EAI Endorsed Transactions on Cloud Systems 17(9): e1

Research Article

A scalable middleware-based infrastructure for energy management and visualization in city districts

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  • @ARTICLE{10.4108/eai.28-6-2017.152753,
        author={Francesco G. Brundu and Edoardo Patti and Matteo Del Giudice and Anna Osello and Michela Ramassotto and Fabrizio Massara and Francesca Marchi and Alberto Musetti and Enrico Macii and Andrea Acquaviva},
        title={A scalable middleware-based infrastructure for energy management and visualization in city districts},
        journal={EAI Endorsed Transactions on Cloud Systems},
        volume={17},
        number={9},
        publisher={EAI},
        journal_a={CS},
        year={2017},
        month={6},
        keywords={Smart City, Pervasive Computing, Smart Devices, Internet of Things, Middleware, District},
        doi={10.4108/eai.28-6-2017.152753}
    }
    
  • Francesco G. Brundu
    Edoardo Patti
    Matteo Del Giudice
    Anna Osello
    Michela Ramassotto
    Fabrizio Massara
    Francesca Marchi
    Alberto Musetti
    Enrico Macii
    Andrea Acquaviva
    Year: 2017
    A scalable middleware-based infrastructure for energy management and visualization in city districts
    CS
    EAI
    DOI: 10.4108/eai.28-6-2017.152753
Francesco G. Brundu1,*, Edoardo Patti1, Matteo Del Giudice2, Anna Osello2, Michela Ramassotto3, Fabrizio Massara3, Francesca Marchi4, Alberto Musetti4, Enrico Macii1, Andrea Acquaviva1
  • 1: Dept. of Control and Computer Engineering, Politecnico di Torino, Italy
  • 2: Dept. of Structural, Construction and Geotechnical Engineering, Politecnico di Torino, Italy
  • 3: Consorzio per il Sistema Informativo, CSI Piemonte, Torino, Italy
  • 4: D’Appolonia S.P.A., Genova, Italy
*Contact email: francesco.brundu@polito.it

Abstract

Following the Smart City views, citizens, policy makers and energy distribution companies need a reliable and scalable infrastructure to manage and analyse energy consumption data in a city district context. In order to move forward this view, a city district model is needed, which takes into account di erent data-sources such as Building Information Models, Geographic Information Systems and real-time information coming from heterogeneous devices in the district. The Internet of Things paradigm is creating new business opportunities for low-cost, low-power and high-performance devices. Nevertheless, because of the "smart devices" heterogeneity, in order to provide uniform access to their functionalities, an abstract point of view is needed. Therefore, we propose an distributed software infrastructure, exploiting service-oriented middleware and ontology solutions to cope with the management, simulation and visualization of district energy data.