The data displayed in the airVentDisplay are only a snapshot of the current state, meant to give indications to the driver. It is not before one are able to look at all the data in a broader context that the full learning can take place. Hence, the effort of streaming the CAN data to the cloud. There are so many providers within the fild of IOT which offers solutions for streaming data. In order to keep the costs at a minimum as well as to test an easy but powerful solution, the service offered from Initial State was selected. A RaspberryPi 3 is attached to the CAN network and streams the data via 4G to the Initial State servers. A multi threaded C++ program is made for the RPi, which collect the CAN data at 100ms intervals as well as the GPS coordinates and streams the buffered data to the cloud at 2s intervals. By this, the data (with 100ms resolution) is easily available by any web browser in near real tim as well as available for analysis after each trackday heat.