Abstract: Methods, systems, and devices for video stream augmentation using a deep learning device are described. A machine learning device of a vehicle may augment a video stream received from cameras of the vehicle and may output the augmented video stream to a display component of the vehicle. For example, a camera of the vehicle may record a video stream of and a sensor of the vehicle may detect information about an environment associated with the vehicle. The camera and sensor may transmit the video stream and information, respectively, to the machine learning device, which may process and modify the video stream based on parameters of the video stream and/or the information. The machine learning device may transmit the modified video streams to the display component, and the display component may display aspects of the modified video stream on a display of the vehicle, such as a rearview mirror.

Abstract: Methods, systems, and devices for security configurations for zonal computing architecture are described. A zonal computing system in a vehicle may be associated with multiple zones. The zonal computing system may include devices (e.g., sensors, actuators) that interact with the vehicle or an environment associated with the vehicle. A memory system included in the zonal computing system may authenticate whether a device associated with a zone is a trusted device and enable or restrict communications with the device based on the authentication. For example, the zonal computing system may include a central processor that communicates with a remote server and the multiple zones and may include a gateway processor coupled with the central processor and the device and associated with the zone. Based on whether the device is trusted, the memory system may enable or restrict communications between the central processer and the device and routed through the gateway processor.