TCC Sistemas de Informação
URI Permanente para esta coleção
Navegar
Submissões Recentes
Item Letramundo: um jogo sério para alfabetização de crianças com Transtorno do Espectro Autista (TEA) em ambiente escolar(Instituto Federal de Educação Ciência e Tecnologia de Alagoas, 2025-07-03) Silva, Arthur Henrique Souza da; Cunha, Mônica Ximenes Carneiro da; http://lattes.cnpq.br/1775024859845111; Kamei, Fernando Kenji; http://lattes.cnpq.br/5033020411757389; Calado, Ivo Augusto Andrade Rocha; http://lattes.cnpq.br/5748220882915553This work presents the development, implementation, and testing of a Serious Games (SG) web application for literacy aimed at children with Autism Spectrum Disorder (ASD) to assist special education and promote social inclusion in the educational environment. The innovative aspects of this study lie in the use of hyperfocus as a strategic tool to enhance student learning and engagement, the use of TEACCH principles, and the use of the phonics method as a literacy model. The tool combines playful elements, specific educational goals, and reading teaching methods based on the latest studies on verbal language, especially in the areas of psycholinguistics and neuroscience. The prototype of this application was tested by special education professionals, and the test results indicated the need for a redistribution of levels and content. The modifications were made during the implementation phase, and the platform was tested with special education professionals from the early years of elementary school and with children with ASD aged 6 to 12, in the first grades of elementary school. The results showed high student interest in the platform, as well as strong adherence to the most current teaching methods for children with ASD.Item Análise da evasão e permanência em cursos superiores de Tecnologia de Informação no Brasil(Instituto Federal de Educação Ciência e Tecnologia de Alagoas, 2026-06-26) Nunes, Iris Mayara Vieira; Moraes Júnior, Edison Camilo de; http://lattes.cnpq.br/8234380347792761; Cruz, Jailton Cardoso da; http://lattes.cnpq.br/9366016044068759; Ferro, Márcio Robério da Costa; http://lattes.cnpq.br/2480382178623363This study analyzes patterns of dropout and persistence in Information Technology undergraduate programs in Brazilian higher education between 2014 and 2024, considering temporal, regional, and sociodemographic perspectives. The research is characterized as quantitative, applied, and descriptive, with a longitudinal approach based on official secondary data from the Higher Education Census provided by the National Institute for Educational Studies and Research Anísio Teixeira (Inep). The analysis was conducted through the organization and exploration of data using Business Intelligence techniques and dimensional modeling, including the development of an analytical dashboard that enabled the visualization and interpretation of indicators related to enrollment, dropout, and program completion. The results reveal a critical scenario, with a dropout rate exceeding 60% at the national level, indicating that the expansion of enrollments in Information Technology programs has not been accompanied by a proportional increase in the effective training of professionals in this field. As a contribution, this study highlights the potential of open educational data combined with analytical tools to support the understanding of educational phenomena and to assist evidence-based decision-making in higher education.Item Fundamentação do Programa Triple-N com o método do estudo e da escrita imanente à vida(2026-06-10) Silva Neto, Natalício Nunes da; Bezerra, Ciro de Oliveira; http://lattes.cnpq.br/8755460275894251; Medeiros, Leonardo Melo de; http://lattes.cnpq.br/1080593968001453; Pinto, Charridy Max Fontes; http://lattes.cnpq.br/4139562888411167; Cruz , Jailton Cardoso da; http://lattes.cnpq.br/9366016044068759Our research focuses on the study of Parkinson’s Disease (PD). But what is Parkinson’s Disease? It is a progressive neurological disorder that develops gradually and compromises the sensorimotor system. For example, it causes symptoms such as tremors, slowness of movement (bradykinesia), and postural imbalance. PD affects millions of people worldwide, across all age groups; however, the elderly population is the most affected. Data from the World Health Organization (WHO) show that approximately 1% of the global population over the age of 65 has the disease. The main reason is the progressive loss of dopamine, which, in confirmed cases of PD, is found to be far below normal levels. Interestingly, studies have shown that reading and writing stimulate the production of neurotransmitters that increase dopamine. Thus, among the various possibilities for preventing the disease, we highlight that studying and writing, when practiced regularly as a personal and social habit, may mitigate the effects of Parkinson’s Disease. Diagnosing PD with precision is challenging, especially in its early stages. Among the existing techniques, micrography is commonly employed. This method essentially consists of handwriting examinations. It is precisely in the refinement of such techniques that Machine Learning (ML) emerges as a powerful category within computer science, improving data classification methods that identify patterns and assist in PD detection. Our research employs three ML models: HOG (Histogram of Oriented Gradients) + Support Vector Machine (SVM), Convolutional Neural Networks (CNN), and Transfer Learning (MobileNetV2), with the aim of classifying handwriting samples and contributing to greater accuracy and efficiency in medical diagnosis of PD. The results of our study highlight the use of a supervised ML program (developed by us and named Triple-N, after the author), which achieved promising performance. Specifically, it reached accuracy rates of 80% for HOG + SVM, 96% for CNN, and 98% for Transfer Learning, when combined with Data Augmentation techniques. These findings suggest that the application of Machine Learning, particularly with Data Augmentation, in the classification of handwriting examinations, can be a valuable tool in PD diagnosis. Two key advantages stand out: [1] low cost and [2] rapid delivery of results, enabling the majority of patients to access diagnosis from the early stages of the disease.Item Predição de crimes violentos contra o patrimônio em Maceió e Arapiraca usando o ConvLSTM(2026-05-02) Ferreira, Leonardo Victor Fernandes; Medeiros, Leonardo Melo de; http://lattes.cnpq.br/1080593968001453; Cruz, Jailton Cardoso da; http://lattes.cnpq.br/9366016044068759; Costa, Breno Jacinto Duarte da; http://lattes.cnpq.br/7418697922506495Spatiotemporal forecasting of violent property crimes is a relevant problem for the planning of preventive actions and for the allocation of public security resources. This work presents a methodological replication, in the context of the cities of Maceió and Arapiraca, of the fine-grained crime forecasting pipeline proposed by Albors Zumel, Tizzoni, and Campedelli (2025), based on a ConvLSTM architecture. From georeferenced records of violent property crimes provided by the Military Police of Alagoas, covering the period from 2012 to 2022, the work organizes the data into regular grids with cells of approximately 0.2 km2, aggregates occurrences in 12-hour windows, binarizes the cell-level signal, and trains a ConvLSTM with explicit imbalance treatment via weighted BCEWithLogitsLoss. Evaluation is performed by sweeping the classification threshold, reporting precision, recall, and F1 both in the traditional variant (cell-by-cell) and with spatial tolerance (Chebyshev neighborhood ≤ 1). The results show that, in both cities, the model achieves performance in the spatial variant significantly higher than in the traditional variant (spatial F1 of approximately 0.24 in Maceió and 0.21 in Arapiraca, against values below 0.05 in the traditional variant), evidencing that the network learns to correctly locate risk neighborhoods even when missing the exact cell. The work also discusses the main limitations of the approach, particularly the extreme sparsity of the data, and proposes directions for future developments, including the incorporation of sociodemographic and human mobility channels and comparison against baseline models.Item Estudo do uso de plataformas digitais em eventos acadêmicos(2025-07-08) Cavalcante, Arthur Henrique Quixabeira; Cruz, Jailton Cardoso da; https://lattes.cnpq.br/9366016044068759; Moraes Junior, Edison Camilo de; http://lattes.cnpq.br/8234380347792761; Medeiros, Leonardo Melo de; https://lattes.cnpq.br/1080593968001453Technological evolution requires academic events to adapt to new trends and tools, where digital platforms have the potential to increase the efficiency, visibility, and experience of academic events, making them more engaging and productive for participants. This research used a 16-question questionnaire with qualitative and quantitative methodology to collect responses from 44 participants, including students, faculty, and professionals from various fields, over a two-week period in May 2025. The objective was to understand the participants' profile, their experience with event platforms, their perceptions of technology in events, and their opinions on what could be improved and what they liked about events that used such platforms. The data were analyzed for discussion. The results revealed that most participants were adults aged 30-59, with a stronger presence of women, and that they have a moderate participation rate in academic events. Furthermore, most participants have already used digital platforms for events, especially Doity and Sympla, and value their ease of use, especially for online registration and certificate issuance. Technology in academic events offers benefits such as practicality, agility, and ease of communication, making them more accessible and efficient. Finally, the study found that most participants would recommend the use of digital platforms for events, demonstrating broad approval and confidence in their effectiveness. However, it suggests improvements such as increasing interaction among participants and making the interface user-friendly and interactive.Item Desenvolvimento de um dispositivo vestível de assistência à locomoção utilizando visão computacional e internet das coisas(INSTITUTO FEDERAL DE ALAGOAS - Ifal, 2026-02-27) Pereira, Guilherme Barbosa; Silva, Cledja Karina Rolim da; http://lattes.cnpq.br/1770216488772332; Silva, Cledja Karina Rolim da; http://lattes.cnpq.br/1770216488772332; Souza, Tarsis Marinho de; http://lattes.cnpq.br/9808563385937929; Tenório, Fernando Antonio Guimarães; http://lattes.cnpq.br/0678507623542382Autonomous urban mobility is an essential aspect of the quality of life for visually impaired individuals, who often face physical and architectural barriers aggravated by the lack of accessibility in cities. Traditional tools, such as the white cane, although fundamental, have limitations in detecting aerial obstacles and in the semantic identification of the environment. Given this scenario, this work proposes the development of a wearable visual assistance system based on the Internet of Things (IoT) and Artificial Intelligence. The solution applies Computer Vision technology as a way to understand the environment. The Image capture and distance measurement are performed by an ESP32-CAM module, while heavy processing and inference occur on an external server. The main innovation lies in the feedback delivery: the server processes the image and sends the synthesized audio alert (Text-to-Speech) in real-time via the WebSocket protocol to an Android mobile application, which instantly reproduces the message through the user's headphones. To validate the proposal, tests were performed that could identify objects and report their distance with low latency. The results demonstrate that the integration between IoT, cloud processing, and mobile devices contributes significantly to increasing safety, contextual perception, and locomotion independence for the visually impaired.Item Aplicação de modelagem computacional e inteligência artificial na classificação do risco de surtos de doenças infecciosas na cidade de Maceió, Alagoas(INSTITUTO FEDERAL DE ALAGOAS - Ifal, 2026-02-20) Oliveira, Samila Raphaela de; Silva, Cledja Karina Rolim da; http://lattes.cnpq.br/1770216488772332; Souza, Társis Marinho de; http://lattes.cnpq.br/9808563385937929; Souza, Társis Marinho de; http://lattes.cnpq.br/9808563385937929; Silva, Cledja Karina Rolim da; http://lattes.cnpq.br/1770216488772332; Santos, Edvonaldo Horácio dos; http://lattes.cnpq.br/8960641809330500; Silva, Leonardo Soares e; http://lattes.cnpq.br/4856480961305199Infectious diseases have historically represented a significant threat to populations worldwide and remain a relevant and priority challenge for public health, reinforcing the need for innovative strategies focused on prevention, surveillance, and control. In Brazil, despite the existence of national epidemiological surveillance systems, the occurrence of outbreaks and the reemergence of infectious diseases reveal limitations and vulnerabilities in the capacity to anticipate and respond to epidemic events. In this context, the early identification of risk patterns is essential to support timely public health actions. Within this scenario, models based on artificial intelligence have gained prominence due to their ability to identify complex patterns and support public health planning. These approaches have demonstrated performance comparable to or superior to traditional statistical methods, becoming essential tools for epidemic monitoring and control. Therefore, this study aims to analyze and compare computational models and machine learning algorithms applied to the classification of the risk of infectious disease outbreaks, using data from the Notifiable Diseases Information System (SINAN). The study seeks to contribute to the advancement of computational modeling in public health and to the strengthening of evidence-based strategies in epidemiological surveillance.Item Panorama da utilização de chatbots de WhastApp voltados para a área da educação: uma revisão sistemática de literatura(2025-11-02) Pereira, Bruno Artur Torres Lopes; Soares, Elvys Alves; http://lattes.cnpq.br/6415531537733982; Costa, Breno Jacinto Duarte da; http://lattes.cnpq.br/7418697922506495; Kamei, Fernando Kenji; http://lattes.cnpq.br/5033020411757389The preparation period for crucial higher education entrance exams, such as the National High School Exam (ENEM), represents a significant challenge in the students' educational journey, while WhatsApp, widely used in the country, stands out as a popular tool for communication, including with bots. As an alternative for ENEM preparation, many students have turned to WhatsApp as an educational platform. The aim of this research is to understand how the literature reports the use of chatbots on WhatsApp for education through a Systematic Literature Review (SLR). Initially, 552 studies were identified, of which only 8 were considered relevant after applying inclusion and exclusion criteria. The results reveal that, despite few initiatives, there is promising potential in integrating chatbots on WhatsApp for educational purposes. The SLR suggests that this technology can be a valuable tool in democratizing access to quality education, especially for high school students.Item Uma proposta de solução para gestão de TCCs no IFAL: um mecanismo antifraude baseado em blockchain(INSTITUTO FEDERAL DE ALAGOAS - Ifal, 2026-02-06) Barboza Neto, Eduardo Carlos; Barbosa, Anderson Felinto; http://lattes.cnpq.br/5590648222014479; Souza; Barbosa, Anderson Felinto; http://lattes.cnpq.br/5590648222014479; Souza, Tarsis Marinho de; http://lattes.cnpq.br/9808563385937929; Silva, Cledja Karina Rolim da; http://lattes.cnpq.br/1770216488772332Information security is an essential aspect for the reliability of systems that handle data, with integrity, authenticity, and availability of information as its pillars. In the context of educational institutions, these principles become even more relevant, since academic documents have institutional, academic, and legal value. The absence of standardized mechanisms for managing and verifying these documents can make them vulnerable to loss, alteration, and fraud. Given this scenario, this work proposes the development of a system for managing the thesis defense process for the Federal Institute of Alagoas (IFAL), using blockchain technology as an anti-fraud mechanism, based on permissioned blockchain with Hyperledger Fabric, integrated with a distributed storage system (IPFS), in which academic documents are securely stored, while only their identifiers and integrity proofs are recorded on the blockchain. The system includes functionalities such as scheduling defenses, document submission and versioning, approval workflow between students, advisors, and coordinators, as well as document authenticity verification. To validate the proposal, a functional prototype was developed with a web interface and API integrated into the blockchain network, allowing for the simulation of its application in an academic context. The results obtained demonstrate that the solution contributes to increasing the reliability, traceability, and transparency of academic records.Item Análise de movimentos motores finos dos dedos utilizando visão computacional: um estudo de caso do Finger Tapping Test (FTT) na doença de Parkinson(2025-11-26) Campos, Herbert Douglas Silva da Silva; Nascimento, Arlyson Alves do; http://lattes.cnpq.br/9395417554768580; Medeiros, Leonardo Melo de; http://lattes.cnpq.br/1080593968001453; Passos, Frederico Salgueiro; Calado, Ivo Augusto; http://lattes.cnpq.br/5748220882915553Parkinson’s disease (PD) is characterized as a neurodegenerative and progressive disorder that affects a significant portion of the elderly population worldwide. The most common symptoms in PD include cognitive problems, which predominantly begin to appear in more advanced stages, unlike the motor symptoms that manifest at the onset of the disease. The Movement Disorder Society Unified Parkinson’s Disease Rating Scale (MDS-UPDRS) is one of the assessments that aid in diagnosing and monitoring the levels of Parkinson’s disease in patients. Within the MDS-UPDRS III, which assesses the motor aspects of patients, there is the Finger Tapping Test (FTT), used to assess bradykinesia and rigidity of movement. FTT is typically administered by a healthcare professional who observes the patient performing the test. However, the use of computer vision can provide a more effective alternative by accurately capturing the movement’s characteristics. The aim of this study was to develop a computer vision system capable of acquiring data from fine finger movements during the FTT and subsequently classify Parkinson’s disease levels according to the MDS-UPDRS. For this study, a computer vision algorithm was created to record data resulting from the abduction and adduction of hand movements during the FTT, calculating the amplitude generated by these movements. A dataset comprising 532 videos of both Parkinson’s and non-Parkinson’s patients, classified into four levels according to the MDS-UPDRS, was used. Subsequently, biomechanical signal processing procedures were conducted. The results obtained indicate that the use of computer vision in assisting healthcare professionals is promising. Data collection from movements allows for the creation of a database that can be used in machine learning models to predict the patient’s disease level based on the MDS-UPDRS. Additionally, a binary classifier was developed to determine the level at which each patient falls, using a Support Vector Machine (SVM) along with the leave-one-out cross-validation technique. This resulted in an accuracy of 73.3% when using the entire available dataset and 76.6% when using only the right-hand FTT.Item Vaso inteligente para o cultivo gamificado de hortaliças e outras variedades de plantas por hidroponia adaptada para ambientes domésticos(2025-11-19) D'Amato, Mikhael de Oliveira Silva; Vieira, Davi Carnauba de Lima; https://orcid.org/0000-0001-7447-4821; http://lattes.cnpq.br/5682382901541282; Kamei, Fernando Kenji; https://orcid.org/0000-0002-5572-2049; http://lattes.cnpq.br/5033020411757389; Medeiros, Flávio Mota; http://lattes.cnpq.br/1874496667181567; Pereira, Francisco Rafael da Silva; ttp://lattes.cnpq.br/0031636331455112The present work introduces the development of a smart pot designed for hydroponic cultivation in domestic environments, integrated with a gamified mobile application that aims to make plant care more accessible, interactive, and educational. The system, named GreenGrow, was structured around two main fronts: (i) the development of the physical prototype of the pot, designed with modular components; and (ii) the creation of an interactive gamified mobile application. Its key features include: real-time monitoring of the pot’s sensors (such as water level, nutrients, humidity, temperature, and solution conductivity), actuator alerts for resource activation (such as fan, irrigation, lighting, nutrient dosing, and solution drainage), and a reward system (gamification) linked to the plant’s health, represented by an animated virtual character. The project also proposes an analysis of existing market solutions, highlighting the distinguishing aspects of this proposal compared to those alternatives. Furthermore, the project includes official software registration with the INPI.Item QR Code como ferramenta de apoio para pessoas com transtorno do espectro autista (TEA): uma análise de viabilidade(2025-11-27) Ferreira, Eyder Tinoco; Kamei, Fernando Kenji; http://lattes.cnpq.br/5033020411757389; Cunha, Mônica Ximenes Carneiro da; http://lattes.cnpq.br/1775024859845111; Bezerra, Tárcio Rodrigues; http://lattes.cnpq.br/5285201763618981; Santos, Eduardo Breno Farias dos; http://lattes.cnpq.br/3318799697977357This study investigates the feasibility of using QR Codes as a complementary tool for the identification and communication of individuals with Autism Spectrum Disorder (ASD). The research stems from the observation that traditional methods, such as the puzzle-piece lanyard and the Autism Spectrum Disorder Identification Card (CIPTEA), while important, present limitations regarding practicality, information updating, and the protection of sensitive data. To assess the potential of QR Codes in this context, a systematic literature review was conducted using the Google Scholar, SpringerLink, and IEEE Xplore databases, resulting in the selection of fourteen studies published between 2019 and 2024. The findings highlighted recurrent benefits such as ease of information access, low implementation cost, real-time verification, and authenticity assurance, along with privacy risk mitigation strategies based on blockchain, digital authentication, and encryption. Subsequently, a questionnaire was applied to fifty-one participants, including individuals with ASD and their guardians, revealing that 82.3% of CIPTEA users consider the document useful for accessing rights but express interest in more dynamic and customizable digital solutions. Based on these results, the GizmoCode web system was developed—a functional prototype built with Java and Angular, designed to generate personalized QR Codes containing contact and support information, implemented in a non-governmental organization (NGO) in Maceió, Brazil. The results indicate that QR Codes represent a viable, secure, and promising alternative to complement the identification of individuals with ASD, contributing to social inclusion, accessibility, and autonomy. However, further studies are recommended to perform heuristic evaluations and assess large-scale adoption in real environments.Item Business intelligence aplicado à análise dos empregos em TI no Brasil (2015 2024)(2025-09-30) Sena, Saulo Roberto de; Moraes Júnior, Edison Camilo de; http://lattes.cnpq.br/8234380347792761; Cruz, Jailton Cardoso da; http://lattes.cnpq.br/9366016044068759; Medeiros, Flávio Mota; http://lattes.cnpq.br/1874496667181567Technology is advancing rapidly, driving profound changes in society. To support these transformations, technology professionals stand out. This study examines the IT job market in Brazil from 2015 to 2024 by creating four dashboards on the distribution of IT jobs by region, states, and municipalities, the profile of employees by gender and age group, and analyzing the allocation of jobs by IT positions and salaries in Brazil. For this, a BI creation methodology was used, leveraging open data from the Ministry of Labor and Employment (MTE).The study addresses the following research questions: Question 1 – Which regions of the country concentrate formal employment, and how is this distribution structured? Question 2 – How is the distribution of formal employment by gender? Question 3 – Which IT professions have grown the most in recent years in Brazil, and what is the profile of the workers in these positions, considering aspects such as salary, average tenure, and job turnover?Item Um guia de boas práticas para criação de uma base de dados pública para auxiliar no desenvolvimento de softwares voltados ao tratamento de transtorno de pânico usando swartwatches(2025-06-26) Duarte, Clísthenes Freire da Cruz; Cunha, Mônica Ximenes Carneiro da; http://lattes.cnpq.br/1775024859845111; Nunes Filho; Nunes Filho, Ricardo Rubens Gomes; http://lattes.cnpq.br/1760182180822152; Cruz, Jailton Cardoso da; http://lattes.cnpq.br/9366016044068759This study sought to create a Good Practices Guide for creating a public and reliable database to assist in the development of applications aimed at detecting and/or treating Panic Disorder (PD), using as a tool the most commonly used wearable device today: the smartwatch. The methodological procedure used in this research consisted of four stages: 1) Systematic Literature Review (SLR) with the aim of verifying the state of the art on the topic in order to understand the situations that hinder the development of applications focused on PD; 2) a documentary research to verify the legal and ethical implications related to the collection and storage of data from PD patients; 3) an exploratory research that consisted of interviews with three psychologists and three psychiatrists in order to identify the legal, ethical and methodological criteria for the condition of collecting biometric data from PD patients; 4) the elaboration of a good practices guide that considers the aspects listed in the previous steps. SLR revealed that applications aimed at predicting and detecting PD have already been developed in hospital research environments, using known Artificial Intelligence algorithms such as Random Forest, Decision Tree, Linear Discriminant Analysis, Adaptive Boosting (AdaBoost), Regularized Greedy Forest, among others, and manipulating variables such as variation in pressure, heart rate, hand movements, speech frequency, electrodermal activity, among others, obtained through measurements carried out on PD patients. The sensors used to measure these variables in question have versions available in most modern smartwatch models. The documentary research stage revealed, through the analysis of the LGPD, that there are legal implications regarding data manipulation. It was also detected, through the analysis of the Professional Code of Ethics for Psychology, that there are ethical implications to be followed when conducting the data collection. The interview stage validated the correlation of the variables indicated in the RSL stage with the TP and added that variables obtained in standard questionnaires, such as related diseases, use of medications, patient impressions, among others, are important for data collection, especially if the patients evaluated have other associated diseases. It was also defined that the ideal profile of a participant in data collection is a person with TP who is not easily influenced and does not have other types of psychological disorders. Finally, from the data collected, an artifact was generated, called a Good Practices Guide, with eight recommended steps for carrying out efficient data collection to be made available to developers. The conclusion highlights the advantages of following the guide produced for standardizing data collection and leaves as future work the activities of preparing the Consent Form and the Cooperation Form, in partnership with legal professionals, and also the preparation of a standard questionnaire with nonbiometric variables that also make up the final database.Item Rotina divertida com Hugo e Sofia: um aplicativo para auxiliar no ensino de atividades de vida diária a pessoas com transtorno do espectro autista(2025-07-08) Ramalho, Jonata Santos; Cunha, Mônica Ximenes Carneiro da; http://lattes.cnpq.br/1775024859845111; Cunha, Mônica Ximenes Carneiro da; http://lattes.cnpq.br/1775024859845111; Araujo, Fabrisia Ferreira de; http://lattes.cnpq.br/9852315723070987; Nunes Filho, Ricardo Rubens Gomes; http://lattes.cnpq.br/1760182180822152This work presents the development of the mobile application Fun Routine with Hugo and Sofia, a mobile solution designed to support the development of skills related to Activities of Daily Living (ADLs) in children and adolescents with Autism Spectrum Disorder (ASD). To ensure the application met user needs, a participatory approach was adopted: over a period of four months, weekly visits were made to AMA-AL, allowing for observation of the participants’ daily routines and dialogue with the institution’s therapists. Based on these interactions, system requirements were defined, and low- and high-fidelity prototypes were developed and validated in collaboration with professionals to ensure accessibility, usability, and alignment with therapeutic practices. The application uses 2D animations featuring the characters Hugo and Sofia to teach the performance of everyday tasks through modeling techniques, promoting more dynamic, accessible, and engaging learning. The app was developed using Expo for the frontend and Laravel for the backend, and it will be used by therapists at the Association of Parents and Friends of Individuals with Autism (AMA) as a complementary resource during therapy sessions.Item Eficiência do processo de folha de pagamento sob a perspectiva da transformação digital: um estudo de caso em uma secretaria de estado(2025-07-08) Oliveira, Mário Andretti da Silva; Cunha, Mônica Ximenes Carneiro da; http://lattes.cnpq.br/1775024859845111; Bezerra, Tarcio Rodrigues; http://lattes.cnpq.br/5285201763618981; Araújo, Fabrísia Ferreira de; http://lattes.cnpq.br/9852315723070987Digital transformation has become a fundamental strategy to modernize public administration, especially in sectors that require a high degree of control and reliability. Payroll management, due to its legal, financial, and operational dimensions, is a critical process where errors and inefficiencies can have significant impacts. In this context, the digitalization and automation of procedures represent opportunities for public institutions seeking greater efficiency and transparency in personnel management. This study aims to analyze the efficiency of the payroll process in a state department through the lens of digital transformation, identifying impacts, challenges, and opportunities for optimization. The methodology was based on a qualitative case study, conducted through semi-structured interviews, employing the storytelling technique, with public servants directly involved in payroll processing. Data collection was complemented by document analysis and direct observation, enabling a comprehensive understanding of both technical and organizational aspects. Content analysis followed Bardin’s method, allowing systematic categorization and interpretation of qualitative data. The MAXQDA Analytics Pro software supported data organization, coding, and analysis, contributing to the traceability and analytical rigor of the research. The results indicate that the adoption of technological tools, such as integrated management systems, database queries, and specific automations, has improved information control and reduced inconsistencies. However, some manual steps still remain, highlighting the need to redesign workflows and expand the use of technology to ensure greater reliability and time savings. It is concluded that digital transformation represents a strategic path for modernizing the public sector, especially in the payroll context. The case analyzed demonstrates that, despite the progress achieved, there is room for significant improvement, provided that efforts are aligned with data-driven management, continuous staff training, and structural investments in information technology.Item Especificação técnica de ferramenta que auxilia na análise dos acidentes de trânsito nas rodovias federais brasileiras por meio de ETL(2024-04-22) Gomes Filho, José Carlos; Moraes Júnior, Edison Camilo de; http://lattes.cnpq.br/8234380347792761; Cruz, Jailton Cardoso da; http://lattes.cnpq.br/9366016044068759; Medeiros, Flavio Mota; http://lattes.cnpq.br/1874496667181567This work presents a technical approach to address the issue of traffic accidents in Brazil, proposing the development of a command-line interface (CLI) in Python for the extraction, transformation, and loading (ETL) of data from federal highway accidents. Business Intelligence (BI) architecture is employed, with emphasis on the star schema in data modeling. The CLI allows for customized execution of the ETL process, including selection of data sets and temporal dimensions. Processed data can be used to feed an interactive Dashboard, built with PowerBI, offering detailed data visualizations and filters by road type and weather conditions. The article aims to provide a robust technical solution for the analysis and prevention of traffic accidents, with the potential to support more effective public policies in this field.Item Estratégias e ferramentas para data analytics no marketing digital: uma revisão sistemática da literatura(2025-06-27) Silva, Emerson Lino da; Cunha, Mônica Ximenes Carneiro da; http://lattes.cnpq.br/1775024859845111; Araújo, Fabrisia Ferreira de; http://lattes.cnpq.br/9852315723070987; Gomes, Anderson Rodrigues; http://lattes.cnpq.br/2811716093058287The growing volume of data generated by user interactions, advertising platforms, and transactional systems reinforces the need for the effective use of data analytics to extract insights and support strategic decision-making in digital marketing. This article presents a systematic literature review (SLR) conducted based on PRISMA guidelines, aiming to investigate the main strategies and tools used for data integration, centralization, organization, and analysis in this context. A search in the IEEE Xplore and Google Scholar databases resulted in the identification of 90 articles. After applying inclusion and exclusion criteria, 4 articles were selected for analysis. The results highlight tools and strategies related to ETL, data storage, and reporting, as well as industry best practices and emerging developments. It is concluded that the use of data analytics tools and strategies contributes to increased productivity and accuracy of information, positively impacting insight generation and the decision-making process in the context of digital marketing.Item Prospecção e detecção de smells em casos de teste escritos no padrão BDD com a linguagem Gherkin(2025) Santos, Felipe da Silva; Soares, Elvys Alves; Souza, Társis Marinho de; Souza, Társis Marinho de; Soares, Elvys Alves; Oliveira, Leonardo Fernandes Mendonça de; Medeiros, Flavio MotaItem Você na Câmara: A inteligência artificial como ferramenta de auxílio à população brasileira no entendimento das propostas legislativas que tramitam pela Câmara dos Deputados(2025) Santos, Gabriel de Jesus; Souza, Társis Marinho de; Souza, Társis Marinho de; Silva, Cledja Karina Rolim da; Tenório, Fernando Antônio Guimarães
- «
- 1 (current)
- 2
- 3
- »