With the advent of connected cars and smart transportation, vehicles are being seamlessly integrated with the daily routine of passengers. As an extension to this, we aim to provide on-the- go personalization of vehicle-feature settings and enable cloud-based passenger-vehicle connectivity. This calls for both passenger identification and in-vehicle localization of the passenger. In this paper, we propose a novel passenger identification and localization system, specifically tuned for a vehicularenvironment,usinglowcostBluetoothlowenerg ybased beacons. A communication device functioning on passenger end is used to constantly monitor the Received Signal Strength Index (RSSI) from a set of wireless beacons fixed inside a vehicle. These RSSI values are exploited to locate the passenger and intimate the cloud to provide personalized feature settings. We propose proximity based and machine learning based localization techniques and analyze their performance. Also, we conduct an exhaustive experimental analysis to arrive at an optimum placement of beacons and present a demonstration of in-vehicle personalization with a real-time use case.


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    Titel :

    Passenger Localization for In-Vehicle Personalization Using BLE Beacons


    Beteiligte:
    Emmanuel, Robin (Autor:in) / Das, Anjana P. (Autor:in) / B., Sandhya (Autor:in) / Thomas, Melbin (Autor:in) / Tripathi, Anshul (Autor:in)


    Erscheinungsdatum :

    01.06.2018


    Format / Umfang :

    1730095 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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