Registro de programa de computador
URI permanente para esta coleçãohttps://rigalileo.itegam.org.br/handle/123456789/9
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Resultados da Pesquisa
Item Desenvolvimento de um Sistema para Monitoramento de Paradas de Máquinas em Linhas de Produção Aplicado ao Processo da Indústria 4.0(Instituto de Tecnologia e Educação Galileo da Amazônia, 2025) LEITE, Jandecy Cabral; SILVA, Valdir Francelino da; SILVA, Simone daCertificate issued by the Brazilian National Institute of Industrial Property (INPI) for the registration of the computer program entitled Development of a System for Monitoring Machine Downtime in Production Lines Applied to the Industry 4.0 Process. Developed in Python, the software aims to monitor equipment stoppages in production lines, providing strategic data to reduce losses, increase operational efficiency, and support decision-making in industrial environments aligned with Industry 4.0 concepts. The registration grants legal protection of the software for 50 years under Law No. 9.609/1998, ensuring proprietary rights to ITEGAM and the authors.Item Sistema Inteligente de Verificação de Pedidos com Visão Computacional e Aprendizado de Máquina para Expedição Industrial 4.0(Instituto de Tecnologia e Educação Galileo da Amazônia, 2025) THEOCHAROPOULOS, Scarlette Silva; SILVA, Maeli Oliveira da; CAMPOS, Paola SoutoCertificate issued by the Brazilian National Institute of Industrial Property (INPI) for the registration of the computer program entitled Intelligent Order Verification System with Computer Vision and Machine Learning for Industrial 4.0 Shipping. Developed in Python, the software aims to optimize industrial processes by integrating computer vision algorithms and machine learning techniques to automate shipping in the context of Industry 4.0. The registration provides legal protection for 50 years under Law No. 9.609/1998, ensuring the proprietary rights of the authors and the holding institution over its technological application.Item Técnicas da Indústria 4.0 aplicadas na melhoria do processo de corte dos terminais das baterias de íon-Lítio(Instituto de Tecnologia e Educação Galileo da Amazônia, 2025) MACIEL, Lincoln Fabio Luiz; NASCIMENTO, Manoel Henrique Reis; ALENCAR, David Barbosa deSoftware registration using Industry 4.0 techniques to improve the terminal cutting process in lithium-ion batteries, developed in C++ and focused on industrial applications in areas AD-06, IN-01, and IN-05.Item Aplicação de Inferência Fuzzy Para Tomada de Decisão em Processos de SMT(Instituto de Tecnologia e Educação Galileo da Amazônia, 2025) LEITE, Herbety Lima; NASCIMENTO, Manoel Henrique Reis; ALENCAR, David Barbosa de; BRITO JUNIOR, Jorge de AlmeidaSoftware developed in Python applying fuzzy inference for decision-making processes in SMT (Surface-Mount Technology), targeting industrial process optimization. The registration is recognized under Brazilian intellectual property law and categorized within engineering and automation domains.Item Sistema Inteligente para monitoramento de subestações elétricas integrado à plataforma SGE: uma aplicação da Indústria 4.0(Instituto de Tecnologia e Educação Galileo da Amazônia, 2025) SANTOS JUNIOR, Hélio Andrade dos; NASCIMENTO, Manoel Henrique Reis; ALENCAR, David Barbosa dePython-based software developed for intelligent monitoring of electrical substations. Integrated with the SGE platform, it provides functionalities tailored for Industry 4.0 applications, enabling automation, real-time data acquisition, and remote diagnostics of critical infrastructure. Classified under electrical engineering and industrial automation.Item Sistema inteligente para detecção de falhas utilizando algoritmo de Árvore de Decisão(Instituto de Tecnologia e Educação Galileo da Amazônia, 2025) PENEDO, Jorge Eduardo Santos; PALADINI, Edson Pacheco; SILVA, Carlos Américo de Souza; LEITE, Jandecy CabralPython-based software employing Decision Tree algorithms to detect faults in industrial or computational systems. Designed for Industry 4.0 environments, it aims to enhance operational reliability and enable automated diagnostics.Item Sistema inteligente para detecção de falhas utilizando algoritmo de máquina de vetores de suporte – SVM(Instituto de Tecnologia e Educação Galileo da Amazônia, 2025) SILVA, Carlos Américo de Souza; PALADINI, Edson Pacheco; PENEDO, Jorge Eduardo Santos; LEITE, Jandecy CabralPython-based software using Support Vector Machine (SVM) algorithms for fault detection systems. Aimed at intelligent automation in industrial settings, the software enhances predictive decision-making accuracy in the context of Industry 4.0.Item Sistema inteligente para classificação de falhas na manufatura de placas utilizando algoritmo de Machine Learning KNN(Instituto de Tecnologia e Educação Galileo da Amazônia, 2025) PENEDO, Jorge Eduardo Santos; PALADINI, Edson Pacheco; SILVA, Carlos Américo de Souza; LEITE, Jandecy CabralPython-based software using the K-Nearest Neighbors (KNN) machine learning algorithm to classify failures in PCB manufacturing lines. Designed for Industry 4.0 environments, it aims to improve predictive failure detection accuracy in automated industrial contexts.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 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.