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Percorrer por autor "Rosse, Higor"

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  • Fairness in Designing Decision-Making Processes with Multi-Agent Systems and Human Factors
    Publication . Vieira, Gustavo; Zeiner, Herwig; Paletta, Lucas; Fernandes, Rui; Rosse, Higor; Sabiri, Khadija; Paz, Juan F De; Barbosa, José
    This paper explores the integration of Human Factors (HF) into Multi-Agent Systems (MAS) to enhance fairness in decision-making processes in Industry 5.0 environments. We contribute with a human-centred perspective in the development of MAS by integrating the physiological aspects of workers in the manufacturing industry. This culminates in the measurement of human resilience. This paper presents an automotive manufacturing environment where wearable sensors and AI-driven analytics assess workers' physiological and psychological stress levels to calculate a human resilience score. This score, along with worker preferences, supports a dynamic worker allocation algorithm based on MAS that adapts to production demands. Our approach embodies the Industry 5.0 vision of technologies that support adaptive, transparent and, above all, fair human management. The system uses advanced technologies to meet business goals and employee needs and to promote a more inclusive, supportive and people-centred work environment.
    2025Capítulo de livro Acesso aberto Ver mais
  • Modelling with NGSI-LD: the VALLPASS project case study
    Publication . Ribeiro, Tiago; Coelho, João Paulo; Jorge, Luísa; Sardão, Joaquim; Gonçalves, José; Rosse, Higor
    The smart cities paradigm covers multiple domains which span from citizens' accessibility and mobility to general infrastructures and services. Hence, smart cities can be seen as an excellent showcase of heterogeneity, namely at the data level. For this reason, they are a perfect candidate for linked data and semantic web concept applications. This powerful combination leads to interoperability at the data level which is one of the ultimate goals of the Internet of Things (IoT). In this reference frame, NGSI-LD is an open framework for context information processing consisting of both a semantic information model and a RESTful Application Programming Interface (API). This paper proposes a methodology for creating semantic data models in the context of IoT, namely to represent and describe data associated with digital twins. The methodology is presented in a practical way, through the process of creating an NGSI-LD semantic data model for the VALLPASS project, inserted in the traffic domain, which is one of the most popular in smart cities.
    2023Comunicação em conferência Acesso aberto Ver mais