PROGRAMA DE PÓS-GRADUAÇÃO EM ENGENHARIA ELÉTRICA (PPGEE)
UNIVERSIDADE FEDERAL DA PARAÍBA
- Telefone/Ramal
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Não informado
Notícias
Banca de DEFESA: VIRGINIA VIEIRA AIRES
Uma banca de DEFESA de MESTRADO foi cadastrada pelo programa.
DISCENTE: VIRGINIA VIEIRA AIRES
DATA: 27/02/2026
HORA: 15:00
LOCAL: https://meet.google.com/cik-gwmx-fut
TÍTULO: Study and Implementation of a Smart Tree in the IoT Context Aiming at Real-Time Measurement of Meteorological Data
PALAVRAS-CHAVES: Wind Prediction, Wavelet Transform, Smart Tree, Machine Learning, Climate Modeling, Temperature Sensors.
PÁGINAS: 52
GRANDE ÁREA: Engenharias
ÁREA: Engenharia Elétrica
RESUMO: Given the growing need for innovative and accessible environmental monitoring solutions,
especially in hard-to-reach areas, this study investigates the use of temperature sensors
installed on a structure inspired by natural trees, referred to as the SmartTree, located at
the Center for Alternative and Renewable Energies (CEAR) of the Federal University of
Paraíba, to estimate meteorological parameters such as wind speed and wind direction.
Motivated by this context, the study proposes an alternative approach to conventional
meteorological monitoring by employing tree inspired structures as natural platforms for
climate sensing, based on the hypothesis that internal temperature variations within the
tree trunk, captured by sensors installed at different heights, depths, and orientations,
indirectly reflect external patterns of wind and ambient temperature. The methodology
is based on the application of the Discrete Wavelet Transform to extract multiscale
features, which are used as input for machine learning models including Random Forest,
Gradient Boosting, Support Vector Machine, and Linear Regression. Data were collected
from nine sensors positioned at different heights and orientations and complemented
by additional information from a nearby weather station. Among the evaluated models,
Random Forest achieved the best performance, reaching high accuracy with a mean
absolute percentage error of 6.60%. The results confirm the potential of the tree inspired
solution as a viable alternative for climate monitoring, with important applications such
as forest fire prevention.
MEMBROS DA BANCA:
Presidente(a) - 1523920 - CLEONILSON PROTASIO DE SOUZA
Interno(a) - 1744179 - WASLON TERLLIZZIE ARAUJO LOPES
Externo(a) à Instituição - YAJUN AN