Enhancing Veracity of IoT Generated Big Data in Decision Making

Xiaoli Liu, Satu Tamminen, Xiang Su, Pekka Siirtola, Juha Röning, Jukka Riekki, Jussi Kiljander, Juha Pekka Soininen

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

    1 Citation (Scopus)

    Abstract

    Data are crucial to support decision making. If data have low veracity, decisions are not likely to be sound. Internet of Things (IoT) generates big data with inaccuracy, inconsistency, incompleteness, deception, and model approximation. Enhancing data veracity is important to address these challenges. In this article, we summarize the key characteristics and challenges of IoT, which influence data processing and decision making. We review the landscape of measuring and enhancing data veracity and mining uncertain data streams. Moreover, we propose five recommendations for future development of veracious big IoT data analytics that are related to the heterogeneous and distributed nature of IoT data, autonomous decision-making, context-aware and domain-optimized methodologies, data cleaning and processing techniques for IoT edge devices, and privacy preserving, personalized, and secure data management.

    Original languageEnglish
    Title of host publication2018 IEEE International Conference on Pervasive Computing and Communications Workshops
    Subtitle of host publicationPerCom Workshops 2018
    PublisherIEEE Institute of Electrical and Electronic Engineers
    Pages149-154
    Number of pages6
    ISBN (Electronic)978-1-5386-3227-7, 978-1-5386-3226-0
    ISBN (Print)978-1-5386-3227-7
    DOIs
    Publication statusPublished - 8 Oct 2018
    MoE publication typeNot Eligible
    EventIEEE International Conference on Pervasive Computing and Communications Workshops, PerCom 2018 - Athens, Greece
    Duration: 19 Mar 201823 Mar 2018

    Workshop

    WorkshopIEEE International Conference on Pervasive Computing and Communications Workshops, PerCom 2018
    Abbreviated titlePerCom 2018
    CountryGreece
    CityAthens
    Period19/03/1823/03/18

    Fingerprint

    Decision making
    Information management
    Cleaning
    Big data
    Internet of things
    Acoustic waves
    Processing

    Keywords

    • big data
    • decision making
    • data mining
    • data models
    • internet of things
    • data analysis

    Cite this

    Liu, X., Tamminen, S., Su, X., Siirtola, P., Röning, J., Riekki, J., ... Soininen, J. P. (2018). Enhancing Veracity of IoT Generated Big Data in Decision Making. In 2018 IEEE International Conference on Pervasive Computing and Communications Workshops: PerCom Workshops 2018 (pp. 149-154). [8480371] IEEE Institute of Electrical and Electronic Engineers . https://doi.org/10.1109/PERCOMW.2018.8480371
    Liu, Xiaoli ; Tamminen, Satu ; Su, Xiang ; Siirtola, Pekka ; Röning, Juha ; Riekki, Jukka ; Kiljander, Jussi ; Soininen, Juha Pekka. / Enhancing Veracity of IoT Generated Big Data in Decision Making. 2018 IEEE International Conference on Pervasive Computing and Communications Workshops: PerCom Workshops 2018. IEEE Institute of Electrical and Electronic Engineers , 2018. pp. 149-154
    @inproceedings{a5ad106ca8cd4935b4d810ec8b7e568f,
    title = "Enhancing Veracity of IoT Generated Big Data in Decision Making",
    abstract = "Data are crucial to support decision making. If data have low veracity, decisions are not likely to be sound. Internet of Things (IoT) generates big data with inaccuracy, inconsistency, incompleteness, deception, and model approximation. Enhancing data veracity is important to address these challenges. In this article, we summarize the key characteristics and challenges of IoT, which influence data processing and decision making. We review the landscape of measuring and enhancing data veracity and mining uncertain data streams. Moreover, we propose five recommendations for future development of veracious big IoT data analytics that are related to the heterogeneous and distributed nature of IoT data, autonomous decision-making, context-aware and domain-optimized methodologies, data cleaning and processing techniques for IoT edge devices, and privacy preserving, personalized, and secure data management.",
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    author = "Xiaoli Liu and Satu Tamminen and Xiang Su and Pekka Siirtola and Juha R{\"o}ning and Jukka Riekki and Jussi Kiljander and Soininen, {Juha Pekka}",
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    Liu, X, Tamminen, S, Su, X, Siirtola, P, Röning, J, Riekki, J, Kiljander, J & Soininen, JP 2018, Enhancing Veracity of IoT Generated Big Data in Decision Making. in 2018 IEEE International Conference on Pervasive Computing and Communications Workshops: PerCom Workshops 2018., 8480371, IEEE Institute of Electrical and Electronic Engineers , pp. 149-154, IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom 2018, Athens, Greece, 19/03/18. https://doi.org/10.1109/PERCOMW.2018.8480371

    Enhancing Veracity of IoT Generated Big Data in Decision Making. / Liu, Xiaoli; Tamminen, Satu; Su, Xiang; Siirtola, Pekka; Röning, Juha; Riekki, Jukka; Kiljander, Jussi; Soininen, Juha Pekka.

    2018 IEEE International Conference on Pervasive Computing and Communications Workshops: PerCom Workshops 2018. IEEE Institute of Electrical and Electronic Engineers , 2018. p. 149-154 8480371.

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

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    AU - Tamminen, Satu

    AU - Su, Xiang

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    AU - Röning, Juha

    AU - Riekki, Jukka

    AU - Kiljander, Jussi

    AU - Soininen, Juha Pekka

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    AB - Data are crucial to support decision making. If data have low veracity, decisions are not likely to be sound. Internet of Things (IoT) generates big data with inaccuracy, inconsistency, incompleteness, deception, and model approximation. Enhancing data veracity is important to address these challenges. In this article, we summarize the key characteristics and challenges of IoT, which influence data processing and decision making. We review the landscape of measuring and enhancing data veracity and mining uncertain data streams. Moreover, we propose five recommendations for future development of veracious big IoT data analytics that are related to the heterogeneous and distributed nature of IoT data, autonomous decision-making, context-aware and domain-optimized methodologies, data cleaning and processing techniques for IoT edge devices, and privacy preserving, personalized, and secure data management.

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    KW - decision making

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    Liu X, Tamminen S, Su X, Siirtola P, Röning J, Riekki J et al. Enhancing Veracity of IoT Generated Big Data in Decision Making. In 2018 IEEE International Conference on Pervasive Computing and Communications Workshops: PerCom Workshops 2018. IEEE Institute of Electrical and Electronic Engineers . 2018. p. 149-154. 8480371 https://doi.org/10.1109/PERCOMW.2018.8480371