INESCC-DL - Artigos em Revistas Internacionais
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- Energy audit as an input for energy management and energy efficiency improvement in a gypsum manufacturing plantPublication . Bernardo, Hermano; Oliveira, Filipe Tadeu; Serrano, LuisThis paper aims at presenting the main results of an energy audit performed to a gypsum production plant, in Portugal, which due to the amount of energy consumed must comply with the Portuguese program SGCIE (Intensive Energy Consumption Management System). The program was created in 2008 to promote energy efficiency and energy consumption monitoring in intensive energy consuming facilities (energy consumption higher than 500 toe per year). Facilities operators are required to perform energy audits and take actions to draw up an action plan for energy efficiency, establishing targets for energy consumption reduction and greenhouse gases emissions indexes. An energy audit was carried out to identify potential energy conservation measures for improving energy efficiency, and also typical energy consumption patterns, sector/equipment load profiles and thermal equipment performance. This tool gives managers the information to support decision making on improving energy performance and reducing greenhouse gas emissions. A number of tangible targets and measures were devised and set to be implemented in the next few years. Results show that there is a considerable potential for reduction in the energy consumption and greenhouse gases emissions of gypsum manufacturing plants. Here, as elsewhere in the industrial sector, energy efficiency can only be achieved through a continuous energy monitoring and management system.
- Rotating speed stability and mechanical vibration analysis of one-stage inertia flexible rotor driven by variable speed drivesPublication . Oliveira, Filipe Tadeu; Donsión, M.P.; Peláez, G.This paper poses some questions as to the adequacy of the widespread use of variable speed drives. It presents a comparison of different variable speed drives, by studying their output wave forms and applying them to a mechanical one stage inertia flexible rotor specially designed for this purpose. The comparison of the output of the variable speed drives used reveals significant differences between them, which affect the way the load is driven and the overall behaviour of the mechanical system. A comparison against a sine wave reference shows that even the best of the variable speed drives used is outperformed, since the “perfect” sine wave ensures constant rotating speed, thus minimizing vibrations along the mechanical shaft.
- Simulation of the effect of voltage transients on an induction motor with ATP/EMTPPublication . Gonçalves, José; Baptista, José; Pires Neves, Luís; Oliveira, Filipe TadeuThe present study aims at understanding the behaviour of the induction motor when subject to different kinds of disturbances. The intention was to broaden the study of some disturbances by using a transient simulation software, ATP/EMTP, and comparing results with laboratory measurements. Obtained simulation results approached very closely the laboratory measurements, with small differences probably due to the model simplifying assumptions and uncertainties associated to the model parameter estimation process. However, although this theoretical model presents a response very similar to the actual model, improvements could be made by better modelling of the mechanical load, and by using different kinds of dynamic loads. Also, the use of more accurate laboratory equipment, and namely, programmable power supplies could lead to more accurate comparisons and better learning.
- Predictable impact of lighting control on the energy consumption of a building through computational simulationPublication . Bernardo, H.; Leitão, S.; Neves, L.; Amaral, P.; Bernardo, Hermano; Pires Neves, LuísBuilding energy simulation tools provide accurate predictions of the energetic performance of buildings and thermal comfort of its occupants, allowing an evaluation of the impact of proposed improvement measures, in order to support choice for the more economically viable. This paper aims at determining the energy saving potential that can be obtained by adequate measures and investments. It presents the simulated values of the impact on the energy consumptions of a building, caused by artificial lighting control systems set to maximize use of natural lighting. Results show that optimization measures have a significant impact on energy consumptions reduction, and lead to important economical savings.
- 2ARTs: A Platform for Exercise Prescriptions in Cardiac Recovery PatientsPublication . Pereira, Andreia; Martinho, Ricardo; Pinto, Rui; Rijo, Rui; Grilo, CarlosDue to limited access, increasing costs and an ageing population, the global healthcare system faces significant coverage problems that call for innovative approaches. Health professionals are actively seeking alternative methods to provide care to an increasingly needy population, without increasing human effort and associated costs. eHealth platforms, which use technology to provide patient care, are emerging as transformative solutions for addressing these problems. This study is centered on the demand for a Decision Support System (DSS) in cardiology to enable doctors to prescribe individualized care inside Cardiac Rehabilitation Programmes (CRPs). The 2ARTs project’s main objective is to include a cardiac rehabilitation platform with a DSS within the hospital infrastructure. This DSS uses models to classify patients into different groups, delivering crucial information to assist with decisions regarding treatment. Regarding the DSS, Principal Component Analysis (PCA) emerged as a standout technique for dimensionality reduction, due to its interoperability with clustering algorithms and superior evaluation metrics. The most appropriate clustering technique was determined to be the K-means algorithm, which was supported by the experts analysis. In accordance with the goals of the 2ARTs project, this integration of PCA and K-means provides meaningful insights that improve reasoned decision-making.
- Systematic Review of Emotion Detection with Computer Vision and Deep LearningPublication . Pereira, Rafael; Mendes, Carla; Ribeiro, José; Ribeiro, Roberto; Miragaia, Rolando; Rodrigues, Nuno; Costa, Nuno; Pereira, AntónioEmotion recognition has become increasingly important in the field of Deep Learning (DL) and computer vision due to its broad applicability by using human–computer interaction (HCI) in areas such as psychology, healthcare, and entertainment. In this paper, we conduct a systematic review of facial and pose emotion recognition using DL and computer vision, analyzing and evaluating 77 papers from different sources under Preferred Reporting Items for Systematic Reviews and MetaAnalyses (PRISMA) guidelines. Our review covers several topics, including the scope and purpose of the studies, the methods employed, and the used datasets. The scope of this work is to conduct a systematic review of facial and pose emotion recognition using DL methods and computer vision. The studies were categorized based on a proposed taxonomy that describes the type of expressions used for emotion detection, the testing environment, the currently relevant DL methods, and the datasets used. The taxonomy of methods in our review includes Convolutional Neural Network (CNN), Faster Region-based Convolutional Neural Network (R-CNN), Vision Transformer (ViT), and “Other NNs”, which are the most commonly used models in the analyzed studies, indicating their trendiness in the field. Hybrid and augmented models are not explicitly categorized within this taxonomy, but they are still important to the field. This review offers an understanding of state-of-the-art computer vision algorithms and datasets for emotion recognition through facial expressions and body poses, allowing researchers to understand its fundamental components and trends.
- Applying deep learning to real-time UAV-based forest monitoring: Leveraging multi-sensor imagery for improved resultsPublication . Marques, Tomás; Carreira, Samuel; Miragaia, Rolando; Ramos, João; Pereira, AntónioRising global fire incidents necessitate effective solutions, with forest surveillance emerging as a crucial strategy. This paper proposes a complete solution using technology that integrates visible and infrared spectrum images through Unmanned Aerial Vehicles (UAVs) for enhanced detection of people and vehicles in forest environments. Unlike existing computer vision models relying on single-sensor imagery, this approach overcomes limitations posed by limited spectrum coverage, particularly addressing challenges in low-light conditions, fog, or smoke. The developed 4-channel model uses both types of images to take advantage of the strengths of each one simultaneously. This article presents the development and implementation of a solution for forest monitoring ranging from the transmission of images captured by a UAV to their analysis with an object detection model without human intervention. This model consists of a new version of the YOLOv5 (You Only Look Once) architecture. After the model analyzes the images, the results can be observed on a web platform on any device, anywhere in the world. For the model training, a dataset with thermal and visible images from the aerial perspective was captured with a UAV. From the development of this proposal, a new 4- channel model was created, presenting a substantial increase in precision and mAP (Mean Average Precision) metrics compared to traditional SOTA (state-of-the-art) models that only make use of red, green, and blue (RGB) images. Allied with the increase in precision, we confirmed the hypothesis that our model would perform better in conditions unfavorable to RGB images, identifying objects in situations with low light and reduced visibility with partial occlusions. With the model’s training using our dataset, we observed a significant increase in the model’s performance for images in the aerial perspective. This study introduces a modular system architecture featuring key modules: multisensor image capture, transmission, processing, analysis, and results presentation. Powered by an innovative object detection deep-learning model, these components collaborate to enable real-time, efficient, and distributed forest monitoring across diverse environments.
- A multi-criteria decision approach to sorting actions for promoting energy efficiencyPublication . Neves, Luís Miguel Pires; Martins, António Gomes; Antunes, Carlos Alberto Henggeler; Dias, Luís Miguel CândidoThis paper proposes a multi-criteria decision approach for sorting energy efficiency initiatives, promoted by electric utilities, with or without public funds authorized by a regulator, or promoted by an independent energy agency, overcoming the limitations and drawbacks of Cost-Benefit Analysis. The proposed approach is based on the ELECTRE-TRI multi-criteria method and allows the consideration of different kinds of impacts, although avoiding difficult measurements and unit conversions. The decision is based on all the significant effects of the initiative, both positive and negative ones, including ancillary effects often forgotten in cost-benefit analysis. The ELECTRE-TRI, as most multi-criteria methods, provides to the Decision Maker the ability of controlling the relevance each impact can have on the final decision in a transparent way. The decision support process encompasses a robustness analysis, which, together with a good documentation of the parameters supplied into the model, should support sound decisions. The models were tested with a set of real-world initiatives and compared with possible decisions based on Cost-Benefit analysis.
- Structuring an MCDA model using SSM: A case study in energy efficiencyPublication . Neves, Luís Miguel Pires; Dias, Luís Miguel Cândido; Antunes, Carlos Alberto Henggeler; Martins, António GomesThis work presents the use of a problem structuring method, Soft Systems Methodology (SSM), to structure a Multi-Criteria Decision Analysis (MCDA) model, aimed at appraising energy efficiency initiatives. SSM was useful to help defining clearly the decision problem context and the main actors involved, as well as to unveil the relevant objectives for each stakeholder. Keeney’s Value Focused Thinking approach was then used to refine and structure the list of objectives according to the perspective of the main evaluators identified. In addition to describing this particular case study, this paper aims at providing some general guidelines on how SSM may facilitate the emergence of objectives for MCDA models.
- Using SSM to rethink the analysis of energy efficiency initiativesPublication . Neves, Luís Miguel Pires; Martins, António Gomes; Antunes, Carlos Alberto Henggeler; Dias, Luís Miguel CândidoThis paper reflects an attempt to rethink the process of analysis of energy efficiency initiatives using soft systems methodology (SSM) as a problem structuring tool. The aim of the work is to provide public and private initiative promoters or evaluators with a structured support for a more informed decision regarding the implementation of energy efficiency measures. The SSM approach contributed with the identification of all market players and their relations, as well as the insight into the deficiencies of current methodologies. Some future work directions are also proposed.