The Boeing Company

Surya Sundar Raj Durairaj

Tim W Anstey

Ameya Deepak Kamat

Sangeeta Suresh Patro

Rodolfo Acuna Santiago

Bhanu Pratap Singh Thakur

Alyssa Marie De Leon

Arun Ojha

Kyle M Hadley

A method for managing computing resources on a vehicle with line-replaceable units (LRUs) including respective allocated system resources for tasks the LRUs are designed to perform and respective unallocated system resources that are available is provided. Implementations of the method include identifying the LRUs and applying a middleware layer across the LRUs to establish an edge computing infrastructure in which the LRUs operate as edge nodes. The middleware layer receives information from the edge nodes identifying the unallocated system resources and identifies data sources onboard the vehicle, data provided by those sources, and tasks to be performed using the data. The middleware further determines expected operational performance of the edge computing infrastructure and distributes the tasks to be performed across the edge nodes based on the expected operational performance of the edge computing infrastructure.

Distributed edge computing platform for vehicles

An aircraft is configured to perform onboard analytics using available onboard systems. The aircraft comprises a cabin and crew network core with a middleware layer comprising an orchestrator configured to send application containers to a number of cabin and crew network smart members to perform the onboard analytics; and the number of cabin and crew network smart members each having a respective edge member daemon, each edge member daemon configured to place a respective cabin and crew network smart member in a joined state with the middleware layer and release resources of the respective cabin and crew network smart member when it leaves a joined state and enters a busy state so that the edge member daemon does not interfere with a primary function of the respective cabin and crew network smart member.

Onboard analytics system and methods of use

A computing system is provided that implements a system classifier including a first artificial intelligence model configured to classify each of a plurality of elements a computer system into one or more defined security categories, and a threat classifier including a second artificial intelligence model configured to classify each of a plurality of identified cybersecurity threats into the one or more defined security categories. The computing system further includes a threat analyzer configured to perform an analysis of a risk posed by each cybersecurity threat to each element of the target computer system based at least on the security categories of the classified cybersecurity threats and the security categories of classified elements of the target computer system, and output a security recommendation based on the analysis.

Cybersecurity threat modeling and analysis

A landing gear monitoring and alerting system includes a locking pin configured to be inserted into an aperture extending through a linkage of an extended landing gear assembly. When inserted into the aperture, the locking pin inhibits movement of the linkage to establish a locked state of the extended landing gear assembly. This system further includes a magnetic sensor and a communication module. The magnetic sensor is disposed proximate the aperture and is configured to sense a magnetic response indicative of the locking pin being disposed within the aperture. The magnetic sensor is configured to generate a sensor output indicative of the locking pin being disposed within the aperture. The communication module has a transmitter coupled to the magnetic sensor so as to receive the sensor output and is configured to responsively transmit a signal indicative of the locking pin being disposed within the aperture.

Aircraft landing gear monitoring and alerting system and method

A computing system is provided implementing a text miner configured to mine unstructured data from unstructured text sources and extract features of a target computer system, and a data flow diagram editor configured to process the extracted features to identify system elements of the target computer system and interrelationships between the identified system elements, and to identify system-related candidate properties of the system elements, and to populate a system element template for each identified system element with the system-related candidate properties for that element. The data flow diagram editor is configured to generate a data flow diagram for the target computer system comprising each identified system element having the candidate properties adopted according to the system property adoption user input, and is configured to display the generated data flow diagram in the graphical user interface.

Growing community of inventors

Bengaluru, India

Surya Sundar Raj Durairaj