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Sobre

Sobre

Arsénio Reis (M) é Especialista de Informatica na Universidade de Trás-os-MOntes e Alto Douro (UTAD). Doutourou-se em 2015, na UTAD. Em 2016 integrou o INESC- TEC como investigador no centro CSIG. De 2006 a 2009, foi Coordenador Técnico de Informática, e de 2009 a 2014 foi Director dos Serviços de Informática e Comuibcações da UTAD. Em 2007, completou o Diploma de Especialização em Sociedade de Informação e Inovação na Admintração Publica (DESIIAP), no Instituto Nacional de Administração (INA), e em 2009, concluiu o Curso de Alta Direção na Administração Pública (CADAP), também no INA. No decurso da sua carreira profisional, esteve envolvido em diversos projectos de investigação e desenvolvimento, em conjunto com parceiros publicos e privados, tendo representado a UTAD em diversas ocasiões, tais como, membro eleito do Conselho Geral da UTAD, entre 2009 e 2012, e vogal executivo da direção da European Information Systems Association(EUNIS), de 2009 a 2014. As sua principais areas de interesse são, desde há muito, as de Aystemas de Informação e Engenharia de Software, e mais recentemente, Acessibilidade, Interação Homem-Computador, e eSaude. Ele produziu mais de 40 papers cientificos, incluindo, capitulos de livro, artigos e comunicações em actas de conferencias e revistas cientificas. Participou na oeganização de eventos cientificos de varias naturezas, nacionais e internacionais, dos quais se destaca, a organização do Congresso da EUNIS em 2012, na UTAD.

Tópicos
de interesse
Detalhes

Detalhes

  • Nome

    Arsénio Reis
  • Cargo

    Investigador Sénior
  • Desde

    01 agosto 2016
012
Publicações

2024

Context-Aware System for Information Flow Management in Factories of the Future

Autores
Monteiro, P; Pereira, R; Nunes, R; Reis, A; Pinto, T;

Publicação
APPLIED SCIENCES-BASEL

Abstract
The trends of the 21st century are challenging the traditional production process due to the reduction in the life cycle of products and the demand for more complex products in greater quantities. Industry 4.0 (I4.0) was introduced in 2011 and it is recognized as the fourth industrial revolution, with the aim of improving manufacturing processes and increasing the competitiveness of industry. I4.0 uses technological concepts such as Cyber-Physical Systems, Internet of Things and Cloud Computing to create services, reduce costs and increase productivity. In addition, concepts such as Smart Factories are emerging, which use context awareness to assist people and optimize tasks based on data from the physical and virtual world. This article explores and applies the capabilities of context-aware applications in industry, with a focus on production lines. In specific, this paper proposes a context-aware application based on a microservices approach, intended for integration into a context-aware information system, with specific application in the area of manufacturing. The manuscript presents a detailed architecture for structuring the application, explaining components, functions and contributions. The discussion covers development technologies, integration and communication between the application and other services, as well as experimental findings, which demonstrate the applicability and advantages of the proposed solution.

2024

Roadmap for Implementing Business Intelligence Systems in Higher Education Institutions: Systematic Literature Review

Autores
Sequeira, R; Reis, A; Alves, P; Branco, F;

Publicação
INFORMATION

Abstract
Higher education institutions (HEIs) make decisions in several domains, namely strategic and internal management, without using systematized data that support these decisions, which may jeopardize the success of their actions or even their efficiency. Thus, HEIs must define and monitor strategies and policies essential for decision making in their various areas and levels, in which business intelligence (BI) plays a leading role. This study presents a systematic literature review (SLR) aimed at identifying and analyzing primary studies that propose a roadmap for the implementation of a BI system in HEIs. The objectives of the SLR are to identify and characterize (i) the strategic objectives that underlie decision making, activities, processes, and information in HEIs; (ii) the BI systems used in HEIs; (iii) the methods and techniques applied in the design of a BI architecture in HEIs. The results showed that there is space for developing research in this area since it was possible to identify several studies on the use of BI in HEIs, although a roadmap for its implementation was not identified, making it necessary to define a roadmap for the implementation of BI systems that can serve as a reference for HEIs.

2024

Roadmap Proposal for the Implementation of Business Intelligence Systems in Higher Education Institutions

Autores
Sequeira, N; Reis, A; Branco, F; Alves, P;

Publicação
Communications in Computer and Information Science

Abstract
Nowadays, Higher Education Institutions (HEIs) are faced with the crucial challenge of establishing and supervising strategies and policies that are essential for decisions in various areas and at various levels. Within this context, the importance of Business Intelligence (BI) has increased significantly, emerging as an essential tool for analysing and managing data. This BI capability enables HEIs to make more informed choices in line with their global strategies. This research focuses on developing a roadmap for the effective implementation of BI systems in HEIs. Using a Design Science Research (DSR) methodology, this work proposes a structured and adaptable roadmap that covers the key factors from the design to the implementation of BI systems in HEIs. This roadmap includes not only a reference architecture for BI systems but also a set of dashboards. The roadmap was validated through a case study at the University of Trás-os-Montes e Alto Douro (UTAD), involving exploratory analysis and feedback from experts. This study stands out for its practical and theoretical approach, offering a strategic and practical guide for the adoption of BI systems in HEIs, thus responding to a need identified in the academic literature. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

2023

A Machine Learning Tool to Monitor and Forecast Results from Testing Products in End-of-Line Systems

Autores
Nunes, C; Nunes, R; Pires, EJS; Barroso, J; Reis, A;

Publicação
APPLIED SCIENCES-BASEL

Abstract
The massive industrialization of products in a factory environment requires testing the product at a stage before its exportation to the sales market. For example, the end-of-line tests at Continental Advanced Antenna contribute to the validation of an antenna's functionality, a product manufactured by this organization. In addition, the storage of information from the testing process allows the data manipulation through automated machine learning algorithms in search of a beneficial contribution. Studies in this area (automatic learning/machine learning) lead to the search and development of tools designed with objectives such as preventing anomalies in the production line, predictive maintenance, product quality assurance, forecast demand, forecasting safety problems, increasing resources, proactive maintenance, resource scalability, reduced production time, and anomaly detection, isolation, and correction. Once applied to the manufacturing environment, these advantages make the EOL system more productive, reliable, and less time-consuming. This way, a tool is proposed that allows the visualization and previous detection of trends associated with faults in the antenna testing system. Furthermore, it focuses on predicting failures at Continental's EOL.

2023

Design of Context-Aware Information Systems in Manufacturing Industries: Overview and Challenges

Autores
Santos, A; Lima, C; Reis, A; Pinto, T; Nogueira, P; Barroso, J;

Publicação
Distributed Computing and Artificial Intelligence, Special Sessions I, 20th International Conference, Guimaraes, Portugal, 12-14 July 2023.

Abstract
In the last 30 years, several academic and commercial projects have explored the context-awareness concept in multiple domains. Ubiquitous computing and ambient intelligence are features associated with the 4th generation industry empowering space to interact and respond appropriately according to context. In the scope of Industry 4.0, context-aware systems aim to improve productivity in smart factories and offer assistance to workers through services, applications, and devices, delivering functionalities and contextualised content. This article, through descriptive research, discusses the concepts related to context, presents and analyses projects related to ubiquitous computing and associated with Industry 4.0, and discusses the main challenges in systems and applications development to support intelligent environments for increased productivity, supporting informed decision-making in the factories of the future. The study results indicate that many research questions regarding the analysed projects remain the same, leading the research in the context-aware systems area to minimise issues related to context-aware features, improving the incorporation of Industry 4.0 paradigm concepts. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Teses
supervisionadas

2023

Aprendizagem automática em testes fim de linha

Autor
Carlos Henrique Carvalho Nunes

Instituição
UTAD

2023

Roadmap para implementação de sistemas de business inteligence em instituições do ensino superior

Autor
Nuno Romeu Cardoso Sequeira

Instituição
UTAD

2023

Uso de assistentes virtuais no apoio à gestão de produção

Autor
Rodrigo Cardoso Pereira

Instituição
UTAD

2022

Tecnologias e aplicações da Interface Cérebro-Computador (BCI)

Autor
Pedro Alexandre santos Letra

Instituição
UTAD

2022

Elders Suport service through unmanned aerial vehicles

Autor
DAVID FERREIRA SAFADINHO

Instituição
UTAD