Departamento de Ensino Superior
URI permanente desta comunidadehttps://ri.ifam.edu.br/handle/4321/956
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8 resultados
Resultados da Pesquisa
Artigo de Periódico Um estudo sobre a aplicação da inteligência artificial na movimentação de materiais a partir de publicações científicas(2025-04-03) Veloso, Jhuly de Souza; Silva, Daniel Nascimento eArtificial intelligence is one of the information and communication technologies that has promoted major transformations in organizations and their production processes, especially material handling. The growing number of published studies led to the development of this study, which aimed to describe the main characteristics of studies that report the application of artificial intelligence in material handling. The method used was the conceptual bibliographic, bibliometric design based on four stages: formulation of research questions, collection of bibliographic data, analysis, organization of the collected data, and generation of answers to the guiding questions. The results showed that the focuses of the applications are a) improvement and optimization of the logistics process, increased rationality of human-machine actions, and optimization of the decision-making process, b) use of several simultaneous methods and techniques, c) facing problematic situations aimed at problem-solving and generation of technologies, d) application of multiple artificial intelligence tools, e) successful results have increased competitiveness and rationality in material handling and f) opening for new and interconnected applications. The conclusion shows that using artificial intelligence has provided an environment for enhancing human cognitive capacity. The main contribution of this study to science is the finding that professional training in logistics needs to incorporate mastery of artificial intelligence.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.Artigo de Periódico Análise de aplicações da inteligência artificial na armazenagem de materiais: um estudo bibliográfico(2025-04-09) Montenegro, Samara da Costa; Veloso, Jhuly de Souza; Silva, Daniel Nascimento eThis study aimed to analyze ten publications that portray the application of artificial intelligence in material storage. The conceptual bibliographic method was used in its four stages: a) formulation of primary and accessory research questions, b) data collection in scientific databases, c) analysis and organization of the collected data, and d) generation and interpretation of the answers to the formulated research questions. The results showed that the goals of the studies focused on problematic situations that can be considered complex, the methods of the studies consisted of numerous techniques and procedures, the artificial intelligence tools applied in the studies were varied and in large quantity, and the results and conclusions of the studies show that artificial intelligence is a technology that can effectively solve problems and help to overcome storage challenges. The conclusion points out that the more complex the problem or challenge to be faced, the greater the effectiveness of artificial intelligence in solving or helping to overcome it. The study's main contribution to science highlights the need for logistics and storage professionals to know and know how to apply artificial intelligence in logistics practice.Trabalho de Conclusão de Curso Uso de redes neurais para identificação de embarcações(2024-09-23) Pedroso, Ytalo Ribeiro da Silva; Santos, Alyson de Jesus dos Santos; http://lattes.cnpq.br/5998752909180697; Santos, Alyson de Jesus dos; http://lattes.cnpq.br/5998752909180697; Souza, Daniel Fonseca de; http://lattes.cnpq.br/4043793492782488; Rodrigues, Marlos André Silva; http://lattes.cnpq.br/0650250324042531Due toitsuniquegeography,theriversoftheAmazonplayasignificant roleinthedailylife of theregion,includingbeingtheonlyaccessinmoreremotecommunities,andthelackof infrastructure inmuchofthiswaterwaynetworkmakesitconducivetothetransportofillegal goods duetothelackofsupervision. When comparedtourbanareas,itispossibletonoticethepotentialforpositiveassistanceto local authoritiesthroughtheuseofrecognitiontechnologies,butthelackofcommunication structures hinderstheimplementationofthesetechnologiesinthesamewayitisdoneincities. This projectproposesthedevelopmentofaneuralnetworkapplicationaimedatassistingin public securityissuesthroughthedetectionofvesselsinportregionslocatedintheStateof Amazonas, combiningArtificial IntelligencetechniquesandEmbeddedSystemsdevices,without the useofnetworkdatatransmission.Themethodologyconsistsof:(a)Acquisitionofvessel images atMarinadoDaviandtheportofManausModerna-StateofAmazonas;(b)Preparation of thedatasetintheexpectedformatforthemodel;(c)Installation,configuration, anduseofthe Jetson NanoBoardintrainingtheNeuralNetwork;(d)UseofTransferLearning,leveraginga pre-trained model(YOLOv4Tiny)formodelgenerationonthenewdataset;(e)Validationofthe obtained results. The resultsshowthatwiththeuseofversionsoptimizedforembeddeddevices,itwaspossible to executetheYOLOv4Tinyalgorithm,performingtheclassification ofvesselsandcontributing with newvesselimages,whichprovidegreaterregionalitytothepresenteddata.Trabalho de Conclusão de Curso Prevenção contra deepfakes: desenvolvimento de um sistema de reconhecimento facial para diferenciar rostos humanos de rostos gerados por IA(2024-03-19) Silva, Romão Charles Silva e; Santos, Alyson de Jesus dos Santos; http://lattes.cnpq.br/5998752909180697; Santos, Alyson de Jesus dos; http://lattes.cnpq.br/5998752909180697; Martins, Gilbert Breves; http://lattes.cnpq.br/4932200790121123; Rodrigues, Marlos André Silva; http://lattes.cnpq.br/0682962508867807This work aims to develop a system based on machine learning that differentiates images of people generated by artificial intelligence from real people, a capability that can be very useful for identifying scams that use generated images. The development of the project was done in 3 main steps: data organization, training and testing. The system was entirely made in Google Colab, therefore, it used Python and the main development tool Tensorflow, two models were trained, one of which has almost twice as many images used for training, with the intention of observing the consequences of using a larger set. At the end of the project, the quantitative and qualitative results of the image classification are shown.Trabalho de Conclusão de Curso Detecção de anomalias médicas no pulmão usando técnicas de inteligência artificial(2023-12-22) Silva, Rafael Reinaldo; Santos, Alyson de Jesus dos; Alyson de Jesus dos Santos; Santos, Alyson de Jesus dos; http://lattes.cnpq.br/5998752909180697; Santos, Lucélia Cunha da Rocha; Fialho, Michaella Socorro Bruce; http://lattes.cnpq.br/9348859124436505; SilvaArtificial Intelligence (AI) is not a contemporary concept, and its presence is not alien to society; currently, numerous applications employ this knowledge. However, despite the growing incorporation of technology in various contexts and increasingly in everyday life, a significant portion of the population still views technological intervention with reservations. In the medical field, it is no different; there is concern about the replacement of healthcare professionals by intelligent machines. Those who think so are mistaken; currently, AI is already involved in various aspects, such as disease prognosis, image understanding, interconnection of prescription databases, among others, and yet there is still a need for human presence. However, such advances do not spread uniformly; there will still be many gaps in the democratization of the application of this resource, whether due to a lack of technology, training, or even distances. In the latter case, it is more common in Brazil, which has continental extensions. According to the World Health Organization (WHO), in the last decade, two of the four leading causes of death in the world are related to respiratory diseases. In Brazil, according to the Ministry of Health, in the first nine months of 2022, there were more than 40,000 deaths from pneumonia alone. This work aims to compare machine learning algorithm models to present the pros and cons of each. Neural networks were used to check a dataset of images for training, validation, and testing of models with the purpose of recognizing and diagnosing cases of pneumonia through only X-ray examinations.Trabalho de Conclusão de Curso Sistema de detecção de capacete baseado em inteligência artificial(2023-03-24) Ramos, Arthur Cabral; Santos, Alyson de Jesus dos; http://lattes.cnpq.br/5998752909180697; Santos, Alyson de Jesus dos; http://lattes.cnpq.br/5998752909180697; Costa, Jaidson Brandão da; http://lattes.cnpq.br/4553321582341998; Compto, Gabriel Pinheiro; http://lattes.cnpq.br/5432787843953143This work aims to develop a system based on machine learning that controls access to areas where the use of helmets as personal protective equipment is mandatory. The project was developed is three main stages: data selection, training and testing. The project used low-cost hardware and free software. The developed system used Python as a programming language in all stages and TensorFlow as the main tool. The operation occurs through a code written in Python that evaluates whether the use of the helmet is being carried out, if the answer is positive, it triggers a device that grants access, in the project the device is represented by an LED.Trabalho de Conclusão de Curso Análise comparativa de algoritmos de reconhecimento facial(2023-02-17) Ricardo, Misael Marques; Santos, Alyson de Jesus dos; http://lattes.cnpq.br/5998752909180697; Santos, Alyson de Jesus dos; http://lattes.cnpq.br/5998752909180697; Costa, Jaidson Brandão da; http://lattes.cnpq.br/4553321582341998; Compto, Gabriel Pinheiro; http://lattes.cnpq.br/5432787843953143THE PURPOSE OF THIS PAPER IS TO CARRY OUT A STUDY ON THE OPERATION OF FACE RECOGNITION ALGORITHMS DESCRIBED IN THE LITERATURE. THREE OF THE FACIAL RECOGNITION ALGORITHMS DESCRIBED IN THE LITERATURE WERE USED AND A TEST SET IS PROPOSED IN ORDER TO EVALUATE THE RESULT AND VERIFY THE POSSIBILITY OF USING THE ALGORITHM IN AN ACCESS CONTROL SYSTEM TO PHYSICAL SPACES. THE EIGENFACES, FISHERFACES AND LBPH ALGORITHMS WERE USED. TO THE TESTS THREE DATABASES WERE USED: THE FIRST WAS CONSTITUTED WITH PHOTOS OF THE AUTHOR AND HIS FAMILY, THE SECOND WAS THE DATABASE OF PEOPLE WITH AND WITHOUT MASKS AND LASTLY THE DATABASE CONSISTED OF PEOPLE WITH AND WITHOUT GLASSES AND THE RESULTS THE ACCURACY OF RECOGNITION WERE REPORTED AND PRESENTED IN THIS PAPER.