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

IoT Data Storage in the Cloud: A Case Study in Human Biometeorology

  • @INPROCEEDINGS{10.1007/978-3-319-67636-4_26,
        author={Brunno Vanelli and A. Pinto and Madalena Silva and M. Dantas and M. Fazio and A. Celesti and M. Villari},
        title={IoT Data Storage in the Cloud: A Case Study in Human Biometeorology},
        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={AAL Cloud computing Human biometeorology IoT},
        doi={10.1007/978-3-319-67636-4_26}
    }
    
  • Brunno Vanelli
    A. Pinto
    Madalena Silva
    M. Dantas
    M. Fazio
    A. Celesti
    M. Villari
    Year: 2017
    IoT Data Storage in the Cloud: A Case Study in Human Biometeorology
    IISSC & CN4IOT
    Springer
    DOI: 10.1007/978-3-319-67636-4_26
Brunno Vanelli1, A. Pinto1, Madalena Silva1, M. Dantas1,*, M. Fazio2,*, A. Celesti2,*, M. Villari,*
  • 1: Federal University of Santa Catarina
  • 2: University of Messina
*Contact email: mario.dantas@ufsc.br, mfazio@unime.it, acelesti@unime.it, mvillari@unime.it

Abstract

The IoT (Internet of Things) has emerged to increase the potentiality of pervasive monitoring devices. However, the implementation and integration of IoT devices, data storage and the development of applications are still considered challenging. This paper presents an infrastructure for aggregating and storing data from different sources from IoT devices to the cloud. In order to evaluate the infrastructure regarding the quality in storage, it has been implemented and verified in an AAL (Ambient Assisted Living) case scenario, the main application being Human Biometeorology. The evaluation of metrics related to sending, receiving and storing data demonstrate that the experimental environment is completely reliable and appropriate for the case study in question.