The Boeing Company

Mark H Boyd

Liessman E Sturlaugson

James M Ethington

Jason M Keller

William J Wood

Melanie K Lorang

Richard A Eith

Leah T Chatkeonopadol

David H Kusuda

Jeffery M Bearce

A cognitive assistant that allows a maintainer to speak to an application using natural language is disclosed. The maintainer can quickly interact with an application hands-free without the need to use complex user interfaces or memorized voice commands. The assistant provides instructions to the maintainer using augmented reality audio and visual cues. The assistant will walk the maintainer through maintenance tasks and verify proper execution using IoT sensors. If after completing a step, the IoT sensors are not as expected, the maintainer is notified on how to resolve the situation.

System and method for interactive cognitive task assistance

Method and apparatus for detecting anomalous flights. Embodiments collect sensor data from a plurality of sensor devices onboard an aircraft during a flight. Feature definitions are determined, specifying a sensor device and an algorithm for deriving data values from sensor data collected from the device. Embodiments determine whether anomalous activity occurred during the flight using an anomaly detection model. An anomaly is detected including at least one of (i) a contextual anomaly where a data instance of a plurality of data instances is anomalous relative to a specific context, or (ii) a collective anomaly where two or more data instances are anomalous relative to a remainder of the plurality of data instances, even though each of the two or more data instances is not anomalous in and of itself. A report specifying a measure of the anomalous activity for the flight is generated.

On-board networked anomaly detection (ONAD) modules

System, methods, and computer program products providing an information asset management system including an information asset registry that stores metadata of information assets and having a logical structure that lineally links information assets. The logical structure includes data structures having a logical element comprising an identifier identifying an information asset, logical elements including metadata of the information asset, and logical elements including lineage information that relates the information asset to other information assets. The program instructions cause the information asset management to perform operations including receiving a query for information describing a first information asset. The operations also include determining lineal links between the first information asset and other information assets. The operations further include retrieving the metadata of the first in formation asset and the information assets. The operations further include providing a result based on the metadata of on the first information asset and the other information asset.

Lineal data storage and retrieval system

Method and apparatus for detecting anomalous flights. Embodiments collect sensor data from a plurality of sensor devices onboard an aircraft during a flight. A plurality of feature definitions are determined, where a first one of the feature definitions specifies one or more of the plurality of sensor devices and an algorithm for deriving data values from sensor data collected from the one or more sensor devices. Embodiments determine whether anomalous activity occurred during the flight using an anomaly detection model, where the anomaly detection model describes a pattern of normal feature values for at least the feature definition, and comprising comparing feature values calculated from the collected sensor data with the pattern of normal feature values for the first feature definition. A report specifying a measure of the anomalous activity for the flight is generated.

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Redondo Beach, CA, United States of America

Mark H Boyd