Banca de QUALIFICAÇÃO: RAFAEL DIAS RIBEIRO DE ALMEIDA

Uma banca de QUALIFICAÇÃO de MESTRADO foi cadastrada pelo programa.
STUDENT : RAFAEL DIAS RIBEIRO DE ALMEIDA
DATE: 21/07/2023
TIME: 08:30
LOCAL: Videoconferência
TITLE:

IoT device for failure prevention and remote monitoring in electrical equipment


KEY WORDS:

Internet of Things, Predictive Maintenance, Artificial Neural Networks.


PAGES: 42
BIG AREA: Engenharias
AREA: Engenharia Elétrica
SUMMARY:

The utilization of technology in daily life pertains to the assimilation of diverse tools and technological devices into routine activities. Since the emergence and proliferation of computers and the internet, technology has progressively permeated our lives, profoundly influencing our communication, work, recreation, and even healthcare practices. Within this context, one recently materialized topic, long contemplated, is the Internet of Things (IoT).

The term IoT refers to a network that harnesses technology to govern and administer an array of devices and systems within its purview. These systems encompass lighting, security, heating, cooling, appliances, and entertainment, among others. The fundamental objective of the Internet of Things is to streamline users' lives by bestowing enhanced comfort, security, energy efficiency, and convenience. Through intelligent and interconnected devices, users can remotely regulate various facets of their environment, whether by means of smartphone applications, virtual assistants, or even voice commands.

This endeavor aims to develop a device for monitoring and detecting malfunctions in diverse electrical equipment. To accomplish this, the IoT device will be crafted upon a robust foundation of electronics, microcontrollers, sensors, and Artificial Neural Networks (ANNs). It will be integrated into the electrical power circuitry of the equipment, thereby assimilating it into an IoT network that will duly apprise the user regarding the operational state or identified faults. Moreover, it will proactively recognize fault patterns prior to their occurrence, provide data pertaining to energy consumption, and enable remote control functionality.


COMMITTEE MEMBERS:
Presidente - 2566657 - SAMAHERNI MORAIS DIAS
Interno - 1577068 - KURIOS IURI PINHEIRO DE MELO QUEIROZ
Externo ao Programa - 2757086 - JOILSON BATISTA DE ALMEIDA REGO - UFRN
Notícia cadastrada em: 05/07/2023 10:37
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