Percorrer por autor "Sequeira, Romeu"
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- Data Engineering Roadmap for Implementing Business Intelligence in Higher EducationPublication . Sequeira, Romeu; Reis, Arsénio; Branco, Frederico; Alves, PauloThis article addresses the implementation of Business Intelligence (BI) systems in Higher Education Institutions (HEIs), focusing on developing an appropriate data architecture that meets the specificities and requirements of this sector. With the rapid advance of information technologies, HEIs face the growing challenge of managing a considerable volume of data, making it essential to implement BI systems that support informed and efficient decision-making. Using the Design Science Research methodology, this study proposes a BI architecture model that aligns technologies with HEIs' academic and administrative needs and facilitates their integration and ongoing maintenance. The model is designed to be flexible and scalable, allowing adaptations as institutional needs evolve. The article describes the architecture development process, from initial planning to implementation, and discusses how this framework can significantly improve data management and the quality of decision-making processes in educational institutions. The research offers practical and theoretical insights for academics and managers seeking to optimize the use of BI in educational contexts.
- Development of an integrated portal for farm audit management with geospatial supportPublication . Correia, Maria; Alves, Joaquim; Sequeira, Romeu; Exposto, JoséThis paper introduces the development of an innovative portal designed to optimize the management of agricultural field audits and ensure compliance with Common Agricultural Policy (CAP) regulations. The system is capable of handling more than five thousand audits, addressing specific audit requirements and integrating geospatial data management through technologies such as Django, and PostGIS, alongside libraries like Leaflet.js and Chart.js. The back end, developed in Django, provides a scalable and reliable infrastructure, supported by containerization deployment, while the front-end offers intuitive tools for data visualization and interaction. The platform’s modular design allows users at various access levels to efficiently manage data, track audit progress, upload documents, and monitor resources. By consolidating all audit tasks into a single application, the system reduces processing time, simplifies workflows, and improves data accuracy, leading to greater overall productivity. Preliminary testing demonstrates the system’s effectiveness for large-scale audits, and its scalability allows for future integrations, including IoT devices and predictive analytics, further enhancing decision-making and real-time data collection. This flexible and efficient solution meets the evolving needs of agricultural management.
- Enhancing agricultural audit systems with IoT and predictive analytics: deployment and performancePublication . Correia, Maria Patrocínia; Alves, Joaquim; Sequeira, Romeu; Exposto, JoséThis article proposes an extension of a geospatial-based agricultural audit platform by integrating Internet of Things technologies and predictive analytics. It builds on previous work to address field connectivity, scalability, and risk anticipation. The proposal outlines a modular architecture, identifies technical challenges and mitigation strategies, and presents use cases for different user profiles. Ethical, legal, and environmental implications of digitalisation are also discussed. This conceptual work supports future experimental validation and highlights the potential of digital transformation to enhance compliance with the Common Agricultural Policy and align with the European Green Deal priorities.
- Enhancing agricultural audit systems with IoT and predictive analytics: deployment and performancePublication . Correia, Maria; Alves, Joaquim; Sequeira, Romeu; Exposto, JoséThis article proposes an extension of a geospatial-based agricultural audit platform by integrating Internet of Things technologies and predictive analytics. It builds on previous work to address field connectivity, scalability, and risk anticipation. The proposal outlines a modular architecture, identifies technical challenges and mitigation strategies, and presents use cases for different user profiles. Ethical, legal, and environmental implications of digitalisation are also discussed. This conceptual work supports future experimental validation and highlights the potential of digital transformation to enhance compliance with the Common Agricultural Policy and align with the European Green Deal priorities
- Roadmap for implementing business intelligence systems in higher education institutions: systematic literature reviewPublication . Sequeira, Romeu; Reis, Arsénio; Alves, Paulo; Branco, FredericoHigher 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.
- Roadmap for implementing business intelligence systems in higher education institutions: validation of a case study at the university of Trás-os-Montes and Alto DouroPublication . Sequeira, Romeu; Reis, Arsénio; Branco, Frederico; Alves, PauloThe adoption of effective policies and access to relevant information are critical to improving strategic management and performance monitoring in Higher Education Institutions (HEIs), which is essential to promote data-driven decision-making. This article describes how an HEI can carry out the validation process when implementing a Business Intelligence (BI) system, and provides a detailed guide to doing so. Through a case study at the University of Trás-os-Montes and Alto Douro, a structured roadmap is validated, which acts as a visual and sequential guide to facilitate the effective implementation of BI solutions. The validation carried out through semi-structured interviews with experts and evaluation of dashboards by user groups, not only confirms the applicability and efficiency of the proposed model but also emphasises its practical relevance, providing valuable insights for the adaptation and use of BI in different educational contexts.