Abstract: An aircraft-based system and method for automated reporting and logging of aircraft maintenance events receives flight deck effects (FDEs) with correlated maintenance messages indicating maintenance statuses (e.g., faults and/or failures) and/or Air Transport Association (ATA) classifications for each reporting aircraft system, subsystem or component. The logging system generates event messages based on each received FDE, predicting additional information based on the correlated maintenance message such as recommended maintenance actions, replacement parts or components, and/or Minimum Equipment List (MEL) actions associated with a component fault or failure. Event messages are automatically transmitted via datalink to ground-based maintenance and dispatch. Further, event messages are automatically logged to an aircraft maintenance log.

Abstract: A system and method for sensor quality detection continuously monitors a context (vehicle state, proximal environmental factors, surrounding environmental conditions) surrounding a vehicle as well as actual sensor output. The system compares actual sensor output with expected sensor output to determine if the sensor has become degraded or if the degradation is due to the surrounding context. Once the system determines the context-based or actual degradation, it determines if the sensor is able to complete an assigned tasking with the degradation within the specific mission-based requirements of the sensor. Should the degraded sensor be unable to complete the task, the system transfers the tasking to a second vehicle equipped with an operational sensor.

Abstract: A system and method for automation of flight functions across an aircraft cockpit provides an open systems architecture to meet next generation mission capabilities for increased aircrew effectiveness. A mission reasoner (MR) receives inputs from a vehicle health system, mission phase analysis, and external assets (wingmen) to build a decision network based on a knowledge database providing a decision aid to automate flight functions across the cockpit. The MR reduces crew workload by providing an automated decision aid and increased situational awareness of own ship aircraft and cooperating nearby vehicle health status relating to a phase of mission success. The MR provides predictive decisions and alternative actions to complete one or more desired mission objectives and determines predictive maintenance and future failures to optimize condition-based maintenance and reduce cost.

Abstract: A system and method for automated video generation for training machine and deep learning algorithms in aviation environments generates photorealistic digital human characters and an aviation environment according to a desired scenario, including fixtures, free objects, lighting and physics configurations, and camera views. Character actions in the desired scenario are mapped to pose sequences which may be manually generated or transferred from image sequences of human activities, including both main character activities specified by the scenario, characters responding to the main characters, and background character actions. A video automation pipeline animates character actions performed by the digital human characters into video datasets with annotation files incorporating detailed pixel and depth information for each frame. Video datasets may include variant video datasets differentiated from the primary dataset by changes in domain variants (e.g.

Abstract: A pilot, commander, or user within an aircraft may ask a query via voice. The query may be converted into text and used to search a knowledge graph. The result from the query may be provided to the user such that the user may obtain improved situational awareness during a mission or otherwise while flying. A line-replaceable unit of the aircraft may execute an architecture for searching the knowledge graph. The knowledge graph may include a schema based, at least in part, on a mission requirement of an aircraft and one or more aircraft systems of the aircraft. Thus, the user may ask for the effect of various sensors or components of the aircraft systems as it relates to the mission.

Abstract: Information regarding flight schedules, available aircraft, and maintenance information is received from one or more systems. A graph database is generated based on the received information. A graph traversal algorithm is applied to the graph database to determine an assignment of the available aircraft to the flight schedules based on reducing a risk of aircraft-on-ground at a remote location, reducing actual costs, or reducing a time cost.

Abstract: A system and method for sensor quality detection continuously monitors a context (vehicle state, proximal environmental factors, surrounding environmental conditions) surrounding a vehicle as well as actual sensor output. The system compares actual sensor output with expected sensor output to determine if the sensor has become degraded or if the degradation is due to the surrounding context. Once the system determines the context-based or actual degradation, it determines if the sensor is able to complete an assigned tasking with the degradation within the specific mission-based requirements of the sensor. Should the degraded sensor be unable to complete the task, the system transfers the tasking to a second vehicle equipped with an operational sensor.

Abstract: A system and method for automation of flight functions across an aircraft cockpit provides an open systems architecture to meet next generation mission capabilities for increased aircrew effectiveness. A mission reasoner (MR) receives inputs from a vehicle health system, mission phase analysis, and external assets (wingmen) to build a decision network based on a knowledge database providing a decision aid to automate flight functions across the cockpit. The MR reduces crew workload by providing an automated decision aid and increased situational awareness of own ship aircraft and cooperating nearby vehicle health status relating to a phase of mission success. The MR provides predictive decisions and alternative actions to complete one or more desired mission objectives and determines predictive maintenance and future failures to optimize condition-based maintenance and reduce cost.

Abstract: A method includes displaying content including an environment, a user entity, and a synthetic entity. The user entity is controllable by a user with respect to the environment and the synthetic entity. The environment and the synthetic entity operate according to a pre-scripted scheme. The method further includes receiving user information. The user information is at least one of a user input and a current physiological state of the user. The method further includes modifying the pre-scripted scheme based on the user information and prior user information. The prior user information comprises at least one of a prior user input and a prior physiological state of the prior user received in response to an interaction of the prior user with the pre-scripted scheme.

Abstract: A system and method are provided for tracking access. At least one passive wireless identification device is provided at a personnel access point. Communication is established between a mobile device and the at least one passive wireless identification device when the mobile device passes the personnel access point. Occurrences of the established communication between the mobile device and the at least one passive wireless identification device are separately communicated to a remote data collection device. The occurrences of the established communication between the mobile device and the at least one passive wireless identification device are recorded in the remote data collection device. Data based on the recorded occurrences of the established communication between the mobile device and the at least one passive wireless identification device is output from the remote data collection device.