Cloud Infrastructures, Services, and IoT Systems for Smart Cities. Second EAI International Conference, IISSC 2017 and CN4IoT 2017, Brindisi, Italy, April 20–21, 2017, Proceedings

Research Article

Dynamic Identification of Participatory Mobile Health Communities

  • @INPROCEEDINGS{10.1007/978-3-319-67636-4_22,
        author={Isam Aljawarneh and Paolo Bellavista and Carlos Rolt and Luca Foschini},
        title={Dynamic Identification of Participatory Mobile Health Communities},
        proceedings={Cloud Infrastructures, Services, and IoT Systems for Smart Cities. Second EAI International Conference, IISSC 2017 and CN4IoT 2017, Brindisi, Italy, April 20--21, 2017, Proceedings},
        proceedings_a={IISSC \& CN4IOT},
        year={2017},
        month={11},
        keywords={Mobile healthcare Middleware Crowdsourcing Mobile Health Communities Community detection},
        doi={10.1007/978-3-319-67636-4_22}
    }
    
  • Isam Aljawarneh
    Paolo Bellavista
    Carlos Rolt
    Luca Foschini
    Year: 2017
    Dynamic Identification of Participatory Mobile Health Communities
    IISSC & CN4IOT
    Springer
    DOI: 10.1007/978-3-319-67636-4_22
Isam Aljawarneh1,*, Paolo Bellavista1,*, Carlos Rolt2,*, Luca Foschini1,*
  • 1: University of Bologna
  • 2: Universidade do Estado de Santa Catarina
*Contact email: isam.aljawarneh3@unibo.it, paolo.bellavista@unibo.it, rolt@udesc.br, luca.foschini@unibo.it

Abstract

Today’s spread of chronic diseases and the need to control infectious diseases outbreaks have raised the demand for integrated information systems that can support patients while moving anywhere and anytime. This has been promoted by recent evolution in telecommunication technologies, together with an exponential increase in using sensor-enabled mobile devices on a daily basis. The construction of Mobile Health Communities (MHC) supported by Mobile CrowdSensing (MCS) is essential for mobile healthcare emergency scenarios. In a previous work, we have introduced the COLLEGA middleware, which integrates modules for supporting mobile health scenarios and the formation of MHCs through MCS. In this paper, we extend the COLLEGA middleware to address the need in real time scenarios to handle data arriving continuously in streams from MHC’s members. In particular, this paper describes the novel COLLEGA support for managing the real-time formation of MHCs. Experimental results are also provided that show the effectiveness of our identification solution.