprise objects

that interact with the system.

It is worth pointing out that the roles of the actors

may overlap. For example, the Data Analyst and the

Moderator may take up the role of Driver, Passenger,

and Pedestrian or a Driver may work as Watchperson

or Data Analyst. In fact, an actor may take up another

role at a certain moment to further contribute with the

system’s goal, which is to reduce vehicle congestion

in the city.

5 DISCUSSION OF RESULTS

The actor Sensor (Citizen and Physical) introduced

in the model may allow for greater system efﬁciency

through the data collected both by physical and hu-

man (VGI) sensors. The communities deﬁned may

take up several roles in the system. They all have a

task in common, i.e., supplying data. It is up to the

system user whether to make a decision or not, such

as whether he or she should follow a certain route or

take another path (if it exists). Figure 5 shows the

roles identiﬁed regarding the communities involved.

The roles speciﬁed of each community may share a

common goal in the system such as supplying volun-

teered data (VGI).

Three communities were identiﬁed that make up

the System for Vehicle Congestion Reduction: Con-

trolling Unit, Pacifying Unit, and Passive Unit. Roles

were attributed to the communities regarding their be-

haviors. As well as a community, the system itself

has its role – to reduce vehicle congestion by provid-

ing information regarding events that hold up the ﬂow

of vehicles through that route. The objects contained

in each of the communities have roles concerning the

activities of their community.

6 CONCLUSIONS AND FUTURE

WORKS

It is concluded that the ICA’s original SDI model pro-

posed by (Hjelmager et al., 2008) and its extension

developed by (Cooper et al., 2011) are solid enough

for the development of an architecture for smart cities.

However, due to the complexity of the domain, two

new specializations had to be included.

The speciﬁcation of the System for Vehicle Con-

gestion Reduction exempliﬁed how smart solutions

can be developed by combining SDI and VGI. Sen-

sors are key parts in the development of smart cities.

Moreover, this combination allows smart applications

to be developed in several domains of a city, thus al-

lowing for the transformation of a “common” city into

a smart city. This way, a sustainable and efﬁcient en-

vironment can be obtained in which the population

has better quality of life and is less impacted by the

inherent issues of a city (congestion, electric grid or

water distribution grid failure). The authors of this

study have high expectations towards the use of SDI

and VGI in the development of smart cities, which

opens a huge space for new researches and techno-

logical innovations.

SMARTGREENS 2017 - 6th International Conference on Smart Cities and Green ICT Systems

248

Figure 5: Attribution of community roles.

ACKNOWLEDGEMENTS

Project partially funded by the agencies CAPES,

FAPEMIG and CEMIG.

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