Abstract: Embodiments of the present disclosure provide techniques for motion stabilized touch control. Reference data comprising one or more stabilized positions for one or more touch points corresponding to one or more touch zones associated with a touch screen device may be generated using a motion stabilization model. One or more touch zones may be adjusted based on the stabilized positions by transmitting-computer executable-instructions configured to cause the one or more touch zones to be aligned with the one or more stabilized positions. One or more touch detection models associated with the touch screen device may be updated by tuning the one or more touch detection models to learn the stabilized positions. One or more dimensions of the one or more touch zones may be recalibrated by adjusting a size of at least one of the one or more touch zones.

Abstract: Embodiments of the present disclosure provide techniques for adaptive tuning of motion stabilization models using artificial intelligence. A motion stabilization model for use with a device may be identified. Context data associated with a device may be identified. Metadata comprising one or more model parameters for the motion stabilization model may be identified. Model adjustment data may be generated based on the context data and the metadata by applying the context data and the metadata to a machine learning tuning model. The model adjustment data may be applied to the motion stabilization model to tune the motion stabilization model. The motion stabilization model may be configured to facilitate motion stabilization to account for screen motion of the display of the device and eye motion of a user relative to each other in a vehicle.

Abstract: Embodiments of the present disclosure provide techniques for enhanced motion stabilization in digital platforms. Motion data associated with a user device may be received. Stabilization adjustment data may be generated using a motion stabilization model and based on the motion data. User interface elements associated with a user interface of the user device may be adjusted based on the stabilization adjustment data.

Abstract: Embodiments of the present disclosure provide motion stabilization software development kit and framework. An example motion stabilization software development kit may include a hardware layer that includes a first set of one or more sensors configured for generating device motion data for a display device within a vehicle and a second set of one or more sensors configured for generating vehicle motion data for the vehicle. The example motion stabilization software development kit may include an API layer that includes one or more APIs and an application layer that includes one or more applications communicatively coupled to the first and second set of one or more sensors. The example motion stabilization software development kit may include a software development kit abstraction layer that includes a motion stabilization model configured to adjust a position of an object on a screen of the display device.

Abstract: Systems, apparatuses, methods, and computer program products are provided herein. For example, a method may include includes receiving, from a plurality of sensors of a vehicle, vehicle related motion data. In some embodiments, the method includes identifying vehicle display configuration data. In some embodiments, the method includes generating vehicle display stabilization data by applying the vehicle related motion data to a vehicle display stabilization model. In some embodiments, the method includes generating a plurality of stabilized vehicle interface components based on the vehicle display stabilization data, vehicle display data, and the vehicle display configuration data. In some embodiments, the method includes causing each of the plurality of stabilized vehicle interface components to be rendered to an interface of a corresponding display device.

Abstract: Systems, apparatuses, methods, and computer program products are provided herein. For example, a method may include receiving aviation operations display data associated with an aircraft. In some embodiments, the method includes capturing aviation operations impact data using one or more aircraft components of the aircraft. In some embodiments, the aviation operations impact data is indicative of an aviation instability event. In some embodiments, the method includes generating aviation stability adjustment data by applying the aviation operations impact data to an aviation stability adjustment model. In some embodiments, the method includes generating a stabilized aviation operations interface component based on the aviation stability adjustment data and the aviation operations display data. In some embodiments, the method includes causing the stabilized aviation operations interface component to be rendered to an aviation operations interface of a device.

Abstract: Systems, apparatuses, methods, and computer program products are provided herein. For example, a method may include identifying head mounted display scene data associated with a head mounted display. In some embodiments, the method includes capturing head mounted display motion data using one or more sensing components associated with the head mounted display. In some embodiments, the method includes generating scene stability adjustment data by applying the head mounted display motion data to a scene motion stabilization model. In some embodiments, the method includes generating a stabilized head mounted display scene based on the scene stability adjustment data and the head mounted display scene data. In some embodiments, the method includes causing the stabilized head mounted display scene to be rendered to a head mounted display interface.

Abstract: Systems, apparatuses, methods, and computer program products are provided herein. For example, a method may include receiving, from a wearable device, head motion data. In some embodiments, the method includes generating eye motion data by applying the head motion data to an eye motion determination model. In some embodiments, the method includes detecting device motion data associated with a device. In some embodiments, the method includes generating vehicle related stabilization data by applying the eye motion data and the device motion data to a vehicle related stabilization model. In some embodiments, the method includes generating a stabilized vehicle related interface component based on the vehicle related stabilization data and vehicle related device display data. In some embodiments, the method includes causing the stabilized vehicle related interface component to be rendered to an interface of the device.

Abstract: Techniques for optimizing flight safety operations for an aircraft are described. In operation, aircraft operational parameters corresponding to a plurality of flight operations are retrieved. The aircraft operational parameters are then analyzed using a first machine learning model to identify a first flight operation, where the first flight operation comprises at least one aircraft operational parameter with deviation beyond a threshold. At least one potential flight safety incident corresponding to the first flight operation is then identified using the at least one aircraft operational parameter. The at least one potential flight safety incident is then analyzed using a second machine learning model to identify a corrective action for the potential flight safety incident, where the second machine learning model is trained using flight safety artifacts comprising a plurality of flight safety incidents and corrective actions to be initiated in response to the plurality of flight safety incidents.

Abstract: Techniques for generating flight operation recommendation for an aircraft are described. In operation, a flight safety hazard is detected on a flight path corresponding to a current flight operation of an aircraft. In response, the current flight operation is modified to generate a modified flight operation. A plurality of avionics parameters is then obtained from avionics systems available onboard the aircraft. A variation in the flight safety hazard is then detected based on at least one avionics parameter from the plurality of avionics parameters. Upon ascertaining the variation to be detrimental to the modified flight operation of the aircraft, the plurality of avionics parameters is analysed using a flight operation recommendation model to generate a plurality of flight operation recommendations. A flight operation recommendation from the plurality of flight operation recommendations is then applied to the modified flight operation.

Abstract: Systems are provided for a system of an integrated suite of software applications platform for an aircraft. An applications layer of operational applications for a user that includes a safety application kit provides information about diversions, weather avoidance, and standard operating procedures (SOP) for the aircraft, an efficiency application kit that provides information about short-cuts to a flight plan, flight level advisories, and cost index advisories for the aircraft, an automation application kit that provides information about flight logs, technical logs, checklists, flight planning and flight summary for the aircraft, and a dispatcher application kit that provides information about re-routing advisories, wind status, flight dispatch and following traffic status for the aircraft. The system has a data access layer that provides access to relevant databases in support of the applications layer.

Abstract: A system includes a communication device, a display, an input/output interface, a processing device, and a memory, storing one or more instructions that cause the system to: receive electronic flight book (EFB) selection information for selecting one EFB GUI from a plurality of selectable EFB GUIs that provide an interface for entry and display of flight information; select one EFB GUI from the plurality of selectable EFB GUIs based on the received EFB selection information; display the selected EFB GUI on the display; receive one or more flight parameters from a flight management system (FMS); display one or more of the one or more flight parameters on the displayed EFB GUI; receive one or more changes to the one or more flight parameters via the input/output interface; and update one or more of the one or more flight parameters in the FMS based on the received one or more changes.

Abstract: A system for an aircraft configured to: provide one or more of the sensed aircraft characteristics to a flight planning tool for processing by one or more features of the flight planning tool; receive a recommended flight setting from the flight planning tool based on the processing by the flight planning tool; compare a current flight setting as determined based on the one or more sensed aircraft characteristics from the plurality of sensors with the received recommended flight setting; determine a potential operational efficiency based on the comparison between the received recommended flight setting and the current flight setting; and provide the potential operational efficiency to a user based on an identity of the user.

Abstract: Disclosed are methods, systems, and one or more computer-readable mediums for performing, by one or more processors located off-board a vehicle, operations including receiving, by the fog based application framework before transit of the vehicle, vehicle operation data from a cloud based database of a cloud based computing system; receiving, by the fog based application framework before and/or in real-time during transit of the vehicle, edge-based vehicle data from one or more edge computing devices of the vehicle; and generating, by the fog based application framework during transit of the vehicle, a plurality of vehicle operation insights based on the vehicle operation data and the edge-based vehicle data.

Abstract: Systems and methods for a situation aware edge analytics framework for communication systems. In certain embodiments, a method includes receiving an analytical model from an external server at a mobile edge node. Further, the method includes acquiring situation information for the mobile edge node from at least one component on the mobile edge node. Moreover, the method includes providing the situation information to the analytical model executing on the mobile edge node. Also, identifying a change in one or more communication link states based on an output of the analytical model. Additionally, transmitting the output of the analytical model to the external server. The method also includes receiving an additional analytical model from the external server by the mobile edge node, where the additional analytical model is based on the output of the analytical model.

Abstract: Disclosed are methods, systems, and one or more computer-readable mediums for providing, by an integrated flight deck (IFD) networked computing system, data acquisition for generating a plurality of inflight operation insights, the IFD networked computing system comprising: a presentation platform, a plurality of framework components, a software development kit (SDK) framework, and one or more user interface libraries configured to develop a plurality of applications from the presentation platform and add one or more additional SDKs and/or libraries to the presentation platform; aggregating, by an orchestrator of the SDK framework, a plurality of data sources to fuse data from the plurality of data sources and create a data packet comprising real-time flight data; generating, the plurality of inflight operation insights by analyzing a plurality of key performance indicators of the created data packet; and assessing a flight parameter based on the generated inflight operation insights.