In the past years, the automotive industry has been integrating multiple hardware in the vehicle to enable new features and applications. In particular automotive applications, it is important to monitor the actions and behaviors of drivers and passengers to promote their safety and track abnormal situations such as social disorders or crimes. These applications rely on multiple sensors that generate real-time data to be processed, and thus, they require adequate data acquisition and analysis systems. This article proposes a prototype to enable in-vehicle data acquisition and analysis based on the middleware framework Robot Operating System (ROS). The proposed prototype features two processing devices and enables synchronized audio and video acquisition, storage, and processing. It was assessed through the implementation of a live inference system consisting of a face detection algorithm from the data gathered from the cameras and the microphone. The proposed prototype inherits the flexibility of the ROS framework and has a modular and scalable design; thus, more sensors, processing devices, and applications can be deployed.


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    Title :

    A Robot Operating System Based Prototype for In-Vehicle Data Acquisition and Analysis


    Additional title:

    Sae Int. J. Commer. Veh


    Contributors:


    Publication date :

    2021-11-10


    Size :

    10 pages




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




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