Abstract: Disclosed are methods, systems, and non-transitory computer-readable medium for distributed vehicle processing. For instance, the method may include: in response to determining a first trigger condition of a first set of trigger conditions is satisfied, performing a first process corresponding to the first trigger condition on-board a vehicle; in response to determining a second trigger condition of a second set of trigger conditions is satisfied, prompting a second process corresponding to the second trigger condition by transmitting an edge request to an edge node and receiving an edge response from the edge node; and in response to determining a third trigger condition of a third set of trigger conditions is satisfied, prompting a third process corresponding to the third trigger condition by transmitting a cloud request to a cloud node and receiving a cloud response from the cloud node.

Abstract: Examples for enhancing veracity of data are described herein. Data from a repository may be received based on a data receiving rule. From the received data, a first dataset may be generated using statistical modeling. Also, a first data veracity score for the first dataset is generated which is indicative of a degree of usability of the dataset. Another aspect relates to identifying an anomaly in the first dataset, the corrector, for each anomaly, to identify a correction technique from amongst a plurality of correction techniques. Further, a second dataset is generated using the identified correction technique having second data veracity score higher than the first data veracity score.

Abstract: A system for assessing a data model includes a data receiver, a model receiver, and a model assessment device. The data receiver receives training data, historical data, and production data. The model receiver receives the data model associated with the historical data and trained using the training data. The historical data includes a first outcome of the data model provided based on an input feature in the production data. The model assessment device identifies a key feature in the production data relative to the input feature based on a target category in the historical data and a statistical distribution of the input feature in the production data. The model assessment device determines a second outcome of the data model based on the key feature. In response to the second outcome being different from the first outcome, the model assessment device determines a veracity score for assessing the data model.

Abstract: Examples for enhancing veracity of data are described herein. Data from a repository may be received based on a data receiving rule. From the received data, a first dataset may be generated using statistical modeling. Also, a first data veracity score for the first dataset is generated which is indicative of a degree of usability of the dataset. Another aspect relates to identifying an anomaly in the first dataset, the corrector, for each anomaly, to identify a correction technique from amongst a plurality of correction techniques. Further, a second dataset is generated using the identified correction technique having second data veracity score higher than the first data veracity score.

Abstract: Disclosed are methods, systems, and non-transitory computer-readable medium for distributed vehicle processing. For instance, the method may include: in response to determining a first trigger condition of a first set of trigger conditions is satisfied, performing a first process corresponding to the first trigger condition on-board a vehicle; in response to determining a second trigger condition of a second set of trigger conditions is satisfied, prompting a second process corresponding to the second trigger condition by transmitting an edge request to an edge node and receiving an edge response from the edge node; and in response to determining a third trigger condition of a third set of trigger conditions is satisfied, prompting a third process corresponding to the third trigger condition by transmitting a cloud request to a cloud node and receiving a cloud response from the cloud node.

Abstract: A method and system provide a backup push-to-talk (PTT) function for a transmitter in a stuck microphone condition. The method determines whether a stuck microphone condition exists in the transmitter, and if the stuck microphone condition exists, the method alerts a user that the stuck microphone condition exists. The method then enables a backup PTT interface for the transmitter such that a backup PTT button is available to the user to activate the backup PTT function. The method alerts the user when the backup PTT function is activated, and sends a message to a receiver after the backup PTT button is engaged by the user.

Abstract: A method and system provide a backup push-to-talk (PTT) function for a transmitter in a stuck microphone condition. The method determines whether a stuck microphone condition exists in the transmitter, and if the stuck microphone condition exists, the method alerts a user that the stuck microphone condition exists. The method then enables a backup PTT interface for the transmitter such that a backup PTT button is available to the user to activate the backup PTT function. The method alerts the user when the backup PTT function is activated, and sends a message to a receiver after the backup PTT button is engaged by the user.

Abstract: Systems and methods for context based controller pilot data link communication (CPDLC) are provided. In certain implementations, a method for CPDLC includes receiving data through the selection of a selectable item on a pilot interface, wherein the pilot interface is a non-CPDLC interface and communicating the data to a CPDLC application. Further, the method also includes constructing a CPDLC message based on the data; and transmitting the CPDLC message to an air traffic controller.

Abstract: Systems and methods for context based controller pilot data link communication (CPDLC) are provided. In certain implementations, a method for CPDLC includes receiving data through the selection of a selectable item on a pilot interface, wherein the pilot interface is a non-CPDLC interface and communicating the data to a CPDLC application. Further, the method also includes constructing a CPDLC message based on the data; and transmitting the CPDLC message to an air traffic controller.