Campus Manaus Distrito Industrial
URI permanente desta comunidadehttps://ri.ifam.edu.br/handle/4321/9
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Resultados da Pesquisa
Trabalho de Conclusão de Curso Controle de um sistema de automatização residencial com software bluetooth para comando com uso de plataforma arduino(2025-10-08) Mesquita, Jonathas Campelo de; Sampaio, Ricardo Brandão; http://lattes.cnpq.br/1715941386400515; Ribeiro, Laura Michaella Batista; http://lattes.cnpq.br/8632002394782219; Prazeres, Roberto Alcides de Lima; http://lattes.cnpq.br/8359446655255416This work presents the development of a home automation system based on the Arduino platform, with control performed through a Bluetooth communication application. The main objective is to provide greater practicality, safety and energy efficiency in the domestic environment, using low-cost and easy-to-implement solutions. The system allows the remote activation of electrical devices, such as lamps and fans, through a Smartphone, ensuring accessibility and convenience to the user. The control interface was developed using an Android-compatible application, which communicates with the JDY-16 Bluetooth module coupled to the Arduino UNO. The tests demonstrated the effectiveness of the system in responding quickly to the commands sent, as well as the reliability of the wireless connection over short distances. The results obtained indicate that the integration between hardware and software is viable for home automation applications, contributing to the dissemination of accessible home automation technologies.Trabalho de Conclusão de Curso O impacto da tecnologia 5G na redução da latência e aumento da capacidade em redes de alta demanda(2025-01-10) Ribeiro, Marcus Paulo Serrão; Santos, Alyson de Jesus dos; http://lattes.cnpq.br/5998752909180697; Frota, Vítor Bremgartner da; http://lattes.cnpq.br/6100146230873494; Rodrigues, Marlos André Silva; http://lattes.cnpq.br/0650250324042531The growing demand for data traffic in mobile networks has posed significant performance challenges, especially when users access content hosted on international servers. In this context, 5G technology emerges as an advanced solution capable of increasing efficiency, reducing latency, and optimizing resource utilization. This work aims to analyze how 5G addresses the issue of slow performance in high-traffic situations by leveraging features such as Network Slicing, edge computing, Massive MIMO, and spectrum aggregation. These features enable the creation of dedicated virtual networks, data processing closer to the enduser, and greater bandwidth, even in overload scenarios. The research will be based on simulations and case studies, comparing 5G's performance with previous generations, such as 4G, in terms of latency, capacity, and spectral efficiency. Furthermore, the study will discuss the impacts of this technology in high-density environments and the regulatory challenges associated with spectrum usage. The expected results include a significant improvement in the quality of service, even in high-demand areas, demonstrating the potential of 5G to transform user experience and global telecommunications infrastructure.Trabalho de Conclusão de Curso Métodos para reconhecimento de resíduos recicláveis através de visão computacional(2025-02-10) Silva, Vitor Arlinson Rodrigues da; Pereira, Micila Sumária Medeiros; http://lattes.cnpq.br/7877913821937987; Santos, Alyson de Jesus dos; http://lattes.cnpq.br/5998752909180697; Fialho, Edevaldo Albuquerque; http://lattes.cnpq.br/1681351413618686; Santos, Renan Cavalcante; http://lattes.cnpq.br/6930748017205035This work proposes the study of methods that seek to unite concepts from society 5.0 and industry 4.0 to be used in favor of sustainability. With the increase in the production of plastic waste around the world and its low recycling rate, there was a need to reduce the impact on the ecosystem. The methodology used was applied, explanatory research with a technological design. As a result, three methods were developed for recognizing recyclable waste. Finally, the method selected used a convolutional neural network to create and train a classifier for a machine, powered by plastic and metal lids. The aim of this system is to promote sustainability and reduce the amount of recyclable materials disposed of inappropriately in the environment. Therefore, this work aims to develop low-cost sorters and select the best one to be used in an machine powered by recyclable waste.Trabalho de Conclusão de Curso Sistema de detecção de Tomates (SDT): uma ferramenta de Gestão para agricultores nas fases de maturação(2025-04-02) Fernandes, Paulo Sérgio Lima; Martiniano, Alexandre Lopes; http://lattes.cnpq.br/2232239320901259; Souza, Wendisson da Silva; Palhares Júnior, Eduardo; http://lattes.cnpq.br/6704112028750834This study presents the development and application of a computer vision system for the detection and classification of tomatoes at different ripening stages using the YOLO v8 model. The system was tested in a controlled agricultural environment, where images and videos were analyzed to identify ripe, green, and rotten tomatoes. To facilitate data visualization and interpretation, an interactive statistical dashboard was implemented, enabling real-time monitoring of agricultural production. In addition to fruit detection, the system was integrated with a climate monitoring module, providing information on temperature, humidity, and precipitation to support decision- making processes. The results indicate that the model demonstrated good performance in identifying ripe and rotten tomatoes, but faced challenges in accurately detecting green tomatoes due to lighting variations and the lower representation of this class in the dataset. This research highlights the potential of artificial intelligence in agriculture, fostering greater efficiency, automation, and quality control in food production.Trabalho de Conclusão de Curso Sistema Integrado de detecção de EPIS - SIDE(2025-04-11) Prestes, Emyli Beatriz Braga; Martiniano, Alexandre Lopes; http://lattes.cnpq.br/2232239320901259; Ribeiro, João Bernardo Aranha; http://lattes.cnpq.br/9027441032059817; Velozo, Hugo Alves; http://lattes.cnpq.br/8351107136518878This work presents the development of a computer vision system aimed at the automatic detection of Personal Protective Equipment (PPE) in workplace environments. The proposal seeks to integrate artificial intelligence technology with occupational safety, contributing to accident prevention and compliance with regulatory standards. The system uses the YOLOv8 model, a real-time object detection neural network trained to identify the main PPE items: helmet, safety glasses, face mask, and reflective vest. The dataset annotation and preparation were carried out using the Roboflow platform, which also facilitated the resizing, organization, and diversification of the images. For image capture, a camera connected to a Raspberry Pi was used, sending the data to a graphical interface developed in Python using the Streamlit framework. This interface allows real-time visualization of the detected equipment, making analysis easier for the user. The system was designed to be easy to implement and operate, offering a low-cost solution with potential application in various industrial sectors. Tests showed promising results regarding detection accuracy, even under different lighting conditions. The research highlights the potential of using computer vision and IoT to promote safer and more intelligently monitored workplaces. The combination of accessible hardware, intuitive software, and deep learning models proved effective in building systems that support occupational safety.Trabalho de Conclusão de Curso Uso do drone Tello Edu como ferramenta integrada para o ensino de programação, visão computacional e inteligência computacional(2025-03-13) Alves Júnior, Washington Henrique; Frota, Vítor Bremgartner da; http://lattes.cnpq.br/6100146230873494; Velozo, Hugo Alves; http://lattes.cnpq.br/8351107136518878; Santos, Alyson de Jesus dos; http://lattes.cnpq.br/5998752909180697This study addresses the utilization of the Tello EDU drone as an integrated educational tool for teaching programming, computer vision, and computational intelligence at the Instituto Federal do Amazonas (IFAM), Manaus Distrito Industrial campus. The general aim is to demonstrate the educational potential of the Tello EDU drone, highlighting its contribution to developing computational thinking and facilitating the practical application of related disciplinary content. The adopted methodology comprises a literature review and a critical analysis of data and previous experiments. Initially, the research focused on visual programming through Scratch, revealing significant student engagement and interest due to the ease and interactivity of the activities. Subsequently, the project introduced Python as a textual programming language, enabling students to execute more complex tasks, such as autonomous flights and advanced command sequences using the DJITelloPy library. Additionally, the study explored practical applications using OpenCV and MediaPipe libraries to implement gesture-based control systems. Results from prior experiments confirmed the viability of this integrated approach, providing students with an intuitive and dynamic learning interface, promoting practical and meaningful learning experiences in programming, computer vision, and computational intelligence. In conclusion, the Tello EDU drone proved to be an effective resource for fostering computational thinking and enhancing practical understanding and application in programming, computer vision, and computational intelligence. This approach significantly contributed to interactive and meaningful learning experiences.Trabalho de Conclusão de Curso Desenvolvimento de dispositivo para telemetria e monitoramento remoto de florestas(2025-04-07) Silva, Rodrigo Pereira; Fialho, Edevaldo Albuquerque; http://lattes.cnpq.br/1681351413618686; Almeida, Fernando Rodrigues de; http://lattes.cnpq.br/5709421178806994; Santos, Renan Cavalcante; http://lattes.cnpq.br/6930748017205035; Oliveira, Ricardo Augusto Medeiros de; http://lattes.cnpq.br/3009905071972756The advancement of Internet of Things (IoT) technologies enables new approaches to environmental monitoring, especially in remote and hard-to-reach areas such as the Amazon Rainforest. The need to track environmental changes, prevent deforestation and forest fires, and facilitate scientific research drives the development of autonomous technological solutions for data collection and transmission. In this context, this work proposes the development of an IoT-based telemetry system for remote forest monitoring, utilizing LoRa technology for communication within a mesh network. The system consists of two main devices: the Monitoring Node, responsible for measuring environmental parameters such as temperature, humidity, atmospheric pressure, and volatile organic compounds; and the Communication Bridge, which transmits the data to a monitoring center via the MQTT protocol. Laboratory and field tests demonstrated the system’s efficiency in data transmission. The results indicate that the proposed approach is viable for environmental monitoring applications and can be further improved with optimizations in energy consumption and the physical structure of the devices.Trabalho de Conclusão de Curso Rede LoRa: análise de desempenho de uma rede de Internet das Coisas em um cenário florestal(2025-04-11) Moraes, Nara Tavares Fernandes; Santos, Alyson de Jesus dos; http://lattes.cnpq.br/5998752909180697; Lacerda, José Cavalcante; http://lattes.cnpq.br/4731128445071858; Rodrigues, Marlos André Silva; http://lattes.cnpq.br/0650250324042531This paper analyzes the performance of LoRa (Long Range) technology in Internet of Things (IoT) networks applied to forest environments, focusing on the Amazon region. The research seeks to understand the impacts of environmental variables, such as temperature, humidity, and vegetation density, on data transmission between IoT devices. To this end, field experiments were conducted, evaluating metrics such as signal range, packet loss rate, and device energy consumption. The results indicate that weather conditions directly influence the efficiency of LoRa communication, affecting network stability and sensor lifespan. Temperature variations, for example, can compromise the performance of electronic components and reduce battery capacity. In addition, natural obstacles, such as large trees, interfere with signal propagation, requiring adjustments to the network configuration to improve its reliability and range. Given these challenges, the research highlights the importance of developing adaptive strategies to optimize connectivity in remote areas. The implementation of efficient IoT networks in forest scenarios can significantly contribute to environmental monitoring, aiding in the conservation of biodiversity and the sustainable management of natural resources. The findings of this study are expected to serve as a basis for future research and improvements in the application of LoRa technology in challenging environments.Trabalho de Conclusão de Curso Análise da implantação da rede de telefonia móvel celular 5G na Cidade de Manaus-AM: estudo de caso /(2025-04-29) Oliveira, Rômolo de Sá; Fontinelle, Carlos Gomes; http://lattes.cnpq.br/8988006492142629; Santos, Alyson de Jesus dos; http://lattes.cnpq.br/5998752909180697; Martiniano, Alexandre Lopes; http://lattes.cnpq.br/2232239320901259The evolution of telecommunications technologies has brought significant transformations to contemporary society, particularly with the advent of fifth-generation mobile networks, known as 5G. This technology promises higher connection speeds, lower latency, and the ability to connect a significantly larger number of devices simultaneously, enabling advancements in solutions such as the Internet of Things (IoT), smart cities, industrial automation, and real-time connectivity. However, the deployment of 5G in regions with specific geographic and socioeconomic characteristics, such as the city of Manaus-AM, presents technical, logistical, and social challenges that warrant scientific investigation. This study aims to analyze the main factors influencing the implementation of the 5G mobile network in Manaus, considering its current technological infrastructure, the logistical obstacles posed by the Amazon region, the socioeconomic impact of the technology, and the prospects for the development of Industry 4.0 within the Manaus Industrial Hub (PIM). The research adopts a case study methodology with a qualitative and quantitative approach, based on bibliographic review, document analysis, and secondary data collection from sources such as ANATEL, IBGE, ITU, and telecommunications operator reports. The results indicate that, despite recent progress in terms of coverage and spectrum availability, there are still limitations related to fiber optic infrastructure, antenna density, and unequal access in peripheral and riverside areas. Furthermore, the integration of 5G into the local industrial sector still requires substantial investments in modernization and technical training. The study concludes that achieving the full benefits of 5G in Manaus requires coordinated efforts between public policies, operator strategies, and digital inclusion initiatives. This research contributes to the understanding of regional challenges in the deployment of 5G in Brazil and provides insights for more equitable and sustainable technological development strategies.Trabalho de Conclusão de Curso Desenvolvimento de um controlador para pêndulo invertido baseado no regulador linear quadrático(2025-04-22) Marques, Noé Beltrão da Silva; Nascimento, José Fábio de Lima; http://lattes.cnpq.br/0056522906128231; Queiroga, Sandro Lino Moreira de; http://lattes.cnpq.br/1031366446350466; Santos, Renan Cavalcante; http://lattes.cnpq.br/6930748017205035The main objective of this study was to design a Linear Quadratic Regulator (LQR) controller to stabilize an inverted pendulum in its vertical position, minimizing the position error and control energy consumption, while ensuring system stability. The specific objectives included defining the DC motor parameters, verifying the system stability, defining the optimal gain matrix K, determining the rank and controllability matrix, as well as simulations under different initial conditions. The methodology involved obtaining the parameters of a DC motor through experimental tests, such as measurements of armature resistance, current, angular velocity and moment of inertia. The system was modeled in state space based on the Euler-Lagrange equations, followed by linearization via Taylor series expansion and Jacobian matrix. The resulting linear model was implemented in the MATLAB/Simulink environment, where the LQR controller was developed and simulated. The results demonstrated that the originally unstable system presented full controllability (rank of the controllability matrix equal to 4) and was successfully stabilized. The cost function associated with the control was minimized using the Riccati equation, ensuring a balance between performance and control effort. The simulations proved the robustness of the controller against parametric variations and external disturbances, validating the effectiveness of the proposed approach.