MASHCA: Monitoring and Hydro Climatological Analysis of the Urban

Microclimate of Latacunga

David Rivas-Lalaleo

1 a

, Alex Santana G.

2 b

, Cristian Molina

, M

onica Huerta

3 c

, Roger Clotet

4 d

Andr

es P

erez

, Luis Santana

and Fernanda O

nate

Universidad de las Fuerzas Armadas ESPE, Latacunga, Ecuador

Instituto Superior Tecnol

ogico Mar

ıa Natalia Vaca, Ambato, Ecuador

Universidad Polit

ecnica Salesiana, Cuenca, Ecuador

Universidad Internacional de Valencia, Valencia, Spain

Colegio Primero de Abril, Latacunga, Ecuador

Instituto Superior Tecnol

ogico Ba

nos, Ba

nos, Ecuador

Keywords:

Urban Microclimate, Climate Change, IoT, Temperature, Humidity.

Abstract:

The climate change has become one of the most studied problems in recent years. Analyses of climate behavior

have traditionally been treated in a macro way, that is, large areas of territory are analyzed. The development

of humanity in particular, which has been denoted by the increase in population and therefore the growth of

cities, has had an effect on the climate. The change in climatic conditions within cities due to the effects of

construction, urban planning, modiﬁcation of territories, among others, are known as urban micro-climates.

These variations require special attention, since these apparently minimal changes can have a great effect on

the life of the population. The purpose of this project is to study the historical data on the behavior of the

urban climate of Latacunga, through the temporal analysis of the data obtained by the meteorological station

of the Universidad de las Fuerzas ESPE, later to develop micro meteorological stations that are installed in

various locations of the city, ﬁnally the information generated and its corresponding reports will be presented

through a web page, thus allowing to have a tool that allows to identify the behavior of the urban microclimate

of the city of Latacunga. The results obtained have made it possible to identify the maximum, minimum and

most frequent values of temperature, humidity, speed and wind direction. In addition, with the installation of

the new stations, the monitoring of variables such as solar radiation, atmospheric pressure, among others, has

increased. With the information processed, it will allow the generation of recommendations oriented to risk

management, urban planning and citizen security.

1 INTRODUCTION

The dynamics of urbanization and growth of the city

has been gradually occurring due to socioeconomic

factors that beneﬁt the inhabitants due to the

concentration of commercial and ﬁnancial activ-

ity, but with it has also created its climatic patterns

different from its geographical location (Huerta et al.,

2021; Sichiqui et al., 2020; Gabriela et al., 2019),

which are called artiﬁcial or urban microclimates.

https://orcid.org/0000-0001-5958-6606

https://orcid.org/0000-0001-8967-7306

https://orcid.org/0000-0003-4435-7987

https://orcid.org/0000-0001-7474-7674

The origin of urban microclimates arises from neg-

ative aspects such as the smog generated by cars and

local industrial facilities that prevent the entry of solar

rays (Barrios-Bello et al., 2019; Garcia-Cedeno et al.,

2019; Guillermo et al., 2019; Abad et al., 2019). In

addition to this, the architecture of the city also in-

tervenes, such as the morphology that generates wind

turbulence, the construction materials of the buildings

and the asphalt required for the mobility of the means

of transport (Brozovsky et al., 2021; Ulpiani et al.,

2021; Maiullari et al., 2021); All this leads to a vari-

ability in temperature, humidity among other meteo-

rological variables with respect to its macroclimate.

Consequently to these atypical climates there is the

134

Rivas-Lalaleo, D., G., A., Molina, C., Huerta, M., Clotet, R., Pérez, A., Santana, L. and Oñate, F.

MASHCA: Monitoring and Hydro Climatological Analysis of the Urban Microclimate of Latacunga.

DOI: 10.5220/0010838300003118

In Proceedings of the 11th International Conference on Sensor Networks (SENSORNETS 2022), pages 134-143

ISBN: 978-989-758-551-7; ISSN: 2184-4380

 2022 by SCITEPRESS – Science and Technology Publications, Lda. All r ights reserved

probability of an increase in the frequency of fog, in-

tensity of storms, concentration of smog among oth-

ers. Currently in the country several agencies provide

meteorological data but at a general level since they

measure the macroclimate of the provinces; These

data are insufﬁcient to take necessary measures within

the urban area in the face of climatic phenomena,

therefore, Latacunga does not have concise informa-

tion that allows identifying potential risks due to the

variability of the climate within the urban perimeter.

The Universidad de las Fuerzas Armadas ESPE,

on its campus located in the downtown area of

Latacunga has a meteorological station that has a

large amount of scattered information that has been

recorded for several years, in this context an applied

research is proposed for the monitoring and analysis

of climatological variables through the implementa-

tion of additional stations in the Ignacio Flores parish,

which allow expanding the coverage of data acquisi-

tion to analyze the behavior of the climate and iden-

tify the evolution of the urban microclimate with re-

spect to time, said information will be disseminated

through a web application accessible to the public.

This research aims to reduce the impact of micro-

climates in urban areas through the analysis of cli-

matological variations, mitigating the levels of pop-

ulation vulnerability to events produced by extreme

changes in the variables to be monitored. Through

this information, it is proposed to create a growing

awareness among citizens to reduce the impact of mi-

croclimates in urban areas, evidencing the changes

that have occurred over time that are imperceptible

to people as these changes develop in large periods

of time. weather. In this aspect, the Information and

Communication Technologies are used that, through

a web application, allow the user to access this infor-

mation in an easy, fast and intuitive way.

The project provides solid information for

decision-making within the framework of the city’s

centralized risk management system, strengthening

local capacities through technology transfer in order

to implement mitigation measures for climate varia-

tions through urban planning and ecology of the city

that limits new urban development zones under con-

cepts of environmental sustainability such as genera-

tion, protection and restoration of green areas; guar-

anteeing the improvement of climatic conditions in

the interior of the city and the reduction of socio- en-

vironmental inequalities at the local level (Padmanab-

hamurty, 1990; Yoon et al., 2017).

2 METHODOLOGY

This section it is based on the analysis of histori-

cal data and the installation of the meteorological

station, taking into account the manufacturer’s stan-

dards, among which the selection of an appropri-

ate geographic location is established; the position,

height and orientation so that the sensors work in

their ideal ranges without generating errors due to

improper handling(Teichmann et al., 2021; Marando

et al., 2022; Amani-Beni et al., 2022). By means of

a checklist, validate the operation of each of the ele-

ments of the station, guaranteeing the ﬁdelity of the

data, an essential basis for determining the urban mi-

croclimate of Latacunga(Bonan, 2000; Brown, 2018;

Barton, 2013).

This research is based on procedures related to

theoretical and experimental research with data col-

lection since October 12, 2020, which consists of a

main station, a mini station and four micro stations

with a sending frequency per minute, of the which

have been collected 400,000, 3,000 and 170,000

records respectively; The diagram is shown in Fig. 1.

The methodology applied to carry out the proposed

objectives involves the general guidelines of the sci-

entiﬁc method, differentiating itself into four phases:

Figure 1: Diagram of the methodology.

2.1 Implementation Phase

This section it is based on the analysis of histori-

cal data and the installation of the meteorological

station, taking into account the manufacturer’s stan-

dards, among which the selection of an appropri-

ate geographic location is established; the position,

height and orientation so that the sensors work in

their ideal ranges without generating errors due to im-

proper handling. By means of a checklist, validate the

operation of each of the elements of the station, guar-

anteeing the ﬁdelity of the data, an essential basis for

determining the urban microclimate of Latacunga.

2.2 Simulation Phase

In this section it is argued the individual operation of

each element in charge of the digitization of the in-

formation based on the conceptual dimensioning, it is

done using specialized software and steps such us:

The logical part of the meteorological station

schedules the sending of the variables in an adequate

format with a sampling time that allows gathering

as much information as possible and reporting in the

MASHCA: Monitoring and Hydro Climatological Analysis of the Urban Microclimate of Latacunga

135

event of sensor failures or power shortages; Regard-

ing the technological infrastructure, it corresponds to

the conﬁguration of the database server, design of the

database with its respective tables and access to the

database through a WAN network; The analysis of the

stored data carried out through a workﬂow that per-

forms the data processing according to the design of

the database and must be replicable for the data avail-

able from the station of Universidad de las Fuerzas

Armadas ESPE. The information monitored is vali-

dated through a dashboard on the web.

2.3 Integration Phase

In this part of the investigation each of the stages is in-

corporated, verifying the ﬂow of information through

each equipment to determine the validity of the data,

the rate of information loss, errors in the information

frames generated, possible interruptions in communi-

cation and detection of common errors produced by

damage or malfunction of the station. A sampling is

carried out to verify the data published in the web in-

strument panel and using a tool to observe the trafﬁc

of the web page to determine the inﬂuence of the in-

formation provided within the citizens of Latacunga.

3 RESULTS

For process and analyze the historical information ob-

tained by the station of Universidad de las Fuerzas Ar-

madas ESPE, the following procedure was followed

with the data collected during 2019 by the station with

geographic coordinates (0°56’09.3”S 78°36’45.6”W)

that have been stored in ﬂat ﬁles. The Fig. 2,

represents the extraction, transformation and loading

(ETL) model; The data is extracted from the differ-

ent ﬁles that are transformed into the date and time

format, erroneous values are also eliminated and the

decimal number format is converted to be able to per-

form the operations necessary for their analysis.

The data is dumped to the database by means of a

synchronization from the transformed ﬂat ﬁle.

Figure 2: ETL Big data.

After this process, it can be detailed that dur-

ing the established period of time (01/01/2019 to

12/31/2019), 2,627,951 records have been obtained

between the variables humidity, temperature, wind

speed and wind direction with a 1 minute sampling

period.

3.1 Temperature Analysis

From the analyzed data it can be observed the disper-

sion of temperature values behaved according to Ta-

ble 1, where the maximum values have been 25.58 °C

in the month of November, while the lowest values

2.97°C are reported in September; The Fig. 3, de-

scribes that 50% of the data are in the range of 11.96

°C to 16.49 °C.

Table 1: Statistics of the temperature variable.

Temperature (°C)

Min. 2.97

Q1 11.96

Median 13.25

Average 14.21

Q3 16.49

Max 25.58

Figure 3: Temperature dispersion.

In the frequency distribution presented in Fig. 4, it

is observed that the value that is repeated the most is

15°C followed by a value of 10°C, the atypical values

are found in the values lower than 5°C and higher at

20°C.

Figure 4: Temperature distribution.

SENSORNETS 2022 - 11th International Conference on Sensor Networks

136

The behavior of the average temperature through-

out the months is observed in Fig. 5; It is determined

that the month of November has a high value while

the months of June and July have low values, in the

scale of the ﬁrst one month is January and the last

months is December.

Figure 5: Average monthly temperature distribution.

In the Fig. 6, presents the dynamics of the aver-

age temperature within 24 hours of the day; In the 7

:00 range it has an average of 12.11°C, while at 12:00

the average is 18.33 ° C and at 18:00 the average has

been 14.50°C. It is also determined that the tempera-

ture increases from 7:00 to 14:00 and decreases from

15:00 to 21:00; the highest temperature values are

from 12:00 to 15:00 and the lowest from 5:00 to 6:00,

the scale represents 24 hours.

Figure 6: Average hourly temperatures.

3.2 Humidity Analysis

The registered values of this variable show that

the months from June to December present the

highest level of humidity 100% while in the months

of September and November the lowest levels are

16.81% and 13.87%. Half of the recorded data are in

the range of 67.97% to 93.66% Table 2, its median

is at a value of 86.19%, which shows that there is a

greater dispersion between the values of 67.97% and

86.19% Fig. 7.

Table 2: Statistics of the humidity variable.

Humidity (%)

Min. 13.87

Q1 67.97

Median 86.19

Average 80.20

Q3 93.66

Max. 100

Figure 7: Moisture dispersion.

In Fig. 8, it is observed that the value that is re-

peated the most within the year is 90% and the atyp-

ical values are distributed among the values less than

30%.

Figure 8: Moisture distribution.

The incidence of average humidity in the month of

September is the lowest, on the other hand, the highest

is registered in the month of February. The Fig. 9, in

general, the annual average humidity is 80.20%.

The distribution of the average humidity with re-

spect to the hours of the day is shown in The Fig.

10, in which it is observed that the lowest values of

average humidity are in the range of 13:00 to 15:00;

There is also the decrease in humidity from 6:00 to

12:00 and increases from 16:00 to 21:00.

3.3 Wind Speed Analysis

This meteorological variable describes a maximum

value of 10.8 m / s in the month of October, 50% of

MASHCA: Monitoring and Hydro Climatological Analysis of the Urban Microclimate of Latacunga

137

Figure 9: Average monthly humidity distribution.

Figure 10: Hourly average humidity.

the data are clustered between 0.7 m/s and 2.5 m/s,

Table 3. The lower part of the box (Q1-median ) is

less than the upper one (median-Q2); This means that

the values between 25% and 50% of the data are less

dispersed than between 50% and 75%, Fig. 11.

Table 3: Statistics of the variable wind speed.

Wind speed (m/s)

Min. 0

Q1 0.7

Median 1.4

Average 1.78

Q3 2.5

Max. 10.8

Figure 11: Wind speed dispersion.

The Fig. 12, presents the histogram with the fre-

quency of the different wind speeds with a value of

0.5 m/s that is repeated more frequently, followed by

1 m/s and outliers in an interval of 6 m/s onwards.

Figure 12: Wind speed distribution.

The distribution of the average monthly wind

speed is not uniform as shown in Fig. 13, having a

maximum average value in the month of June and a

minimum in the months of April, May and Novem-

ber, it could be argued that its value It tends to 1.78

m/s which represents its annual average value. In Fig.

14, it can be contrast whit the month in which there is

less wind is in the month of May.

Figure 13: Average monthly distribution of wind speed.

Figure 14: Monthly percentage of calm minutes.

The wind speed distributed by hours presents an

interval from 7:00 to 13:00 in which the wind speed

SENSORNETS 2022 - 11th International Conference on Sensor Networks

138

increases until it reaches a maximum value at 14:00,

after which it begins to decrease in the interval from

15:00 to 19:00, in the rest of the hours. presents a

uniform value with slight variations, Fig. 15.

Figure 15: Hourly average wind speed.

3.4 Wind Direction Analysis

This variable is described in degrees having as ref-

erence points 0°, 90°, 180° and 270° that represent

North, East, South and West. Table 4 shows that 50%

of the data are distributed between the values from

99° to 189°, with more dispersed values from 189°

onwards, Fig. 16.

Table 4: Wind speed dispersion.

Wind direction (°)

Min. 0

Q1 99

Median 150

Average 146.01

Q3 189

Max. 354

Figure 16: Wind speed dispersion.

The frequency distribution of the wind direction

Fig. 17, describes that most of the time it has a value

of 170 ° and 180 ° that represent a trend towards the

South.

Figure 17: Wind direction distribution.

The Fig. 18, describes a clearly preferential direc-

tion in the South-East quadrant that concentrates the

greatest amount of data, emerging on the South side.

Figure 18: Polar representation of the annual wind direc-

tion.

In this part can see in Fig. 19, that in the months

of April, May and November there is a partial accu-

mulation towards 30 ° with a high concentration of

values, which contrasts with the minimum monthly

average values of wind speed, while in June and Julio

a symmetry is detected with respect to 180 ° (South).

Figure 19: Polar representation of every months of the year

wind direction.

MASHCA: Monitoring and Hydro Climatological Analysis of the Urban Microclimate of Latacunga

139

3.5 IoT Implementation

In order to meet the second speciﬁc objective which

mentions the implementation of a meteorological sta-

tion for the acquisition of data in situ, this station was

selected according to the following criteria: number

of sensors, connectivity, power supply and the avail-

ability of a platform in the cloud. In Table 5, the me-

teorological variables and their measurement ranges

are detailed with their respective accuracy value that

guarantees that the obtained value is close to the real

value.

Table 5: Measurement ranges.

Sensors Values Accuracy

Temperature (C) -40 a 65 ±1ºC

Humidity(%) 10 a 99 ± 5%

Barometric Pressure 8.85 a 32.50 ± 0.08

(inHg) inHg

Solar radiation (lx) 0 a 200000 ±15%

UV index 0 a 15 ± 1

Rain (mm) 0 a 10000 ± 10%

Direction of the wind 0 a 360 ± 1º

Wind speed (km / h) 0 a 160 ±10%

The equipment that meets these characteristics

is the WS2902-B model manufactured by Ambient

Weather, this station is currently installed at the Uni-

versidad de las Fuerzas Armadas ESPE campus Lat-

acunga. After the implementation of this equipment,

the following trend graphs were obtained for each of

the climatological variables Fig. 20, the same ones

that represent the data of a complete week

Figure 20: Trends of meteorological variables: a) Tempera-

ture, b) UV Index, c) Humidity, d) Solar Radiation, e) Wind

Direction, f) Rain, g) Wind Speed and h) Relative Pressure.

In order to increase the measurement points, re-

mote micro stations are designed which have as a

characteristic the measurement of temperature and

humidity with storage in the cloud. These teams are

developed in the following architecture that is detailed

in Fig. 21, where the design of devices was done

through the use of Wireless technology. Data Analyt-

ics in the Cloud is carried out through the communica-

tion of data between the device and the development

platform, the use of data involves the study of the his-

torical analytics of the data with statistical techniques.

Figure 21: Data Architecture.

In order to begin, the platform used for the de-

velopment of the architecture is described. This is

GOOGLE CLOUD PLATFORM. Thanks to all the

characteristics of integration, programming and use of

data, through friendly programming interfaces, with

different ecosystems of devices connected to the in-

ternet, once the hardware has been designed, im-

plemented and installed, the measurement processes

and their corresponding adjustments are carried out

through comparative calibration techniques with stan-

dard instruments.

Figure 22: Instances of standard equipment development,

Mini-MASHCA.

The information acquired by these points was con-

trasted with the Fluke-971 (TEMPERATURE, HU-

MIDITY METER) and Fluke-923 (AIR VELOCITY

METER) standard equipment. Obtaining a measure-

ment error between the standard instrument and the

micro stations with the following quantities: 9.2% for

temperature and 2.5% for humidity, this can be seen in

Fig. 22 where the value acquired by the micro station

is displayed versus the data acquired by the standard

equipment.

SENSORNETS 2022 - 11th International Conference on Sensor Networks

140

In order to comply with the following speciﬁc ob-

jective in which it is mentioned developing a web ap-

plication to visualize the data and interpret the analy-

sis thereof, a website has been implemented accord-

ing to the following characteristics.

3.6 Web Site Diagram

In the following URL: (https://sites.google.com/

view/mashca), the information of the station installed

in the Universidad de las Fuerzas Armadas ESPE

campus Latacunga and the micro meteorological sta-

tions installed in urban areas are displayed, In this

web application you can see the time values of each of

the variables with their respective trends in a 24 hour

range and the table of values of the previous day, Fig.

23.

Figure 23: MASHCA Web Application.

Using the GOOGLE ANALYTICS tool, as shown

in Fig. 24, it has been possible to observe the behav-

ior of the users who enter the website, the data that

are most consulted. It has been determined that mea-

surement of data visited by users. (where the number

of page views is shown, the page value, as well as the

active users.

Figure 24: Measurement of data visited by users.

After fulﬁlling the aforementioned objectives,

which have corroborated the general objective of this

project, which is ”To develop a monitoring and analy-

sis system of the urban microclimate of Latacunga.” ,

where a historical record of the behavior of the urban

climate of Latacunga with respect to the year 2019 has

been generated, based on the information provided

by the station of The Universidad de las Fuerzas Ar-

madas ESPE. Finally, the urban microclimate of the

city was determined through the implementation of

new meteorological stations, among the indicators is

information such as the date of consultation of each

tag (device), the number of consultations made to the

tag and the respective events of the Climatological

variables collected according to the season that is ac-

cessed. All this is shown in Fig. 25. As a ﬁnal re-

sult, it has been shown that under the cloud computing

scheme where historical data has been used, new data

stored in the cloud, through meteorological stations

under the IoT paradigm, it has been possible to moni-

tor the different nuances of the urban microclimate of

the city of Latacunga.

Figure 25: Dynamic data trend.

4 CONCLUSION

The study of urban microclimates at present is serving

not only the knowledge of the behavior of the climate

in a certain geographical area of the country, but also

in the planning of study disciplines in the social ﬁeld

such as tourism; This by virtue of the data collected,

processed and exposed, since in the ﬁeld of tourism in

general and in the same sector of the economy but in

Latacunga in particular, due to its architectural com-

position, allows public or private entities involved in

tourism, forecast the behavior of the weather at cer-

tain hours, which in the case of this recommendation

is tourism, that is, the data will allow tourists to know

how the weather will behave in the urban part of Lat-

acunga on a given day, this since The city is a purely

urban or cultural tourist destination, and the weather

factor is a transcendental point in the daily planning

of the tourist, no travelers wants to go to the beach in

cold weather, so neither does any cultural tourist want

to visit the city in a day of heavy rain.

With the fulﬁlment of the general objective and

the speciﬁc objectives, the hypothesis that mentions

that from the analysis of the data obtained by the me-

teorological stations can be made a map of the be-

havior of the urban microclimate of Latacunga can

be considered, this can be done when the quantity of

existing data acquires the necessary density to cap-

ture the resource, which could be veriﬁed through

the implementation of micro meteorological stations,

MASHCA: Monitoring and Hydro Climatological Analysis of the Urban Microclimate of Latacunga

141

developed to measure, with temperature and humid-

ity measurement characteristics, within the standard-

ized measurement ranges for the stations meteorolog-

ical conditions and with an average error of less than

3%.With the application of the measurement of the

climate carried out by the meteorological stations in-

stalled in strategic points of the urban area of Lata-

cunga, the changes generated by urban development

and the presence of microclimates, due to structural

changes of buildings throughout history, were demon-

strated. of the city since the synergy of new and old

constructions in the environment give way to conﬁrm

this change in the data, with comparisons with his-

torical data of the climate registered in the city espe-

cially using databases of state entities. It can also be

mentioned that the historical information of the cli-

mate in Latacunga that was recorded by the station

was contrasted with the information acquired in real

time through the Data Studio software which gener-

ates reports of the behavior of the climate in the city,

having an appreciation of data taken in urban environ-

ments.

The dissemination of the results obtained as a test

has been registered among a limited group of people

who have generated recommendations to improve the

graphic interface of the website, the ways of present-

ing the data, navigation schemes among others, thus

allowing improve interaction with users. In this sec-

tion, the participation of teachers and students of the

participating universities, members of local govern-

ment bodies, citizens in general, among others, who

present a wide spectrum of points of view on the pre-

sentation of the information acquired and processed,

can be noted. Where it was determined that the most

appropriate way for researchers to access this data is

through a web page, due to the versatility of sharing

information regardless of the operating system, which

is used due to the expertise of the developers. Realiz-

ing that it is the most appropriate form of presentation

of data for technical reasons such as: data availabil-

ity, latency, ability to mine data in this type of web

applications.

The reports generated from the analyses carried

out present a glimpse of the climate behavior within

the city. This information was obtained through the

analysis of large volumes of data, for which cloud

servers were used where the data generated by the

professional weather station and the weather micro-

stations are stored, the reports are processed and gen-

erated. are presented on the website, which can be

accessed by any citizen to consult the behavior of the

climate in real time of the climatological variables

that affect the microclimate, it should be noted that

all the information contained in the site has been de-

scribed in the previous sections, where the parameters

of time, amount of data, frequency of use as well as

climate variables are clearly identiﬁed in detail.

FUTURE WORKS

The future lines to follow are the use of artiﬁcial intel-

ligence in order to generate algorithms for predicting

climate behavior, adding other types of variables such

as urban maps, urban planning, among others. In the

design of devices, the implementation of spaces con-

nected to the internet with 5G can be considered, im-

proving the capacity of the devices to collect informa-

tion as well as becoming pioneers in the development

of this type of technology. On the other hand, a dis-

semination plan for the project must be carried out at

the level of social networks, citizen groups.

ACKNOWLEDGEMENTS

The authors thank the higher education institutions

that contributed to the research with their authors,

such us: Universidad de las Fuerzas Armadas ESPE,

Instituto Superior Tecnol

ogico Mar

ıa Natalia Vaca,

Universidad Polit

ecnica Salesiana, Cuenca, Univer-

sidad Internacional de Valencia, Colegio Primero de

Abril, Latacunga, Ecuador, Instituto Superior Tec-

nol

ogico Ba

nos, Consorcio de Gobiernos Aut

onomos

Provinciales del Ecuador, Red de desarrollo urbano

sostenible Cotopaxi-GIS, and the projects MASHCA-

REDUS 2020, ”Prototype of early warning systems

for frost”, as well as the project number ESPE-008-

007-2017-07-27: “PLATANO – Intelligent Techno-

logical Support Platform for small and medium agri-

cultural producers”, carried out jointly with the Uni-

versidad Politecnica Salesiana collaboration, and the

Wicom Energy Research group.

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