Bluetooth has, in recent years, gained more and more momentum. New commodity objects and wearables implementing Bluetooth Smart technology (Low Energy) are released everyday. In particular, the ever increasing number of discoverable devices both inside and outside a populated area gives us an encouraging insight on future research directions for this technology. In this paper, based on a sensing system developed as an Android application, we evaluate Bluetooth Classic and Low Energy discovery characteristics from a vehicular perspective. By recording information about devices nearby (e.g. the number of discovered devices, their signal strength, manufacturer information) and the GPS location we can derive interesting information about a driver's situation, as well as his/her environment. Presented results indicate that the amount of discovered devices and signal strengths are dependent on velocity and road category. Finally, future work and discussions address potential use-case applications based only on Bluetooth discovery, such as low energy and privacy friendly road and traffic context awareness. The sensing system used in this article is free online under the MIT License.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Towards characterizing Bluetooth discovery in a vehicular context


    Contributors:


    Publication date :

    2016-12-01


    Size :

    1930677 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Bluetooth low energy for inter-vehicular communications

    Bronzi, Walter / Frank, Raphael / Castignani, German et al. | IEEE | 2014


    Towards Semantic Object Discovery for Vehicular Named Data Networks

    Grewe, Dennis / Wagner, Marco / Schildt, Sebastian et al. | IEEE | 2018


    Characterizing Travel Time Variability in Vehicular Traffic Networks

    Mahmassani, Hani S. / Hou, Tian / Dong, Jing | Transportation Research Record | 2012


    Simulation Model of Bluetooth Passive Scanning for Vehicular Traffic Monitoring

    Boudabous, Safa / Garbiso, Julian / Ali, Shabbir et al. | IEEE | 2020


    Context based vehicular traffic prediction

    WANG ZHI HU / ZHAO SHIWAN / LIU JING LAN et al. | European Patent Office | 2023

    Free access