ON-BOARD NETWORKED ANOMALY DETECTION (ONAD) MODULES

Patent №

US 10,587,635

Granted

2020-03-10

Filed 2017

Owner

THE BOEING COMPANY

Lab

AI components

4

ml · kr · planning · hardware

Assignment

Recorded

Dataset

AIPD

2023_r1 edition

Application

15475713

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.

Machine learningKnowledge representationPlanningAI hardwareH04L 63/1425B64D 45/00B64F 5/60G06F 17/11G07C 5/0808G07C 5/085H04L 63/1416B64D 2045/0085+3 more

AI classification

Knowledge representation1.00
Machine learning1.00
Planning0.98
AI hardware0.98
Vision0.40
Natural language0.03
Evolutionary computation0.02
Speech0.00

Ownership

THE BOEING COMPANY

assignment · 418100855

Assignors

KELLER, JASON M., ETHINGTON, JAMES M., STURLAUGSON, LIESSMAN E., BOYD, MARK H.

On an employer assignment, the assignors are typically the inventors.

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