Foundations of Data Quality Assurance for IoT-based Smart Applications

Rodrigo Tognieri, Glauber Camponogara, Juha-Pekka Soininen, Carlos Kamienski

    Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

    10 Citations (Scopus)


    Most current scientific and industrial efforts in IoT are geared towards building integrated platforms to finally realize its potential in commercial scale applications. The IoT and Big Data contemporary context brings a number of challenges, such as providing quality assurance (defined by availability and
    veracity) for sensor data. Traditional signal processing approaches are no longer sufficient, requiring combined approaches in both architectural and analytical layers. This paper proposes a discussion on the adequate foundations of a new
    general approach aimed at increasing robustness and antifragility of IoT-based smart applications. In addition, it shows results of preliminary experiments with real data in the context of precision irrigation using multivariate methods to
    identify relevant situations, such as sensor failures and the mismatch of contextual sensor information due to different spatial granularities capture. Our results provide initial indications of the adequacy of the proposed framework.
    Original languageEnglish
    Title of host publication2019 IEEE Latin-American Conference on Communications (LATINCOM)
    EditorsCarlos A. Gutierrez
    PublisherIEEE Institute of Electrical and Electronic Engineers
    Number of pages6
    ISBN (Electronic)978-1-7281-3955-5
    ISBN (Print)978-1-7281-3956-2
    Publication statusPublished - 2019
    MoE publication typeA4 Article in a conference publication
    EventIEEE Latin-American Conference on Communications - Salvador, Brazil
    Duration: 11 Nov 201913 Nov 2019


    ConferenceIEEE Latin-American Conference on Communications


    • Data quality
    • internet of things
    • precision irrigation
    • smart applications


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