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International Conference on Emerging technologies and Factory Automation (ETFA)

作者： Luis Piardi André Oliveira Pedro Costa Paulo Leitão Research Center in Digitalization and Intelligent Robotics (CeDRI) Instituto Politécnico de Bragança Bragança Portugal Faculty of Engineering University of Porto (FEUP) Porto Portugal Universidade Tecnológica Federal do Paraná (UTFPR) Curitiba-PR Brazil Technology and Science (INESC TEC) Institute for Systems and Computer Engineering Porto Portugal Laboratório Associado para a Sustentabilidade e Tecnologia em Regiões de Montanha (SusTEC) Instituto Politécnico de Bragança Bragança Portugal

ISBN: (数字)9798350361230

ISBN: (纸本)9798350361247

Cyber-physical systems (CPS) rapidly expand within industrial contexts in a new era of digitalization, processing power, and inter-device communication capabilities. These advancements integrate technologies such as the Internet of Things (IoT), artificial intelligence (AI), and cloud and edge computing, granting processes and operations a high degree of autonomy. In addition, these interconnections foster collective intelligence arising from information exchange and collaboration between components, often outperforming individual capabilities. This collective intelligence manifests in fault detection and diagnosis (FDD) tasks within CPS, as it significantly improves the flexibility, performance, and scalability. However, the inherent complexity of CPS poses challenges in determining the best configuration of the collaboration parameters, such as when and how to collaborate, wherein incorrect adjustments may lead to decision errors and compromise the system's performance. With this in mind, this paper proposes seven metrics to evaluate collaboration performance for fault detection and diagnosis in multi-agent systems (MAS)-based CPS, evaluating when the collaboration is beneficial or when the collaboration parameters need to be adjusted. The experiments focus on collaborative fault detection in temperature and humidity sensors within warehouse racks, where the proposed evaluation metrics point out the impact of collaboration on the detection task, as well as possible actions to be adopted to improve the agent's performance.

关键词： Measurement Temperature sensors Fault detection System performance Collaboration Cyber-physical systems Collective intelligence Sensors Internet of Things Artificial intelligence

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Modelling the Dependence of Chlorophyll Leaf-Clip Measures on Vegetation Indices Derived from Multispectral UAS Images in Vineyards Parcels

Modelling the Dependence of Chlorophyll Leaf-Clip Measures o...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Gil Gonçalves Umberto Andriolo Lúcio Paiva Cristiano Premebida António Ferraz Department of Mathematics University of Coimbra Coimbra Portugal Department of Electrical and Computer Engineering INESC Coimbra Coimbra Portugal Research Centre for Natural Resources Environment and Society Polytechnic Institute of Coimbra Coimbra Agrarian Technical School Coimbra Portugal Department of Electrical and Computer Engineering Institute of Systems and Robotics University of Coimbra Coimbra Portugal NASA Jet Propulsion Laboratory Pasadena United States

Multispectral images and leaf-clip measurements were used for evaluating the Chlorophyll (Chl) content on grapevine leaves through the use of vegetation indices. The multispectral leaf images were taken by a sensor onboard an UAS, which was placed over a table at a height of 70 cm. Images were radiometrically and geometrically processed to obtain accurate coregistered five band image stacks. Using a Kmeans segmentation, each leaf imaged in a multispectral image was automatically detected and the mean leaf reflectance values were used to compute three vegetation indices: NDVI, NDRE, and GLI. When compared to leaf-clip measurements, the results indicated that the NDRE index was the best predictor of Chl leaf content (R2=0.81). The obtained NDRE regression model can be used in UAS-based multispectral orthomosaics to generate canopy Chl maps at vine-row scale, which can assist vine growers in monitoring the spatial and temporal variability of grapevine vigor.

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Laser Engraving for 3D Surfaces: A Robotized Application Case Study 16th

Laser Engraving for 3D Surfaces: A Robotized Application Ca...

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16th APCA International Conference on Automatic Control and Soft Computing, CONTROLO 2024

作者： Alvarez, Mariano Brancalião, Laiany Carneiro, Jorge Costa, Paulo Coelho, João Paulo Gonçalves, José Instituto Politécnico de Bragança Campus de Santa Apolónia Bragança5300-253 Portugal Instituto Politécnico de Bragança Campus de Santa Apolónia Bragança5300-253 Portugal Faculty of Engineering of the University of Porto Porto4200-465 Portugal University of Léon Campus de Vegazana s/n León24071 Spain GRESTEL – Produtos Cerâmicos S.A. Vagos Portugal INESC TEC - Institute for Systems and Computer Engineering Technology and Science Porto Portugal

ISBN: (纸本)9783031817236

One of the industry’s most common applications of lasers is engraving, which is generally performed on flat surfaces. However, there are many situations where the object to be engraved has an unevenly curved geometry. In those cases, the light power density will be different along the surface for a fixed head, leading to a poor engraving result. This work deals with this problem by designing a robotic application capable of detecting variations on the object surface and automatically creating a trajectory to engrave on it correctly. This was made possible through a robotic manipulator, a time-of-flight distance sensor, and a data processing algorithm over the measured data. Obtained results were acquired using a custom-made test rig and validated by delivering consistent engraving results on irregular surface shapes. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Robotic assembly

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MonoVisual3DFilter: 3D tomatoes' localisation with monocular cameras using histogram filters

arXiv

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arXiv 2023年

作者： Magalhães, Sandro Costa dos Santos, Filipe Neves Moreira, António Paulo Dias, Jorge Faculty of Engineering University of Porto Porto Portugal INESC TEC Instituto de Engenharia de Sistemas e Computadores Tecnologia e Ciência Porto Portugal Institute of Systems and Robotics Department of Electrical Engineering and Computers University of Coimbra Coimbra Portugal Khalifa University of Science Technology and Research Abu Dhabi United Arab Emirates

Performing tasks in agriculture, such as fruit monitoring or harvesting, requires perceiving the objects' spatial position. RGB-D cameras are limited under open-field environments due to lightning interferences. So, in this study, we state to answer the research question: "How can we use and control monocular sensors to perceive objects' position in the 3D task space?" Towards this aim, we approached histogram filters (Bayesian discrete filters) to estimate the position of tomatoes in the tomato plant through the algorithm MonoVisual3DFilter. Two kernel filters were studied: the square kernel and the Gaussian kernel. The implemented algorithm was essayed in simulation, with and without Gaussian noise and random noise, and in a testbed at laboratory conditions. The algorithm reported a mean absolute error lower than 10 mm in simulation and 20 mm in the testbed at laboratory conditions with an assessing distance of about 0.5 m. So, the results are viable for real environments and should be improved at closer distances. © 2023, CC BY-NC-ND.

关键词： Fruits

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Differential Refractometric Platform for Reliable Biosensing based on Long-period Gratings and Molecular Imprinting 27

Differential Refractometric Platform for Reliable Biosensing...

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27th International Conference on Optical Fiber Sensors, OFS 2022

作者： Mendes, João P. Coelho, Luís C. C. Pereira, Carlos M. Jorge, Pedro A. S. Chemistry Research Unit of University of Porto Faculty of Sciences University of Porto Porto4169-007 Portugal Faculty of Sciences of University of Porto INESC TEC - Institute for Systems and Computer EngineeringTechnology and Science Porto4169-007 Portugal Departamento de Química E Bioquímica Faculdade de Ciências Universidade do Porto Porto4169-007 Portugal Departmento de Física E Astronomia Faculdade de Ciências Universidade do Porto Porto4169-007 Portugal

ISBN: (纸本)9781957171142

A new (bio)sensing platform based on differential refractometric measurements was developed. The sensing scheme is based on the combination LPFGs/MIP/NIP, involving a dual channel system for real-time compensation of non-specific interactions. The correction system improves the sensor behavior by reducing the response to interferents by 30%. © 2022 The Author(s).

关键词： Effective refractive index Long period gratings Optical standards Sensor performance Sensors Temperature sensors

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Tensions in design and participation processes: An ethnographic approach to the design, building and evaluation of a collective intelligence model

Tensions in design and participation processes: An ethnograp...

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International Conference on computer Supported Cooperative Work in Design

作者： Ramon Chaves Claudia Motta Antonio Correia Jano de Souza Daniel Schneider Systems Engineering and Computer Science Program (PESC/COPPE/UFRJ) Rio de Janeiro Brazil Postgraduate Program in Informatics PPGI/UFRJ Rio de Janeiro Brazil Tércio Pacitti Institute of Computer Applications and Research (NCE) Federal University of Rio de Janeiro Brazil UTAD INESC TEC and University of Trás-os-Montes e Alto Douro Vila Real Portugal College of Information Science & Technology University of Nebraska at Omaha Omaha NE USA

This paper explores the challenges and strategies used to design, build and evaluate a collective intelligence (CI) model to support discussions about cities. Through an autoethnography of ideas and discussion practices in both online and offline contexts, this work explores the tensions between the chosen methodological approaches, including design science research (DSR) and participatory action research (PAR). Moreover, we also examine the challenges and pitfalls observed during the practical conduction of this research when involving participants in the process of empirically evaluating the proposed model. Finally, aspects related to the autoethnographic process itself as a reflective method are discussed alongside the consequences of desiring and seeking participation in the research process.

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Impact of COVID-19 and Ukraine-Russia Conflict on the National Energy and Climate Strategies of Portugal and Spain

Impact of COVID-19 and Ukraine-Russia Conflict on the Nation...

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International Conference on European Electricity Market, EEM

作者： Max Alberto López-Maciel Mónica Meireles José Villar André Oliveira Edimar Ramalho Fátima Lima Mara Madaleno Marta Ferreira Dias Margarita Robaina DAO & CESAM University of Aveiro Aveiro Portugal ISCTE-University Institute of Lisbon and Business Research Unit (bru_iscte) Lisboa Portugal Campus da FEUP INESC TEC Centre for Power and Energy Systems Porto Portugal GOVCOPP – Research Unit on Governance Competitiveness and Public Policies DEGEIT – Department of Economics Management Industrial Engineering and Tourism University of Aveiro Aveiro Portugal

ISBN: (数字)9798350381740

ISBN: (纸本)9798350381757

This research examines the impact of the COVID-19 pandemic and the Ukraine-Russia conflict on Portugal and Spain's national energy and climate plans. Both countries have updated their plans in response to these events, emphasizing energy efficiency, renewable energy investment, and circular economy principles. Portugal focused on addressing energy poverty and digitalization, while Spain accelerated its energy transition to align with the European Green Deal. Additionally, the Ukraine-Russia conflict prompted measures to enhance energy security and NECPs in both countries. Through a semi-systematic literature review spanning 2020–2023, our study analyzes how these global events shaped national energy and climate plans. The case studies of Portugal and Spain highlight the importance of flexibility and resilience in crafting sustainable energy strategies during such a complex crisis.

关键词： COVID-19 Renewable energy sources Bibliographies Green products Europe Pollution measurement Security

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Mapping Tokenomics Arrangements to Expand the Digital Nomad Ecosystem

Mapping Tokenomics Arrangements to Expand the Digital Nomad ...

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International Conference on computer Supported Cooperative Work in Design

作者： Marcos Antonio de Almeida António Correia Jano Moreira de Souza Daniel Schneider Systems Engineering and Computer Science Program (PESC/COPPE/UFRJ) Rio de Janeiro Brazil INESC TEC and University of Trás-os-Montes e Alto Douro Vila Real Portugal College of Information Science & Technology University of Nebraska at Omaha Omaha NE USA Postgraduate Program in Informatics PPGI/UFRJ Rio de Janeiro Brazil Tércio Pacitti Institute of Computer Applications and Research NCE/UFRJ Rio de Janeiro Brazil

The Massification of remote work, in response to the COVID-19 pandemic, has been causing significant changes in productive and working arrangements, both for individuals, organizations, and society. At the level of personal life philosophy, for example, this transformation can be evidenced in the dissemination of digital nomadism values such as work/leisure balance among corporate workers. On the other hand, at the level of gig/crowd work platforms, the emergence of tensions may indicate the exhaustion of sociotechnical design models adopted by big techs. We show how evidence collected from digital nomads in empirical ethnography studies can inform HCI/CSCWD researchers of design-oriented strands to explore emerging opportunities in new creative digital crypto-economic ecosystems. Finally, we present a proposed research agenda to explore DNs’ activities in the crypto-economic ecosystem.

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Hybrid Recommendation System for Young Football Athletes Customized Training

Hybrid Recommendation System for Young Football Athletes Cu...

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Future of Information and Communication Conference, FICC 2020

作者： Matos, Paulo Rocha, João Gonçalves, Ramiro Santos, Filipe Abreu, David Soares, Hugo Martins, Constantino Computer Science Department Engineering Institute - Polytechnic of Porto Porto Portugal Trás-os-Montes e Alto Douro University Vila Real Portugal GECAD Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development Porto Portugal INESC TEC - Institute for Systems and Computer Engineering Technology and Science Porto Portugal

ISBN: (纸本)9783030394448

Information and communication technologies (ICTs) are been increasingly used in sports over the past decades, especially in professional football, with the goal of enhancing preparation and improve the athletes’ performance. Training programs, however, are not accessible for young and amateur athletes. Most of the systems available, don’t have learning skills to adjust, develop and find new suggestions for training, specifically designed for each athlete. In this paper we present the Smart Coach architecture and user adaptation model and describe our hybrid recommendation system to help the development of young athletes. It simplifies the relationship between the team’s technical staff leaders and their young athletes, enhancing the counselling of the young person and their development as an athlete. The system allows performance evaluation for young athletes utilizing various measurements. The match information is captured intuitively and adaptively by acquaintances, relatives and staff, using a comfortable smartphone interface. © Springer Nature Switzerland AG 2020.

关键词： Recommender systems

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BYtecounter: Improving Vehicle Turning-Movement Counting

BYTECounter: Improving Vehicle Turning-Movement Counting

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International Conference on Intelligent Transportation

作者： Mateus Líbano Monteiro Alexandre Bernardino H. Sofia Pinto Computer Science: Artificial Intelligence and Cybersecurity from Instituto Superior Técnico Universidade de Lisboa Portugal Department of Electrical and Computer Engineering Institute for and Systems and Robotics of Instituto Superior Técnico Universidade de Lisboa Portugal INESC-ID and Department of Computer Science and Artificial Intelligence Instituto Superior Técnico Universidade de Lisboa Portugal

This paper proposes a methodology to enhance the accuracy of vehicle turning-movement counting in video footage. The methodology uses a three-component system comprising object detection, object tracking, and object turning-movement counting. To improve vehicle detection, a custom vehicle neural network called YOLOv7-vehicles-0.1 was trained using a unique vehicle dataset comprising COCO, KITTI, and OpenImages datasets. Additionally, a novel tracker named BYtecounter was developed, using two virtual drawing objects, Regions and Lines, to count vehicles' turning movements based on trajectory information. The performance of our system was evaluated using the UA-DETRAC dataset, achieving an overall Movement Counting Accuracy (MCAcc) of 93.5% with a processing rate of 82.86 frames per second. This paper demonstrates that BYtecounter outperforms the state-of-the-art tracker, BYTE, and highlights the superiority, in terms of counting metrics, of YOLOv7-vehicles-0.1 over YOLOv7 models trained on the COCO dataset.

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