The techniques of this disclosure relate to a vehicle occupancy-monitoring system. The system includes a controller circuit that receives occupant data from an occupancy-monitoring sensor of a vehicle. The controller circuit determines an occupancy status of respective seats in a cabin of the vehicle based on the occupancy-monitoring sensor. The controller circuit indicates the occupancy status of the respective seats on a display located in a field of view of occupants of the vehicle. The display is integral to one of a roof light module, a door panel, or a headliner of the cabin. The system can improve passenger safety by alerting the operator and other occupants about the occupancy status of the passengers.

Systems and methods by a telematics server are provided. The method includes receiving, over a network, training data including model input data and a known output label corresponding to the model input data from a first device, training a centralized machine-learning model using the training data, determining, by the centralized machine-learning model, an output label prediction certainty based on the model input data, determining an increase in the output label prediction certainty over a prior predicted output label certainty of the centralized machine-learning model, and sending, over the network, a machine-learning model update to a second device in response to determining that the increase in the output label prediction certainty is greater than an output label prediction increase threshold.

The techniques of this disclosure relate to a vehicle occupancy-monitoring system. The system includes a controller circuit that receives occupant data from an occupancy-monitoring sensor of a vehicle. The controller circuit determines an occupancy status of respective seats in a cabin of the vehicle based on the occupancy-monitoring sensor. The controller circuit indicates the occupancy status of the respective seats on a display located in a field of view of occupants of the vehicle. The display is integral to one of a roof light module, a door panel, or a headliner of the cabin. The system can improve passenger safety by alerting the operator and other occupants about the occupancy status of the passengers.

Disclosed is a base unit including a video link hub electrically connected to a user interface device to transmit a signal, a first system-on-chip (SoC) configured to provide a first infotainment function, and a processor configured to determine whether the first SoC is operating abnormally. When a second SoC is powered on, the first SoC performs authentication with respect to the second SoC, and when the processor determines that the first SoC is operating normally, the first SoC generates a first execution signal for display of a composite infotainment function, obtained by combining the first infotainment function with a second infotainment function provided by the second SoC, on the user interface device, and transmits the first execution signal to the video link hub, and the processor controls the video link hub to transmit the first execution signal to the user interface device.

Systems, methods, and non-transitory media are provided for a vehicle and mobile device interface for vehicle occupant assistance. An example method can include determining, based on one or more images of an interior portion of a vehicle, a pose of a mobile device relative to a coordinate system of the vehicle; determine a state of an occupant of the vehicle;

and send, to the vehicle, data indicating the state of the occupant and the pose of the mobile device relative to the coordinate system of the vehicle.

Systems and methods by a telematics server are provided. The method includes receiving, over a network, training data including model input data and a known output label corresponding to the model input data from a first device, training a centralized machine-learning model using the training data, determining, by the centralized machine-learning model, an output label prediction certainty based on the model input data, determining an increase in the output label prediction certainty over a prior predicted output label certainty of the centralized machine-learning model, and sending, over the network, a machine-learning model update to a second device in response to determining that the increase in the output label prediction certainty is greater than an output label prediction increase threshold.

A vehicle is provided with a button that is depressed by a driver at any time for inputting intention information indicating an intention of approving a condition or an intention of rejecting the condition. The intention information inputted by the depressing operation of the button is transmitted to an information providing center. The intention information is transmitted together with position information indicating a point where the button is depressed and time information indicating a time. In the center, a server provides related information related to the transmitted intention information as a feedback. The server also supposes the reason why the transmitted intention information is inputted, and transmits the supposed reason to a closed SNS or an open SNS with a response form. The server then determines a reason of input based upon a response in accordance with the response form, and accumulates the determined reason in an information storage section so as to be retrievable in association with the intention information.

Various aspects of a device and method to manage interaction with one or more control circuits in a vehicle and one or more wearable devices are disclosed herein. The device comprises one or more circuits configured to receive a first set of input values from the one or more wearable devices associated with a first user. The one or more wearable devices are communicatively coupled to the device used in the vehicle. A second set of input values is received from one or more vehicle sensors embedded in the vehicle. An operating mode of the device is determined based on the received first set of input values and the second set of input values. One or more functions of the vehicle are controlled based on the determined operating mode of the device.

Embodiments are directed towards providing a dynamic application environment where separate components of an application can execute on separate processing hardware at any given point in time. A host device monitors current operating characteristics associated with a computing device, such a head unit of an automobile, and based on those characteristics selects which components of one or more applications to execute on the computing device and which components to execute on the host device, if any. The host device provides the selected components to the computing device for execution by the computing device and the host device executes any other components that are not executed by the computing device. The host device monitors the current operating characteristics associated with the computing device, and modifies the selection of which components are executing on which device based on changes in current operating characteristics.

A method and system couples a first user interface with a second user interface. The first user interface is implemented in the form of a mobile terminal or one or more back-end components. The second user interface is implemented in the form of a control device of a vehicle. The method includes the steps of: registering one or more elements of the first user interface; determining one or more display elements based on first heuristics and the one or more elements, wherein the one or more display elements are configured to reproduce at least one portion of the one or more elements; and displaying the one or more display elements on the second user interface. The system has the control device and/or the one or more back-end components, wherein the control device and/or the one or more back-end components are configured to carry out the method.