PPG.EGPSA/ITEGAM
URI permanente desta comunidadehttps://rigalileo.itegam.org.br/handle/123456789/1
A comunidade dispõe da produção técnica e científica do Programa de Pós-graduação em Engenharia, Gestão de Processos, Sistema e Ambiental (PPG.EGPSA) do Instituto de Tecnologia e Educação Galileo da Amazônia (ITEGAM), fruto da atividade de pesquisa e desenvolvimento (P&D). É possível acessar os trabalhos de conclusão do programa de pós-graduação, artigos e livros vinculados a pesquisa, desenvolvimento, inovação e extensão.
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186 resultados
Resultados da Pesquisa
Item Smart Energy: aplicação do sistema fotovoltaico utilizando algoritmos genéticos para tomada de decisão na indústria 4.0(Instituto Nacional da Propriedade Industrial (INPI), 2024) OLIVEIRA, Adriana Waschington Carneiro de; SILVA, Simone daThis document certifies the registration of the "Smart Energy" software, which employs genetic algorithms for decision-making in the context of Industry 4.0. The application focuses on photovoltaic systems, aiming to optimize industrial processes through advanced computational techniques.Item Algoritmo Genéticos aplicado à Qualidade de Energia - DASHBOARD(Instituto de Tecnologia e Educação Galileo da Amazônia, 2025) ALMEIDA, Anderson Alexandre Silva de; LEITE, Jandecy CabralRegistration of a computer program entitled "Genetic Algorithms Applied to Power Quality - DASHBOARD," valid for 50 years from January 1st following the publication date (12/17/2024). The program was created for specific applications outlined in the technical areas defined by the National Institute of Industrial Property (INPI).Item Sistema de Teste Funcional com Rastreabilidade para Carregadores de Celular(Instituto de Tecnologia e Educação Galileo da Amazônia, 2025) MAUÉS, Elvis Jardim; LEITE, Jandecy CabralRegistration of a computer program entitled "Functional Test System with Traceability for Cell Phone Chargers," valid for 50 years from January 1st following the publication date (11/14/2024). Developed in C++, the program applies to specific areas defined by the National Institute of Industrial Property (INPI).Item Redes Neurais Artificiais para Comparação entre Propriedades Mecânicas Materiais(Instituto de Tecnologia e Educação Galileo da Amazônia, 2025) DIAS, Jonathan Oliveira; LEITE, Jandecy CabralRegistration of a computer program entitled "Artificial Neural Networks for Comparison of Mechanical Properties of Materials," developed in Python. The program is valid for 50 years from January 1st following the publication date (12/03/2024). Its applications cover engineering, materials, and artificial intelligence areas as specified by the National Institute of Industrial Property (INPI).Item MODELO DE REDE NEURAL PARA PREVISÃO DE DESEMPENHO MECÂNICO DE MATERIAIS ESTRUTURAIS E POLIMÉRICOS(Instituto de Tecnologia e Educação Galileo da Amazônia, 2025) BRITO JUNIOR, Jorge de Almeida; LEITE, Jandecy CabralThis document certifies the registration of the software entitled "Neural Network Model for Predicting Mechanical Performance of Structural and Polymeric Materials." The program, developed in Python, employs deep learning techniques to predict mechanical properties of structural and polymeric materials. The application contributes to advancements in material studies, optimizing industrial processes and scientific research.Item Sistema Automatizado para Monitoramento e Gerenciamento das Pulseiras Eletrostáticas por Meio de Dashboard(Instituto de Tecnologia e Educação Galileo da Amazônia, 2025) MAUÉS, Elvis Jardim; LEITE, Jandecy CabralThis document certifies the registration of the software entitled "Automated System for Monitoring and Managing Electrostatic Wristbands via Dashboard." Developed in C++, the system enables real-time control and monitoring of electrostatic wristbands used in industrial environments, with data visualization through an intuitive dashboard. The program aims to enhance safety and operational efficiency, providing an innovative solution for managing electrostatic devices.Item Aplicação de Inteligência Artificial para Previsões e Ajustes de Fator de Potência (FP) por Fase(Instituto de Tecnologia e Educação Galileo da Amazônia, 2025) ALMEIDA, Anderson Alexandre Silva de; LEITE, Jandecy CabralThis document certifies the registration of the software entitled "Application of Artificial Intelligence for Predictions and Adjustments of Power Factor (PF) by Phase." Developed in Python, the program leverages artificial intelligence techniques to accurately predict and adjust the power factor of electrical systems. The solution aims to optimize the energy performance of three-phase systems, reducing losses and promoting greater operational efficiency.Item Gestão de Energia Solar - Consumo, Geração e Bateria(Instituto de Tecnologia e Educação Galileo da Amazônia, 2025) ALMEIDA, Anderson Alexandre Silva de; LEITE, Jandecy CabralThe computer program titled "Solar Energy Management - Consumption, Generation, and Battery" was developed to optimize solar energy consumption and generation, integrating battery management to maximize energy efficiency.Item E_SOLAR_GERAÇÃO_REAL - Monitoramento de Consumo Real de Energia Solar(Instituto de Tecnologia e Educação Galileo da Amazônia, 2025) ALMEIDA, Anderson Alexandre Silva de; LEITE, Jandecy CabralThe computer program titled "E_SOLAR_GERAÇÃO_REAL - Real-Time Solar Energy Consumption Monitoring" was developed to perform real-time monitoring of solar energy consumption, providing precise data for efficient energy management in photovoltaic systems.Item Arquitetura Computacional para Controle de Monitoramento de Qualidade de Energia utilizando Ferramentas de Inteligência Artificial focado na Indústria 4.0 com Integração de Energias Renováveis(Instituto de Tecnologia e Educação Galileo da Amazônia, 2025) ALMEIDA, Anderson Alexandre Silva de; LEITE, Jandecy CabralThe computer program titled "Computational Architecture for Energy Quality Monitoring Control" employs Artificial Intelligence tools to implement advanced solutions for energy quality monitoring. The program is geared towards Industry 4.0 and aims to integrate renewable energy into cutting-edge industrial systems.