Banca de QUALIFICAÇÃO: PEDRO HENRIQUE MEIRA DE ANDRADE

Uma banca de QUALIFICAÇÃO de DOUTORADO foi cadastrada pelo programa.
STUDENT : PEDRO HENRIQUE MEIRA DE ANDRADE
DATE: 17/12/2021
TIME: 14:00
LOCAL: meet.google.com/cbz-ojcp-arx
TITLE:

TEDA Regressor: An Unsupervised Regression Technique Based on TinyML Approach

KEY WORDS:

TEDA Regression, TinyML, Unsupervised, Regression, data stream.

PAGES: 70
BIG AREA: Engenharias
AREA: Engenharia Elétrica
SUBÁREA: Eletrônica Industrial, Sistemas e Controles Eletrônicos
SPECIALTY: Automação Eletrônica de Processos Elétricos e Industriais
SUMMARY:

The insertion in the network of everyday objects within the reality of the Internet of Things (IoT) brings new possibilities such as data processing at the edge of the application. When processing is performed in a resource-constraints device, such as a microcontroller, and using machine learning techniques, we have the concept of TinyML (Tiny Machine Learning). Within this context, the present work develops an unsupervised regression technique aimed at TinyML and IoT applications involving data streams. The technique is based on the concepts of typicality and eccentricity of samples from the dataset to be processed and uses a recursive least squares filter approach for regression. Preliminary results, extracted from 2 data sets, proved to be promising and with conditions for improvement.

BANKING MEMBERS:
Presidente - 2885532 - IVANOVITCH MEDEIROS DANTAS DA SILVA
Interno - 1153006 - LUIZ AFFONSO HENDERSON GUEDES DE OLIVEIRA
Externo à Instituição - CLAUBER GOMES BEZERRA - IFRN