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About

About

  • Investigador do CESE - Centro de Engenharia de Sistemas Empresariais, do INESC TEC e Professor Adjunto no Instituto Politécnico do Porto;
  • Doutorado em Engenharia Informática pela Faculdade de Engenharia da Universidade do Porto;
  • A área de especialização foca problemas relacionados com a organização de informação em ambiente colaborativos (redes colaborativas) e a representação de conhecimento de domínio de forma partihada;
  • Participação em vários projetos nacionais e internacionais;
  • Com publicações científicas em atas de conferências e revistas;
  • Os interesses de investigação focam-se no estudo de: 1) métodos e teorias para agilizar a gestão de informação e partilha de conhecimento; 2) mecanismos de representação colaborativa de conhecimento; 3) princípios da semiótica cognitiva na construção de modelos pra estrutturação, organização de informação e visualização de informação em contextos industriais.

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Details

Details

001
Publications

2021

An IIoT Solution for SME’s

Authors
Cunha, B; Hernández, E; Rebelo, R; Sousa, C; Ferreira, F;

Publication
Lecture Notes in Electrical Engineering - CONTROLO 2020

Abstract

2021

Boosting E-Auditing Process Through E-Files Semantic Enrichment

Authors
Sousa, C; Carvalho, M; Pereira, C;

Publication
Advances in Intelligent Systems and Computing - Trends and Applications in Information Systems and Technologies

Abstract

2021

A Model for Designing SMES’ Digital Transformation Roadmap

Authors
Cunha, L; Sousa, C;

Publication
Advances in Intelligent Systems and Computing - Trends and Applications in Information Systems and Technologies

Abstract

2020

A Decision-Support System for Preventive Maintenance in Street Lighting Networks

Authors
Carneiro, D; Nunes, D; Sousa, C;

Publication
Advances in Intelligent Systems and Computing

Abstract
An holistic approach to decision support systems for intelligent public lighting control, must address both energy efficiency and maintenance. Currently, it is possible to remotely control and adjust luminaries behaviour, which poses new challenges at the maintenance level. The luminary efficiency depends on several efficiency factors, either related to the luminaries or the surrounding conditions. Those factors are hard to measure without understanding the luminary operating boundaries in a real context. For this early stage on preventive maintenance design, we propose an approach based on the combination of two models of the network, wherein each is representing a different but complementary perspective on the classifying of the operating conditions of the luminary as normal or abnormal. The results show that, despite the expected and normal differences, both models have a high degree of concordance in their predictions. © 2020, Springer Nature Switzerland AG.

2020

Decision intelligence in street lighting management

Authors
Nunes, D; Teixeira, D; Carneiro, D; Sousa, C; Novais, P;

Publication
Advances in Intelligent Systems and Computing

Abstract
The European Union has been making efforts to increase energy efficiency within its member states, in line with most of the industrialized countries. In these efforts, the energy consumed by public lighting networks is a key target as it represents approximately 50% of the electricity consumption of European cities. In this paper we propose an approach for the autonomous management of public lighting networks in which each luminary is managed individually and that takes into account both their individual characteristics as well as ambient data. The approach is compared against a traditional management scheme, leading to a reduction in energy consumption of 28%. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2020.