P
Paulo Carreira
Researcher at Instituto Superior Técnico
Publications - 53
Citations - 875
Paulo Carreira is an academic researcher from Instituto Superior Técnico. The author has contributed to research in topics: Data warehouse & Energy management. The author has an hindex of 14, co-authored 53 publications receiving 691 citations. Previous affiliations of Paulo Carreira include Technical University of Lisbon & INESC-ID.
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Building automation systems: Concepts and technology review
TL;DR: Systematizes fundamental concepts and requirements of BA systems, defining each aspect based upon established literature standards and concluding that none of the existing approaches are able to fully overcome the problem of heterogeneity by satisfactorily addressing all the aspects of BA endorsed by the standards.
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Towards an energy management maturity model
TL;DR: In this paper, the authors propose an Energy Management Maturity Model that can be used to guide organizations in their energy management implementation efforts to incrementally achieve compliance with energy management standards such as ISO 50001.
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Comparative assessment of low-complexity models to predict electricity consumption in an institutional building: Linear regression vs. fuzzy modeling vs. neural networks
Henrique Pombeiro,Henrique Pombeiro,Rodolfo Santos,Paulo Carreira,Paulo Carreira,Carlos A. Silva,João M. C. Sousa +6 more
TL;DR: The adequacy of plain-designed non-linear models to predict energy consumption in a real-world Intelligent Building setting by using simple predictor variables such as time-of-day, weather conditions, and occupancy as estimated from WiFi traffic is studied.
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Can HVAC really learn from users? A simulation-based study on the effectiveness of voting for comfort and energy use optimization
TL;DR: The results indicate that employing a k-means machine learning technique enables the automatic configuration of an HVAC system to reduce energy consumption while keeping the majority of occupants within acceptable comfort levels.
Proceedings ArticleDOI
Energy Cloud: Real-Time Cloud-Native Energy Management System to Monitor and Analyze Energy Consumption in Multiple Industrial Sites
TL;DR: This work proposes a cloud-native industrial EMS solution with cloud computing capabilities that is expected to generate useful knowledge in a shorter time period, enabling organizations to react quicker to changes of events and detect hidden patterns that compromise efficiency.