the case study on the maiandeua island, at amazonian, brazil

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In Situ Sensory Platform for Characterization of Climate

Behaviors on Human Health in Urban Forest Environments –

The Case Study on the Maiandeua Island, at Amazonian, Brazil

Almir T.L. Neto, Marcos H.K. Sampaio, O.A. Chase, J. Felipe S. Almeida, Carlos Tavares-da-Costa-Júnior

Resumen: Esta investigación presenta una plataforma

sensorial desarrolada através de lá integración de

diferentes tipos de sensores em um ecossistema com el

fin de obtener alguna característica del clima de la isla

Maiandeua. Esta isla es un estudio de caso de la

superficie forestal urbano, cuyo objetivo es caracterizar

el comportamiento climático con las variables

ambientales de temperatura y humedad, todo para

identificar los impactos ambientales sobre la salud

humana y la biodiversidad del foresta. El BRASSEN

contiene un agente inteligente especialista para detectar

comportamientos relacionados con el conforto térmico

y el malestar en los seres humanos, y el riesgo o sin

riesgo (seguridad) de fuego o lluvia en entornos

forestales. Los resultados de los experimentos

empíricos con esta plataforma se proporcionan. Por lo

tanto, este trabajo considera un novedoso estudio en IN-

SITU (local) tecnologías para las zonas forestales

urbanas.

Palabras Clave: Plataforma Sensorial, Sistemas

Ambientales, Modelización Ambiental.

Abstract: This research presents a cyberphysical

sensory platform developed through the integration of

different kinds of sensors on an ecosystem in order to

obtain some climate characteristic of the Maiandeua

Island. This isle is a case study of urban forest area,

whose goal is to characterize the climatic behavior with

environmental variables of temperature and humidity,

all to identify environmental impacts on human health

and biodiversity of the forest. The BRASSEN platform

contains an specialist intelligent agent to detect

behaviors related to thermal comfort and discomfort in

humans, and the risk or without risk (safety) of fire or

rain in Forest Environments. The results of empirical

experiments with this platform are provided. So, this

work considers a novel study in IN-SITU (local)

technologies for urban forest areas.

Keywords: Sensory platform, Environmental Systems,

Environmental Modeling.

Introduction The cyberphysical systems (CPS) are electronic devices

with intelligent computing and communication

elements are integrated into the physical components of

nature [1]. The focus of this work is developing new

methods in design and construction of sensors based on

cyberphysical concept to the particularities of

ecosystems, especially the Amazon biome [2]. The

BRASSEN (acronym to Brazil Autonomous System

Sensory) is a cyberphysical sensory system built in this

research for monitoring agricultural and antropized

area. The temperature and humidity sensors are used in

data acquisition of environmental variables of the

plantations and forest scenario. The temperature,

humidity and dew point determine the primal

environmental factors, which influence human comfort

and agricultural activities [3]. This study has objective

the use of geoprocessing and remote sensing techniques

in order to map and quantify the climate behavior of

environments, through the use of indexes.

The indexes are based on expert knowledge of

researchers and professionals in agronomy, forestry and

climate change [4]. The advantage of detecting these

behaviors early is so that we can prevent and avoid

possible environmental accidents, so that such

situations do not spread to the urban area and vice-

versa.

________________________________________________________

Almir Tavares L. Neto is a Student of M.Sc. in Electrical Eng. at

Federal University of Para, Brazil, (email: [email protected])

Marcos H.K. Sampaio is a Student of M.Sc. in Electrical Eng. at Federal University of Para, Brazil, (email: [email protected])

Otavio A. Chase is a Professor at Amazonian Federal Rural

University, Brazil, (e-mail: [email protected]) J. Felipe S. Almeida is a Professor at Amazonian Federal Rural

University, Brazil, (e-mail: [email protected])

Carlos Tavares da Costa Júnior is a Professor at Federal University of Pará, Brazil, (e-mail: [email protected])

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The issue of global climate change is increasingly

relevant in the context of a population of over seven

billion people whose activities have been altering the

surface characteristics such as vegetation cover, and

also the concentration of gases that interact strongly

with radiation in atmosphere [5]. According to the

IPCC (Intergovernmental Panel on Climate Change)

report the people who will suffer most certainly will be

the cities in development of countries, especially

tropical countries [6]. In these cases the systems that

can characterize environmental behaviors if they do

very important, because these places don’t have

historical data of environmental variables to be used as

sources for prediction models and pattern recognition.

Cyberphysical Sensory Platform The BRASSEN performs all the functions of a

datalogger and has the task of analyzing climate

behaviors of fire and rain risk in an urban forest by an

intelligent agent, which contains expert systems of the

standards related to environmental variables of

temperature, relative humidity and dew point, an your

relation with urban forests located in the amazon. The

design of such systems, therefore, requires

understanding the joint dynamics of computers,

software, networks, and physical processes [2 - 4]. The

platform (fig. 1) has features like – time

synchronization and geographic information system

(GIS) that collects localization and data of platform [8].

Fig. 1 Hardware Core Architecture of BRASSEN

The platform has – an embedded computer is a

PIC18F252 8 bits microcontroller; SHT75 digital high

precision sensor of temperature and humidity; The

Zigbee (IEEE 802.15.4) module is the wireless

interface channel of communication. The climate

behaviors identified are shown on a map. The box that

houses and protects the hardware has physical

properties for thermal and mechanical shock

absorption.

The Experiment in Maiandeua Island The investigations took place in an urban area of

Maiandeua Island at Amazonian Region (State of Pará

at North of Brazil, 0°37’02.57’’S, 47°32’07.85’’O elev

0 to 4m). The fig. 2 presents the Maiandeua Island.

Since the 1980s there has been an increase in

Maiandeua population, which led to the advancement

of urbanization of the island. Also prohibited the use of

motor vehicles, but there is strong pressure from

residents for the initial release for motor-vehicles and

construction of paved trails.

Since the early 2000s, deforestation and urbanization of

some areas of the island has been noticed that these

places there was a rise in temperature and diseases

related to thermal discomfort, such as viral infections,

colds and respiratory problems [7].

Fig. 2 Localization and area of Maiandeua Island

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The Experiment: The experimental characterization

was organized as follows: 20 places in the island were

selected to be made the data acquisition of temperature,

humidity and dew point. The places chosen are the red

dots seen in fig. 2, this is the area which suffered most

deforestation and urbanization, all this by being near

the sea (Atlantic Ocean) and facilitate transport, trade

and tourism.

In this work the emphasis is on data acquired ate the

“Lagoa da Princesa” (Pond of the Princess), as shown

in fig. 3.

Fig. 3 “Lagoa da Princesa” at Maiandeua Island, May 2012.

The fig. 4 shows the BRASSEN fixed at their point in

“Lagoa da Princesa” for the data acquisition of

temperature, relative humidity and dew point.

Fig. 4 BRASSEN fixed to a tree, in a height of 1.80m from the floor.

Knowledge of Climate Behaviors The urban forests are more humid even though the

temperature of the dew point and vapor pressure are

approximately equal to the external area (city) [7]. The

risk of fire behavior for example is to detect high

temperatures and low humidity in the forest area; this

indicates a high risk of fire. The integration of

information these environmental variables in a rule-

knowledge is a vital challenge to achieve integrated

information of sensors for use with math an empirical

models of their relationships.

The Angstron Forestry Index: To detect behaviors

related to fire risk is used Angstron index [1]:

)27(1,005,0 aTRHB (1)

This index (B) developed in Switzerland in the

1950s is based on data mainly air temperature (Ta) and

relative humidity (RH), both measured daily ate 13:00

hours. There is a cumulative index, for whenever the

value of the index Angstron is less than 2.5 there is a

risk of fire, that is, the day the weather will be favorable

to the occurrence of fire.

The Human Health Indexes in Ecosystems: The

human thermal comfort requirements are related to the

functioning of your organism, whose mechanism,

complex, can be roughly compared to a heat engine that

produces heat according to their activity.

The human needs to release heat in sufficient quantity

so that their internal temperature remains around 37°C

(homeothermy) with very narrow limits between 36.1

and 37.2°C, being 32°C lower limit and 42°C the upper

limit for survival in a state of sickness. When the heat

exchange between the human body and the

environment, occur without great effort, the sense of

the individual’s thermal comfort and your work

capacity is maximum.

However, if environmental conditions cause thermal

sensation of cold or heat is because the body is losing

heat more or less required to homeothermy. This will

only be achieved with additional effort, which

represents overhead, declining work performance and

even problems health.

Human Thermal Comfort Index: The Human

Comfort Index (ICH) was calculated using [7]:

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)10(9

5 aa eTICH (2)

To which Ta is the air temperature in degrees Celsius;

ea is the vapor pressure can be calculated as follows:

100

)( RHee s

a

(3)

Where es is the vapor pressure of saturated air and can

be calculated using the Tetens equation [7]:

)3.237(

)5.7(

1010.6 a

a

T

T

se (4)

The table 1 shows the classification of the degree of

thermal confort in the ICH function of the values

obtained.

Table 1: Human Comfort Index (ICH) Classes

Degrees of Comfort Degrees of Humidity

(°C)

Comfortable 20 – 29

Varying Comfort 30 – 39

Bearable Discomfort 40 – 45

Unbearable Discomfort 46 OR MORE

Human Thermal Discomfort Index: The Human

Discomfort Index (IDH) was calculated using [9]:

5.4136.099.0 da TTIDH (5)

Where Td is the dew point of the air temperature and

can be estimated according to the equations:

),(

),(

RHTa

RHTbT

a

ad

(6)

)ln(),( RHTb

TaRHT

a

aa

(7)

Where a=17.27, b=237.7 (°C) and RH is the relative humidity divided by 100 (one hundred). The values ranges of the discomfort index (IDH) concerning thermal comfort experienced by people are described in table 2 [8]:

Table 2: Ranges relating to conditions of discomfort thermal comfort

experienced by people (IDH)

Effect IDH Range

Stress due to heat IDH > 80

Uncomfortable due to the heat 75 > IDH < 80

Comfortable 60 > IDH < 75

Uncomfortable due to cold 55 > IDH < 60

Stress due to cold IDH < 55

Experimental Results The data acquisition was made on May 20, 2012 under

“Lagoa da Princesa”. The sampling time of acquisition

was set to 1 minute. More than 300 samples (minutes)

were recorded in the database BRASSEN and

understand the minutes range from 11:00AM to

16:00PM, it is during this time interval in which the

diagnostic behavior of environmental variables in

tropical areas should be made to assess levels of risk

and thermal comfort [5][8].

The fig. 5 shows the evolution of temperature e relative

humidity respectively.

0 50 100 150 200 250 30030

35

40

45

50

55

60

65

70Temperature and Relative Humidity Evolution 11:00AM to 16:00PM

Time (min)

Tem

pera

ture

(°C

) /

RH

(%

)

Temperature

Relative Humidity

Fig. 5 Temperature and Relative Humidity Evolutions.

In fig. 5 it is notable that since the beginning of the data

acquisition at 11:00AM occurs the increasing

temperature and decreasing the relative humidity. This

information is important to generate intuitively

behavioral tendencies of environmental variables.

For example, the data acquisition of this trend

characterizes the climate behavior as a hot and dry day,

as this increases the potential risk of fire or thermal

discomfort. However, if the temperature is decreasing

and humidity increasing, this trend leads to possibility

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of rain or thermal comfort. The figures 6 and 7 shows

the evolutions of ICH and IDH respectively.

0 50 100 150 200 250 30046

47

48

49

50

51

52

53

54

55

56Human Comfort Index, ICH Evolution 11:00AM to 16:00PM

Time (min)

ICH

(°C

)

ICH Index at "Lagoa da Princesa", Maiandeua

Fig. 6 ICH Index Evolution.

0 50 100 150 200 250 30084

85

86

87

88

89

90

91

92Human Discomfort Index, IDH Evolution 11:00AM to 16:00PM

Time (min)

IDH

(%

)

IDH Index at "Lagoa da Princesa", Maiandeua

Fig. 7 IDH Index Evolution.

It is notable in figures 6 and 7 that from 13:00PM there

is an evolution of the indexes of comfort and

discomfort, reaching the effect “Stress due to Heat” and

the degree “Unbearable Discomfort” respectively.

On this day at 11:30AM the population was advised to

wear sunscreen and to drink much liquid to avoid

dehydration. The fireman brigade was on alert for risk

of fire, especially between 13:00PM and 14:00PM as

show in fig. 8.

0 10 20 30 40 50 601.3

1.4

1.5

1.6

1.7

1.8

1.9

2Angstron Index, B Evolution 13:00PM to 14:00PM

Time (min)

AN

GS

TR

ON

ANGSTRON INDEX AT "Lagoa da Princesa", Maiandeua

Fig. 8 ANGSTRON Index Evolution.

The procedure to detect a risk of fire at 13:00 at interval

of one hour is a standard condition of the atmosphere of

all terrestrial ecosystems [5][8].

Conclusion The analysis of forest ecosystems (physical

environment) by qualitative knowledge (intelligent

agents) obtained reliable results when compared to

quantitative model of Angstron index. This is due to

this index is not designed for the climate conditions in

antropized areas. When the mathematical model of

climate behavior is unknown, then use indexes models

that are commonly based on empirical knowledge. The

use of indexes for environmental characterization

becomes a reliable and safe solution.

The BRASSEN is distinguished from other solutions in

data acquisition because it contains the knowledge to

analysis of the environment, this is justified by the

interaction that exists between the electronic and

physical layers. The next additions to the sensory

platform are actuators for control of irrigation and soil,

in order to increase the level of interaction with the

environment may act directly in a physical way.

References

[1] O.A. Chase, M.H.K. Sampaio, J.R. Brito-de-Souza, J. Felipe Almeida., “Sensory Platform Architecture Based on

Cyberphysical Systems for Climate Behaviors Detecting in

Urban Forest Environments”, IEEE Sensors Conference, p. 1567-1570, ISBN: 978-1424492909, Limerick, Ireland, UK,

2011.

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[2] O.A. Chase, M.H.K. Sampaio, J.R. Brito-de-Souza, J. Felipe

Almeida., “Data Acquisition System: An Approach to the Amazonian Environment”, IEEE Latin America Transactions,

Vol 10, No. 2, March 2012, ISSN: 1548-0992, BRA, 2012.

[3] N. Wiener, “Cybernetics or Control and Communications in the

Animal and Machine”, 1nd ed., MIT Press, ISBN: 978-

0262730099, USA, 1948.

[4] E. A. LEE, “Cyber Physical Systems: Design Challenges”.

International Symposium on Object / Component / Service-

Oriented Real-Time Distributed Computing (ISORC), May 6, 2008 Orlando, FL, USA, 2008.

[5] INTERGOVERNMENTAL PANEL ON CLIMATE CHANGE

IPCC. “Climate Change 2001: the scientific basis IPCC WG I TAR”. Cambridge: Cambridge Univ. Press. 881p., GBR, 2001.

[6] U. MELO, “Climate Change: Defense and Intelligence”,

Brazilian Intelligence Magazine, n. 5, ISSN: 1809-2632, Brasília-DF, ABIN, BRA, 2009.

[7] V.L. Barradas, “Air temperature and humidity and human

comfort index of some city parks of Mexico City” International Journal of Biometeorology, Jun; 35(1):24-8, MEX, 1991.

[8] H.S.P. ONO, T. Kawamura, “Sensible Climates in Monsoon

Asia”, International Journal of Biometeorology, Vol. 35, n.XX, pp. 39-47, JPN, 1991.

Authors

Almir Tavares Lima Neto received the B.Eng. degree

in computer systems engineering from the Amazonian

Superior Studies Institute, IESAM, Brazil, in 2009 and

the M.Sc. candidate degree in Electrical Engineering &

Energy Systems from the Federal University of Pará,

UFPA, Brazil, in 2012. His research interests lie in

Data Base Management and Embedded Systems.

Marcos Henrique Kumagai Sampaio received the

B.Eng. degree in computer systems engineering from

the Amazonian Superior Studies Institute, IESAM,

Brazil, in 2008 and the M.Sc. candidate degree in

Electrical Engineering from the Federal University of

Pará, UFPA, Brazil, in 2012.

His research interests lie in Robotics, Embedded

Electronical Systems, and Artificial Intelligence.

Otavio Andre Chase (S’10, M’12) received the B.Eng.

degree in computer systems engineering from the

Amazonian Superior Studies Institute, IESAM, Brazil,

in 2007, and the M.Sc. degree in Electrical Engineering

& Energy Systems and the D.Sc. candidate degree from

the Federal University of Pará, UFPA, Brazil, in 2009

and 2012 respectively.

He has been Professor of Systems Engineering at

the Amazonian Federal Rural University, UFRA,

Brazil, since 2010. His research interests lie in

Robotics, Cybernetics and Environmental Complexity.

He was a member of the teams that developed projects

in computer systems, robotics, and forecast sensory

platforms from IESAM, UFPA, UNB, FURG and

UFRA respectively.

He is on the founding member and researcher for

the Centre for Environmental Complexity Synthesis,

CENOSYS, Brazil, since 2011.

José Felipe Souza de Almeida (M´98) Degree in

physics from the Federal University of Pará (UFPA),

Belém, Pará, Brazil (1996). Is a member of the

Academy of Sciences of Pará (ACP). His master's in

physics (UFPA/1999) and Ph.D. in Electrical

Engineering (UFPA/2004) and participated in the

National Program Post–doctored (PNPD-UFPA/2008).

Link Current: Adjunct Professor II of the

Amazonian Federal Rural University (UFRA),

researcher at the Laboratory of Cyberphysical Systems

(LASIC-UFRA) and founding member of Centre for

Environmental Complexity Synthesis (CENOSYS)

located at the Federal University of Rio Grande

(FURG), Rio Grande do Sul, Brazil, 2011.

He works in the Theory and Applications in

Telecommunications, Electrodynamics, Electrical

Systems Protection, and Engineering Education.

Carlos Tavares da Costa Junior (M´92) degree in

Electrical Engineering from Federal University of Pará

(1987), MS in Electrical Engineering from Federal

University of Rio de Janeiro (1991), Brazil. The Master

of the Productique et Automatique Institut National

Polytechnique de Grenoble (1996) and doctorate in

Automatique Et Productique by Institut National

Polytechnique de Grenoble (1999), France.

He is currently Associate Professor at the Federal

University of Pará has experience in Electrical

Engineering with emphasis on Industrial Electronics,

Systems and Electronic Controls.

Acting on the following topics: Power Systems,

Turbogenerators, Adaptive Systems, Supervised

Systems and Fuzzy Control.

the case study on the maiandeua island, at amazonian, brazil

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