SysIoTML: A Technique for Modeling Applications in the Context of IoT

Rodrigo Nascimento

1 a

, Vinicius Santos

1 b

, Bruno Carvalho

1 c

, Jone Correia

1 d

, Luis Rivero

1 e

Rodrigo Santos

2 f

, Francisco Silva

1 g

, Ariel Teles

3 h

and Davi Viana

1 i

Federal University of Maranhao - UFMA, Avenida dos Portugueses, 1966, Sao Luis, MA, Brazil

Federal University of the State of Rio de Janeiro – UNIRIO, Rio de Janeiro, RJ, Brazil

Federal Institute of Education, Science and Technology of Maranh

ao, IFMA, Araioses, MA, Brazil

Keywords:

IoT Systems, Modeling Technique, SysML.

Abstract:

The Internet of Things (IoT) is a concept that connects smart objects equipped with sensors, networks, and

processing technologies that work together to provide an environment in which smart services are brought

to users. Systems modeling should be conducted to create IoT Systems and ensure the implementation of

a good system. IoT increases the complexity of systems modeling due to novel concepts that need to be

addressed. However, there are no established techniques for systems modeling for this speciﬁc context. This

paper presents the development of a new technique for IoT systems modeling, the SysIoTML, an extension of

SysML. Such techniques consider speciﬁc aspects of IoT Systems (behavior and interactivity). We proposed

the SysIoTML and conducted a concept-proof to analyze the technical feasibility. The developed technique

proved useful, and the participants were able to model the proposed problem. The main contribution is to

advance IS modeling through a new technique.

1 INTRODUCTION

The Internet of Things is a concept that aims at the

digital interconnection of everyday objects to the in-

ternet. It is a paradigm that allows composing systems

from uniquely addressable objects (things) equipped

with the identiﬁcation, sensation, or actuation of be-

haviors and processing capacities that can commu-

nicate and cooperate to reach a goal (Motta et al.,

2018). From primary devices with simple systems so-

lutions to large-scale, high-performance systems that

produce and analyze vast amounts of data, IoT will

reach all areas of interest (Jacobson et al., 2017), ar-

eas that directly involve humans. IoT allows physi-

cal objects (sensors, vehicles, buildings, and others)

https://orcid.org/0009-0007-5676-2396

https://orcid.org/0009-0003-1944-7072

https://orcid.org/0009-0008-6188-7537

https://orcid.org/0009-0005-7945-8085

https://orcid.org/0000-0001-6008-6537

https://orcid.org/0000-0003-4749-2551

https://orcid.org/0000-0001-8389-3679

https://orcid.org/0000-0002-0840-3870

https://orcid.org/0000-0003-0470-549X

to collect and transmit data, incorporating sensors,

software, and other technologies, to connect and ex-

change data with other devices and systems on the In-

ternet.

Smart devices and services are carried out through

the various applications that run in the IoT envi-

ronment (Miao and Liu, 2016). Various capabil-

ities such as producing/consuming data and online

services improve daily life and activities around the

world through the context of IoT (Talavera et al.,

2017).

IoT scenarios apply to using IoT devices in their

daily activities. In addition, IoT applications have

some beneﬁts for users to choose the best opportu-

nity in any case, decision-making, management, and

monitoring (Ghobaei-Arani et al., 2018).

In recent years, IoT has been widely present ev-

erywhere in most aspects of human life, such as cities,

homes, universities, industry, organizations, agricul-

tural environments, hospitals, and health centers (Mu-

ralidharan et al., 2018). Despite the motivations of the

different application domains, they all have a com-

mon and shared goal: to provide smart services to in-

crease the quality of human life (Bello and Zeadally,

2019).

Nascimento, R., Santos, V., Carvalho, B., Correia, J., Rivero, L., Santos, R., Silva, F., Teles, A. and Viana, D.

SysIoTML: A Technique for Modeling Applications in the Context of IoT.

DOI: 10.5220/0011988500003467

In Proceedings of the 25th International Conference on Enterprise Information Systems (ICEIS 2023) - Volume 2, pages 187-194

ISBN: 978-989-758-648-4; ISSN: 2184-4992

 2023 by SCITEPRESS – Science and Technology Publications, Lda. Under CC license (CC BY-NC-ND 4.0)

187

Information Systems, including IoT Systems, ben-

eﬁt from the use of modeling, which helps developers

better visualize the system’s planning and design, in

addition to allowing the development to be more ade-

quate. It should be noted that complex computer sys-

tems require a high level of quality, and the search for

such systems has motivated the development of mod-

eling methods (Lima et al., 2021).

Literature and industry present modeling lan-

guages that aim to create graphical representations of

systems, such as UML (Uniﬁed Modeling Language)

and SysML (Systems Modeling Language). Systems

modeling is the process of developing abstract mod-

els of a system’s components, providing everywhere

in most aspects of human life system does (Jacobson

et al., 2017). In IoT systems, several additional as-

pects need to be modeled. These are aspects inherent

to this type of system, such as speciﬁc behavior and

interaction (Motta et al., 2018).

The behavior of an IoT system can help in

decision-making and actions because what makes

a smart system are the devices used, the decision-

making process, and the entire solution architecture

(Atabekov et al., 2015). Furthermore, many IoT de-

vices and systems perform functions based on human

behavior. Therefore, social relationships (for exam-

ple, friendship and conﬂict) of people are very criti-

cal, which must be considered in IoT with device-to-

device communications (Chen et al., 2018)

Interaction can help to understand the dynamics

of a system, its structural organization, and the inter-

action between objects, especially with the increasing

complexity and number of devices. New architectural

styles are required to address your needs for scalabil-

ity, fault isolation, and ﬂexibility (Herrera-Quintero

et al., 2018).

This work aims to deﬁne a technique for model-

ing IoT systems, considering the aspects of behavior

and interaction. Additionally, we conducted a proof

of concept (PoC) with nine participants to verify tech-

nique feasibility. The deﬁned technique has four di-

agrams, extensions of diagrams presented in SysML:

Use Case Diagram, Sequence Diagram, Block Deﬁ-

nition Diagram, and State Machine Diagram. The re-

sults of the study show that the technique is favorable

for modeling IoT systems, in addition to being use-

ful and easy to understand, all participants were able

to perform the modeling of the experiment, but some

difﬁculties were pointed out in the block deﬁnition di-

agram by some participants.

This paper is organized as follows: Section 2

presents the background; Section 3 presents the tech-

nique; Section 4 presents the Proof of concept; and

Section 5 presents the conclusion and future work.

2 BACKGROUND

IoT is a recent communication paradigm that en-

visions a near future, in which objects of every-

day life will be equipped with microcontrollers,

transceivers for digital communication, and proper

protocol stacks. That will make them capable of com-

municating with each other and with users, becoming

an integral part of the Internet (Atzori et al., 2010).

The IoT vision can become the foundation to realize a

uniﬁed urban-scale Information and Communication

Technologies (ICT) platform, so unlocking the poten-

tial of the vision of concepts such as Smart Cities

(Hern

andez-Mu

noz et al., 2011), thus being able to

be a concept that enables and provides the main sup-

port for Smart Cities. In this section, we present the

aspects of IoT modeled in our technique, behavior, in-

teraction, and other concepts related to the research.

2.1 Behavior and Interaction

In (Motta et al., 2018), the IoT Facets are presented,

which represent the vision of the different facets that

characterize the IoT multidisciplinary. Facets rep-

resent different disciplines and knowledge areas in-

volved in IoT. The authors present the challenges in-

volving software engineering and the IoT. An analysis

of the IoT deﬁnitions identiﬁed through a literature

review, a report by a state-owned company, and the

concerns of professionals were carried out, thus deﬁn-

ing the necessary facets for the materialization of IoT.

As a result, the problem domain and seven different

facets were obtained: connectivity, things, behavior,

smartness, data, interactivity, and environment.

Behavior comprises the realization of reactions, so

it may be necessary to use software solutions, seman-

tic technologies, data analysis, and other areas to im-

prove the behavior of things. In this sense, all manip-

ulation, analysis, and data processing were encapsu-

lated in this facet, dealing with the implemented be-

havior and the generated results. The idea of the be-

havior of the system results from its constituent parts.

Behavior is generated by the interaction and collab-

oration of two or more devices, and the combination

of more straightforward behaviors can generate more

complex behavior.

Interactivity takes place in the interaction to ex-

change information between actors and things, and

the degree to which this happens. Actors involved

with IoT applications are not limited to humans, we

also have animal and thing-to-thing interactions.

In the technique presented in this paper, we choose

only two of these facets, because modeling the behav-

ior of software can help to a better understanding of

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the system and the factors that inﬂuence their behav-

ior. Interaction modeling can help to understand the

dynamics of a system, its structural organization, and

the interaction between objects. We believe that, for

an initial version of the technique, these two facets are

interesting, as they work with the basis of any system,

which is how it should behave and interact with the

users.

To support the development of applications in the

context of IoT, (Motta, 2021) presents an instrument

called IoT Roadmap. In IoT Roadmap, evidence is

collected for each of the facets, aiming to address

some existing challenges of IoT.

In the SysIoTML technique, we used the speciﬁc

recommendation items for each facet, provided by the

IoT Roadmap. These items were used as resources for

each facet, and these resources were used to adapt the

modeling diagrams. Table 1 presents the characteris-

tics pointed out in the IoT Roadmap for the Behavior

Facet, where three properties are deﬁned: IoT object,

sensor, and actuator with their respective characteris-

tics. The same table also presents the characteristics

pointed out in the IoT Roadmap for the Interactivity

Facet.

2.2 UML

The UML is a language for specifying, visualizing,

building, and documenting the artifacts involved in

software systems, modeling business, and other non-

software systems. The UML represents a collection

of engineering best practices that have proven effec-

tive in modeling large and complex systems (Booch

et al., 1999).

A UML proﬁle deﬁnes the mechanisms used to

adapt the UML metamodel to new platforms or a spe-

ciﬁc domain. The responsibility of the metamodel is

to deﬁne a language that will be used to elaborate a

model. Thus, the stereotypes of a UML proﬁle will

be instantiated from a certain element of the UML

metamodel. The UML metamodel is composed of

the concepts of classes, attributes, associations, and

so on. It is primarily a set of stereotypes, constraints,

and sometimes classes and other elements that adapt

the UML metamodel to a speciﬁc domain or purpose;

proﬁles are external to a model and extend the UML

without changing the base metamodel.

2.3 SysML

IoT systems need modeling to be developed with

quality. Decision-making must seek an option that

presents the best performance, the best evaluation, or

the best agreement between the expectations of the

decision-maker, considering the relationship between

the elements.

In SysML, requirements, and block deﬁnition di-

agrams are often used to describe the hierarchy of a

system, such as a tree of parts (e.g. equipment tree).

The requirements diagram presents a simple hierar-

chy of text-based requirements, and the block deﬁni-

tion diagram is used to deﬁne a system or component

at any level of the system hierarchy (OMG, 2019).

SysML is a general-purpose architectural model-

ing language for Systems Engineering applications.

It enables the speciﬁcation, analysis, design, veriﬁ-

cation, and validation of a wide range of systems.

These systems may include hardware, software, in-

formation, processes, personnel, and facilities (OMG,

2019). The Sequence, State Machine, Use-Case, and

Package diagrams have not changed from the UML.

The block deﬁnition, activity, and inner block dia-

grams have been modiﬁed from the UML and the re-

quirements and parametric diagrams are new (OMG,

2019).

3 SysIoTML

In recent years, IoT has been widely used in most as-

pects of human life everywhere, like homes, cities,

farms, hospitals, factories, universities, etc. There-

fore, systems aimed at human well-being need to be

modeled properly, especially with their behavior and

interaction, so that these systems in the development

phase are done appropriately, this triggered the need

for modeling with a simple notation but complete in

the context of IoT.

The IoT Roadmap provides speciﬁc recommen-

dation items for each facet. We convert these items

into characteristics for the behavior and interactivity

facets. Finally, we used these features to adapt exist-

ing modeling diagrams that covered IoT aspects.

For adaptation, we used the concept of stereotypes

(OMG, 2019). A stereotype is an extensibility mech-

anism that allows you to adapt or customize models

with speciﬁc constructs for a particular domain, plat-

form, or development method.

We created a modeling technique for systems in

the IoT context, where four diagrams were developed,

extensions of the diagrams found in SysML: Use Case

Diagram, Sequence Diagram, Block Deﬁnition Dia-

gram, and State Machine Diagram.

3.1 Use Case Diagram

The Use Case Diagram presents a simple and easy-

to-understand language so that users can have a gen-

SysIoTML: A Technique for Modeling Applications in the Context of IoT

189

Table 1: Behavior and Interactivity Facet Characteristics (Motta, 2021).

Facet Deﬁne Characteristics

Behavior

IoT Object The IoT object metadata

Identify identiﬁcation technology

Describe the event

Describe identiﬁcation type

Behavior

Sensor Set sensor related data

Describe an abnormal condition

Indicate the limit and the desired values

Set sensor device

Establish rules for the sensor

Behavior

Actuator Describe manual or automatic mode

Locate the action

Identity who triggers the action

Enter the circumstances to trigger the action - input

Establish the consequences of an action - output

Identify who acts

Interactivity

Deﬁne users, roles, and responsibilities

Deﬁne data for users and roles

Deﬁne human-thing or thing-thing interaction

Set interaction method (gesture, touch, etc.)

Identity interaction IoT object

Identify the sequence of interaction and expected result

eral idea of how the system will behave. It identiﬁes

the actors (users, other software that interacts with the

system, or even some special hardware), who will use

the software in some way, as well as the services, that

is, the options that the system will make available to

the actors, known in this diagram as Use Cases.

In SysIoTML, the actors will be represented

through the <<stereotype>> Stakeholder, and their

relationship with an object will be through a use

case, which will communicate with an object through

the <<interaction>>. The objects will be repre-

sented through the <<stereotype>> IoT object, with

two <<extend>>, <<extend>> Sensor and the

<<stereotype>> Actuator. You can have more than

one <<stereotype>> IoT Object, with more than one

<<stereotype>> Sensor or <<stereotype>> Actu-

ator. Figure 1 shows this diagram.

Some important rules for this diagram: the

<<stereotype>> Sensor and the <<stereotype>>

Actuator cannot have use cases directly linked

to them. The <<stereotype>> Stakeholder and

<<stereotype>> IoT objects can have use cases di-

rectly linked to them.

3.2 Sequence Diagram

The Sequence Diagram is concerned with the tempo-

ral order in which messages are exchanged between

the objects involved in a given process. A Sequence

Diagram usually identiﬁes the generating event of the

modeled process, as well as the actor responsible for

this event, and determines how the process should un-

fold and be completed by sending messages, which in

general trigger methods between objects.

In SysIoTML, the actors will be represented

through the <<stereotype>> Stakeholder. Through

an initial interaction between the <<stereotype>>

Stakeholder and the object <<stereotype>> object,

from there the process, can unfold together with

the other three objects: <<stereotype>> Sensor,

<<stereotype>> Controller and <<stereotype>>

Actuator. Figure 2 presents this diagram.

It is not allowed to create lifelines other than those

already established, you can create more than one of

those already established.

3.3 Block Deﬁnition Diagram

The Block Deﬁnition Diagram deﬁnes the features of

a block and any relationships between blocks, such

as associations, generalizations, and dependencies, in

terms of characteristics, operations, and relationships.

It is used to deﬁne the characteristics of each Block in

terms of its structural and behavioral characteristics.

In SysIoTML, a block will have three

<<stereotype>>: <<stereotype>> object,

<<stereotype>> Sensor, and <<stereotype>>

Actuator, each with predeﬁned values and properties

that must be ﬁlled in. Figure 3 presents this diagram.

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Figure 1: Use Case Diagram.

Figure 2: Sequence Diagram.

Figure 3: Block Deﬁnition Diagram.

3.4 State Machine Diagram

This diagram tries to follow the changes suffered in

the states of an instance. It is a type of behav-

ioral diagram that shows transitions between various

objects, describing actions, conditions, and conse-

quences. This diagram is interesting for modeling

behavior as it can show all possible states of an IoT

Object, sensor and actuator.

In SysIoTML, the classes <<stereotype>> Sen-

sor and <<stereotype>> Actuator will represent

changes in states suffered due to an Interaction. The

<<stereotype>> IoT Objects enables/disables the

<<stereotype>> Sensor and <<stereotype>> Ac-

tuator.

4 PROOF OF CONCEPT

The Proof of Concept (PoC) aims to analyze the fea-

sibility of the ﬁrst version of our technique. To carry

out this study, we used an IoT system scenario related

to trafﬁc in an urban center.

Trafﬁc signs are the most basic instrument for col-

lecting road trafﬁc data in a city, that is, they allow the

management of vehicle and pedestrian trafﬁc ﬂow, as

well as the starting point for data acquisition. For ex-

ample, vehicle and pedestrian count, trafﬁc speed, and

congestion. Trafﬁc light control is an important and

challenging problem in the real world as trafﬁc signals

can provide potential solutions to ensure improved

and efﬁcient transport and consumption, energy con-

sumption, environmental protection, increased pro-

ductivity, and citizen satisfaction (An et al., 2017)

(Wei et al., 2019) (Guo et al., 2019).

The work by (Souza et al., 2020) presents the re-

quirements for an experiment with trafﬁc signs, of

which we ﬁlter seven to be used in our feasibility

study, as they are related to the behavior and inter-

action of the system. The selection of these require-

ments was validated by a researcher in software engi-

neering. The requirements are:

1. The system must control the trafﬁc pattern of ve-

hicles at the intersection;

2. The system must control the pedestrian trafﬁc pat-

tern at the intersection;

3. The system must store the ﬂow of vehicles on the

roads;

4. The system must store the pedestrian ﬂow on the

roads;

SysIoTML: A Technique for Modeling Applications in the Context of IoT

191

5. The system must track the trafﬁc pattern related to

each road;

6. The system must allow synchronization of trafﬁc

signs;

7. The system must allow the detection of the pres-

ence of pedestrians

4.1 Conduction

We performed the PoC with nine participants: two

have a baccalaureate level and seven have a mas-

ter level, all of whom have modeling knowledge and

some academic or professional knowledge of IoT. The

Table 2 presents the proﬁle of the study participants,

their academic degree, and their knowledge in mod-

eling and IoT, where, Academic represents only aca-

demic knowledge, Academic/project represents aca-

demic knowledge and a project, Project/professional

represents more than one project or up to six months

of professional work and Professional represents

more than one year of professional work.

To carry out the study, we used the context of

smart trafﬁc signs. Each participant received: (1)

a description of the problem to be modeled; (2)

guides for using each SysIoTML diagram; and (3)

participant characterization and SysIoTML assess-

ment questionnaires. These guides introduce the idea

of SysIoTML and explain in detail the use and re-

strictions of each diagram. Guides are available at:

https://drive.google.com/drive/folders/18ypev8Nl7m

lNdZ5n5A ksVLW9c4N1qY1?usp=share link.

Regarding the technique evaluation questionnaire,

participants answered questions about the ease and

usefulness of the technique. Additionally, we asked

them to evaluate each diagram separately and express

opinions about the diagrams. The questionnaire is

available at: https://docs.google.com/forms/d/e/1F

AIpQLSfsxedBVmCg5hjk5cOdYkX1TKpl8YYPBr

Thf9nVi74CPkl5rQ/viewform.

4.2 Results and Discussion

Each participant needed about thirty minutes to model

each SysIoTML diagram. Regarding the ease of un-

derstanding the diagrams, participants indicated pos-

itive results. Participant 1 reported that “The com-

ponents of the diagrams are easily understood, fa-

cilitating their use.”. Additionally, participant three

pointed out that “The diagrams are easy to under-

stand, the guide presents clear and objective infor-

mation on how it works”. Similarly, we had positive

results for the ease of use of the diagrams, according

to participant 1 “It was possible to use the proposed

solution to model the test application”.

About the models created from the modeling tech-

nique, the answers of the participants show that the

additional elements are adequate for the modeling of

applications in this domain. Participant 2 described

that: “[the technique] allows describing the sensors

that make up an IoT scenario and the interaction with

them”. Additionally, participant 8 indicated that “it

was interesting to model using the three domains:

Stakeholder, Object, and Sensor, this helped to orga-

nize each area and its responsibility”.

By speciﬁcally analyzing each diagram, we can

conclude that the diagrams are useful for identifying

the elements of smart objects. According to partici-

pant 1, “Extended diagrams are useful. The addition

of elements such as smart objects, sensors, and actu-

ators in UML diagrams seems to be interesting and

useful”.

On the other hand, participant 5 pointed out the

difﬁculty in “understanding how objects/ sensors/ ac-

tuators are correlated in a block” and also stressed

the need for “means of giving clearer internal rela-

tionships between actuators/sensors/objects”. Two

participants (5 and 8) suggested that our technique

would be better used and easier to “draw” the dia-

grams if there was some modeling tool with the for-

mats of our pre-built diagrams.

Another point highlighted during the analysis of

responses was the applicability of other scenarios of

IoT systems. Participant 6 reported that our technique

was useful for modeling the proposed scenario, but

that it would be interesting to test it in other scenarios,

because according to a participant “I don’t know if, in

other more complex cases that may have to represent

other aspects, there may be some additional need”.

The researchers involved in deﬁning the technique

also analyzed the resulting diagrams for each partici-

pant. We identiﬁed that the participants were able to

model the problem and the requested elements, such

as identiﬁcation sensors. To facilitate the analysis, we

made an “oracle”, to know what was expected from

the resulting diagram.

The “oracle” we did in two steps:

1. In the ﬁrst, two participants from our group did

the experiment with trafﬁc signs separately.

2. In the second, meetings were held with the entire

group of researchers to expose the models made

and a debate on each point presented.

Our idea was to reach a consensus on what was

expected as a result of the modeling done by the par-

ticipants, in addition to having a way for us to eval-

uate the resulting diagrams. With the “oracle”, we

analyzed each diagram. As a result, we found that the

modeling carried out came close to what was ideal-

ized. However, we also noticed that two participants

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Table 2: Characterization of participants.

ID Academic Degree Modeling Experience IoT Knowledge

1 Master’s Academic/project Academic/project

2 Graduate Project/professional Academic/project

3 Graduated Academic Academic/project

4 Master Academic/project Academic

5 Master’s Professional Professional

6 Master’s Professional Academic

7 Master Academic/project Project/professional

8 Master’s Professional Academic

9 Master’s Professional Academic/project

had difﬁculties: (1) when creating the Block Deﬁ-

nition Diagram, two participants did not provide de-

tails of the characteristics. In our guide, we oriented

to present/describe the details of each character; (2)

Regarding the use case diagram, participant 5 repre-

sented a link between the use case and actuator. In

SysIoTML such a link is not allowed because the use

case interacts only with IoT Object. Figure 4 present

the wrong link created by participant 5.

Figure 4: Participant 5 Use case.

After analyzing the resulting diagrams and the

participants’ responses, we conclude that the tech-

nique is appropriate for IoT Systems modeling, but

improvements are needed on how to formulate the

block deﬁnition diagram and rules of the diagram’s

representations.

5 CONCLUSION AND FUTURE

WORK

The IoT is increasingly entering the daily lives of

the population through smart devices and systems.

Modeling IoT applications is important to ensure the

proper development of systems that will operate in the

most diverse domains.

In this paper, we present the SysIoTML to model

applications in the IoT scenario. The focus of the

technique is the behavior and interaction modeling

of an IoT system. To evaluate the technique, we

conducted a PoC involving smart trafﬁc signs with a

group of participants. Each participant modeled the

scenario/system separately. With the experiments car-

ried out, we noticed that the technique was useful and

was well accepted by the participants.

An evaluative questionnaire about the technique

was delivered to each participant. The result of the

questionnaire answered by the participants showed

that the technique was well accepted by them and was

easy to use, despite the indication of some partici-

pants for improvements. With the “oracle” we made,

we noticed that the diagrams made by the participants

came close to what was expected. We also noticed

that some participants had difﬁculties in some points,

which were pointed out as improvements in the ques-

tionnaire, such as, for example, one of the partic-

ipants, when assembling the Block Deﬁnition Dia-

gram, did not ﬁll in the properties indicated by him

with information.

The limitation of our technique is the inclusion

only of the IoT Facets of Behavior and Interactivity.

This is a limitation because it does not encompass ev-

erything an IoT system should have. Another limita-

tion is the use of the technique in only one example.

For better validation, the technique must be tested in

other contexts.

In future work, ﬁrst, we have the improvement in

the relationship between the object, sensor, and actu-

ator in the block deﬁnition diagram since this was a

point addressed by some participants. In addition, we

need to carry out experiments in other smart scenar-

ios, to better verify the performance of the technique

and the development of a tool that helps our tech-

nique. And ﬁnally, the expansion of the technique to

encompass all seven IoT Facets and the Domain Prob-

lem, so that the technique encompasses all aspects of

IoT.

SysIoTML: A Technique for Modeling Applications in the Context of IoT

193

ACKNOWLEDGMENTS

This research is part of the INCT of the Future

Internet for Smart Cities funded by CNPq proc.

465446/2014-0, Coordenac¸

ao de Aperfeic¸oamento

de Pessoal de N

ıvel Superior – Brasil (CAPES)

– Finance Code 001, FAPESP proc. 14/50937-1,

and FAPESP proc. 15/24485-9. This work was

supported by the CAPES - PROCAD - Amazo-

nia (88887.200532/2018-00); National Council for

Scientiﬁc and Technological Development – CNPq

(308059/2022-0); and the State of Maranh

ao Re-

search Funding Agency - FAPEMA (UNIVERSAL-

00745/19, BEPP-01608/21, BEPP-01768/21).

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