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.
