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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42 resultados
Resultados da Pesquisa
Item Unified System for Detecting and Mitigating Evil Twin Attacks on Industrial Wi-Fi Networks with IoT/IIoT(Instituto de Tecnologia e Educação Galileo da Amazônia, 2025) SILVA JÚNIOR, Walter Claudino da; NASCIMENTO, Manoel Henrique ReisWi-Fi network security in industrial environments has become a critical challenge in the era of digital transformation, especially with the widespread adoption of IoT and IIoT devices. The Evil Twin attack, which creates fraudulent access points identical to legitimate ones, poses a serious threat to confidentiality and availability in industrial systems. This study proposes a Unified Detection and Mitigation System (UDMS) that integrates RADIUS-based robust authentication, continuous monitoring using Snort intrusion detection system, and centralized access management via Active Directory. Tested in five progressive scenarios, the system reduced attack success rates from 87% (WPA2-PSK) to just 2%, while maintaining latency below 400ms, with low false positive (6%) and false negative (3%) rates. The research provides a practical framework for securing industrial Wi-Fi networks without compromising operational performance.Item Automation and Intelligent Control in Drying and Curing of Paints and Varnishes: Application of Industry 4.0(Instituto de Tecnologia e Educação Galileo da Amazônia, 2025) SOUZA, Raimundo Alberto Farias de; SANTOS, Eliton Smith dosThis study investigates the technologies, methods and challenges involved in drying and curing paints and varnishes applied to reflective strips, with emphasis on Industry 4.0-based solutions. It proposes an integrated hardware–software model for automatic detection of curing level through light radiation. A controlled-environment prototype and real-time control system aim to optimize the process, accelerate UV photopolymerization and improve product quality.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 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 Automation and Intelligent Control in Drying and Curing of Paints and Varnishes: Application of Industry 4.0(Instituto de Tecnologia e Educação Galileo da Amazônia, 2025) SOUZA, Raimundo Alberto Farias de; SANTOS, Eliton Smith dos; ALENCAR, David Barbosa de; CAMPOS, Paola Souto; MORAES, Nadine Mustafa; Jandecy Cabral LeiteThis research aims to investigate the technologies, methods, and challenges in the drying and curing process of paints and varnishes applied to reflective strips, focusing on implementing Industry 4.0-based solutions. It proposes an integrated hardware and software model to automatically detect the curing level through light radiation, along with a real-time control system to optimize the process. Among the evaluated technologies, ultraviolet light curing (photopolymerization) stands out, aiming to enhance industrial production with quality and efficiency.Item Proposta de um algoritmo de detecção de falhas com lógica fuzzy para otimização de motores elétricos em processos de fundição de alumínio(Instituto de Tecnologia e Educação Galileo da Amazônia, 2024) SILVA, Lenildo Marcos da Mota; BRITO JUNIOR, Jorge de AlmeidaThis study proposes the development of a fault detection system based on fuzzy logic to optimize electric motors in aluminum casting processes. The theme is grounded in the need to enhance efficiency and operational continuity in the casting industry, minimizing unplanned downtime and maintenance costs. The primary objective is to create a fuzzy control model that enables real-time monitoring of critical variables, such as temperature, pressure, and electric current, to facilitate predictive fault detection. Methodologically, operational scenario simulations were conducted to evaluate the model’s performance under adverse conditions, including overload and overheating, with validation through experimental testing. Results indicate that the proposed fuzzy system accurately identifies anomalies and issues preventive alerts, extending motor lifespan and reducing downtime. It is concluded that the model can be integrated with supervisory systems like SCADA, enhancing predictive maintenance and operational efficiency. This technological solution shows promise for the aluminum casting industry and potential applications in other industrial sectors.Item Hardware didático para mapeamento indoor com LiDAR: uma abordagem para a Indústria 4.0(Instituto de Tecnologia e Educação Galileo da Amazônia, 2024) GUABIRABA, Rafael Braga; MARTINELLI FILHO, NelsonThe Manaus Industrial Hub is an innovation center driven by industry, government, and education, requiring accelerated workforce qualification for Industry 4.0. The rapid technological transition demands effective training strategies, reducing dependence on external models. Therefore, the development of accessible educational systems is essential to prepare professionals for this new reality. This dissertation proposes a compact architecture capable of supporting ROS, focusing on indoor environment mapping. This platform is designed for educational purposes, providing an introductory experience in robotics. The selected materials prioritize portability, utilizing a Raspberry Pi 4 Model B and an RPLidar 360° laser sensor. The results demonstrate the system's feasibility for both educational and industrial applications, contributing to the training of skilled professionals for Industry 4.0.Item Optimization of Economic and Environmental Dispatch Using Bio-inspired Computer Metaheuristics(Instituto de Tecnologia e Educação Galileo da Amazônia, 2023) NASCIMENTO, Manoel Henrique Reis; CAMPOS, Paola SoutoThis chapter addresses the optimization of economic and environmental dispatch in electric power systems using bio-inspired computational metaheuristics. Techniques such as Genetic Algorithms, Particle Swarm Optimization, and Ant Colony-Based Algorithms are analyzed. The study demonstrates how these approaches can reduce operational costs and minimize environmental impacts, ensuring energy efficiency and sustainability.Item Desenvolvimento de um Sistema de Monitoramento de Carga em Baterias Fotovoltaicas Utilizando Python(Instituto de Tecnologia e Educação Galileo da Amazônia, 2023) David Barbosa de; LEITE, Jandecy CabralThe article presents a Load Monitoring System for Photovoltaic Batteries developed in Python, aiming to provide users with precise and real-time information about the charge status of the batteries. This system is particularly relevant due to the increasing adoption of photovoltaic solar energy as a renewable energy source, allowing the optimization of photovoltaic systems' performance and contributing to more efficient energy consumption management.Item Avaliação de imunidade eletromagnética radiada do protocolo IOT LORA(Instituto de Tecnologia e Educação Galileo da Amazônia, 2024) RIBEIRO, Jhonatan; SANTOS, Eliton Smith dosIndustrial automation, historically based on wired technologies, has evolved toward wireless solutions, driven by the increasing interconnection of devices and the need to overcome logistical and range limitations. In Industry 4.0, wireless communication plays a central role by integrating sensors, actuators, and control systems into an intelligent production environment. This integration enables real-time data collection and analysis, facilitating automation, optimization, and process flexibility. Despite the benefits, adopting wireless technologies faces significant challenges, particularly electromagnetic interference (EMI), which can compromise the operation of devices and systems. This study presented an analysis of the electromagnetic immunity of the LoRa protocol, using the Heltec V2 board, which incorporates the SX1278 chip, to evaluate its robustness in environments subject to electromagnetic interference. The tests, conducted according to the IEC 61000-4-3 standard, identified critical failure frequencies such as 232.4 MHz, 412 MHz, and 615.2 MHz under different parameter configurations. In these conditions, partial or total communication loss was observed, depending on the intensity of the irradiated field, demonstrating that different configurations can significantly impact the system's immunity. Solutions such as using robust protocols, including LoRaWAN and NB-IoT, spectral spreading techniques, electromagnetic shielding, and filters can mitigate the effects of EMI. Furthermore, future strategies include developing adaptive algorithms to dynamically adjust communication parameters and signal failures, enhancing the resilience and reliability of the LoRa protocol in complex industrial environments. The results of this research contribute to improving wireless communications in Industry 4.0, highlighting LoRa as an essential technology for robust and efficient connectivity.