INESC TEC - Institute for Systems and Computer Engineering, Technology and Science (INESC TEC)

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Using virtual choreographies to identify office users' behaviors to target behavior change based on their potential to impact energy consumption

Publication . Cassola, Fernando; Morgado, Leonel; Coelho, António; Paredes, Hugo; Barbosa, Antonio; Tavares, Helga; Soares, F. J.

Reducing office buildings’ energy consumption can contribute significantly towards carbon reduction commitments since it represents ∼40% of total energy consumption. Major components of this are lighting, electrical equipment, heating, and central cooling systems. Solid evidence demonstrates that individual occupants’ behaviors impact these energy consumption components. In this work, we propose the methodology of using virtual choreographies to identify and prioritize behavior-change interventions for office users based on the potential impact of specific behaviors on energy consumption. We studied the energy-related office behaviors of individuals by combining three sources of data: direct observations, electricity meters, and computer logs. Data show that there are behaviors with significant consumption impact but with little potential for behavioral change, while other behaviors have substantial potential for lowering energy consumption via behavioral change.

2022-06-14Journal article

Open access

Combining low-code development with ChatGPT to novel no-code approaches: a focus-group study

Publication . Martins, José; Branco, Frederico; São Mamede, Henrique; Martins, José

Low-code tools are a trend in software development for business solutions due to their agility and ease of use. There are a certain number of vendors with such solutions. Still, in most Western countries, there is a clear need for the existence of greater quantities of certified and experienced professionals to work with those tools. This means that companies with more resources can attract and maintain those professionals, whilst other smaller organizations must rely on an endless search for this scarce resource. We will present and validate a model designed to transform ChatGPT into a low-code developer, addressing the demand for a more skilled human resource solution. This innovative tool underwent rigorous validation via a focus group study, engaging a panel of highly experienced experts. Their invaluable insights and feedback on the proposed model were systematically gathered and meticulously analysed.

2023-11-01Journal article

Restricted access

A survey on association rule mining for enterprise architecture model discovery

Publication . Pinheiro, Carlos; Guerreiro, Sérgio; São Mamede, Henrique

Association Rule Mining (ARM) is a field of data mining (DM) that attempts to identify correlations among database items. It has been applied in various domains to discover patterns, provide insight into different topics, and build understandable, descriptive, and predic- tive models. On the one hand, Enterprise Architecture (EA) is a coherent set of principles, methods, and models suit- able for designing organizational structures. It uses view- points derived from EA models to express different concerns about a company and its IT landscape, such as organizational hierarchies, processes, services, applica- tions, and data. EA mining is the use of DM techniques to obtain EA models. This paper presents a literature review to identify the newest and most cited ARM algorithms and techniques suitable for EA mining that focus on automating the creation of EA models from existent data in application systems and services. It systematically identifies and maps fourteen candidate algorithms into four categories useful for EA mining: (i) General Frequent Pattern Mining, (ii) High Utility Pattern Mining, (iii) Parallel Pattern Mining, and (iv) Distribute Pattern Mining. Based on that, it dis- cusses some possibilities and presents an exemplification with a prototype hypothesizing an ARM application for EA mining.

2023-12-21Journal article

Restricted access

Immersion for AI: immersive learning with artificial intelligence

Publication . Morgado, Leonel

This work reflects upon what Immersion can mean from the perspective of an Artificial Intelligence (AI). Applying the lens of immersive learning theory, it seeks to understand whether this new perspective supports ways for AI participation in cognitive ecologies. By treating AI as a participant rather than a tool, it explores what other participants (humans and other AIs) need to consider in environments where AI can meaningfully engage and contribute to the cognitive ecology, and what the implications are for designing such learning environments. Drawing from the three conceptual dimensions of immersion—System, Narrative, and Agency—this work reinterprets AIs in immersive learning contexts. It outlines practical implications for designing learning environments where AIs are surrounded by external digital services, can interpret a narrative of origins, changes, and structural developments in data, and dynamically respond, making operational and tac-tical decisions that shape human-AI collaboration. Finally, this work suggests how these insights might influence the future of AI training, proposing that immersive learning theory can inform the development of AIs capable of evolving beyond static models. This paper paves the way for understanding AI as an immersive learner and participant in evolving human-AI cognitive ecosystems.

2025Conference object

Open access

Factors affecting cloud computing adoption in the education context: systematic literature review

Publication . Santos, António; Martins, José; Gonçalves, Ramiro; São Mamede, Henrique; Branco, Frederico; Pestana, Pedro Duarte; Martins, José

This systematic literature review investigates the factors influencing cloud computing adoption within both educational and organizational settings. By synthesizing a comprehensive body of research, this study finds and analyzes the determinants that shape the decision-making process about cloud technology adoption. Security, cost-effectiveness, scalability, interoperability, and regulatory compliance are examined across educational institutions and organizational contexts. Additionally, socio-economic, political, and technological factors specific to each context are explored to provide a nuanced understanding of the challenges and opportunities associated with cloud computing adoption. The review reveals commonalities and differences in adoption drivers and barriers between education and organizational environments, offering insights into tailored strategies for effective implementation. This research contributes to the existing literature by shedding light on the multifaceted nature of cloud adoption and offering valuable guidance for educators, organizational leaders, policymakers, and technology providers looking to use cloud computing to enhance operations and services.

2024-05-28Journal article

Open access