An aggregation and visualization technique for crowd-sourced continuous monitoring of transport infrastructures

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    Abstract

    Smartphones have revolutionized the way infrastructure health monitoring applications operate. Their ubiquitous sensing and communication capabilities have made measurement data for infrastructural health monitoring applications easily available. They, however, also introduced a new challenge, namely the huge amount of data that is generated. This new reality prompts the need for efficient techniques to handle, process, aggregate, and visualize this huge amount of streaming data.
    Original languageEnglish
    Title of host publication2017 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2017
    Place of PublicationPiscataway, NJ
    PublisherIEEE
    Pages219-224
    Number of pages6
    ISBN (Print)9781509043385
    DOIs
    Publication statusPublished - 2 May 2017
    EventIEEE International Conference on Pervasive Computing and Communications, PerCom 2017 - Kona, Big Island, United States
    Duration: 13 Mar 201717 Mar 2017
    http://www.percom.org/Previous/ST2017/

    Conference

    ConferenceIEEE International Conference on Pervasive Computing and Communications, PerCom 2017
    Abbreviated titlePerCom
    CountryUnited States
    CityKona, Big Island
    Period13/03/1717/03/17
    Internet address

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    Keywords

    • Computational geometry
    • Crowd-sensing
    • Delaunay Triangulation
    • Infrastructure health monitoring
    • Map generation
    • Map-matching
    • Predictive maintenance

    Cite this

    Seraj, F., Meratnia, N., & Havinga, P. J. M. (2017). An aggregation and visualization technique for crowd-sourced continuous monitoring of transport infrastructures. In 2017 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2017 (pp. 219-224). Piscataway, NJ: IEEE. https://doi.org/10.1109/PERCOMW.2017.7917561