Granted Patent B2

US 12,694,793 · App. 18/479,883 · Granted Jul 28, 2026

Inventors: Milind Vasudeo Naik (Frankfurt am Main, DE); Pablo Costas Álvarez (Majadahonda, ES)

Assignee: Jeppesen ForeFlight, Inc.

G08G5/50G06F16/258G08G5/20G08G5/34G08G5/55

Abstract

Claims (70)

1 . A method for automated distribution of aeronautical information, the method comprising:

identifying a source dataset for the aeronautical information, wherein the source dataset is in a common data format and has changes;

identifying a destination dataset for the aeronautical information, wherein the destination dataset is in the common data format;

determining an overlap between the source dataset and the destination dataset;

identifying the changes present in the overlap between the source dataset and the destination dataset;

identifying the changes in the source dataset, wherein identifying the changes comprises:

creating a source tree for source features in the source dataset in the common data format,

creating a baseline tree for baseline features in a baseline dataset in the common data format,

comparing nodes between the source tree and the baseline tree to form a comparison, and

determining the changes in the source features in the source dataset and the baseline features in the baseline dataset based on the comparison;

generating a destination change dataset in a destination format specific to the destination dataset, wherein the destination change dataset comprises the changes present in the overlap; and

sending the destination change dataset in the destination format to a destination database storing the destination dataset in the destination format.

2 . The method of claim 1 , further comprising:

updating the destination dataset in the destination database using the destination change dataset in the destination format.

3 . The method of claim 1 , further comprising:

generating a change report identifying the changes for the destination dataset in the destination database.

4 . The method of claim 1 , wherein determining the overlap comprises:

determining the overlap between source features in the source dataset and destination features in the destination dataset.

5 . The method of claim 1 , wherein determining the overlap comprises:

receiving the source dataset in a source format;

converting the source dataset from the source format to the common data format;

converting the destination dataset from the destination format to the common data format; and

comparing the source dataset in the common data format to the destination dataset in the common data format to determine the overlap between the source dataset and the destination dataset.

6 . The method of claim 1 , wherein comparing the nodes comprises:

comparing the nodes between the source tree and the baseline tree using a comparison system selected from at least one of a machine learning model, genetic algorithm, and a hash comparison process to form the comparison.

7 . The method of claim 1 , wherein the common data format is a common extensible markup language schema and the destination format is a destination extensible markup language schema.

8 . The method of claim 1 , wherein a source format is based on an implementation of a model selected from a group comprising an Aeronautical Information Exchange Model, a Flight Information Exchange Model (FIXM), and an International Civil Aviation Organization Meteorological Information Exchange model (IWXXM).

9 . The method of claim 1 , wherein the destination database is selected from one of an aviation database, a chart database, a pilot operation manual database, and an airport mapping database.

10 . A change detection system comprising:

a computer system; and

a change detector configured to:

identify a source dataset for aeronautical information, wherein the source dataset is in a common data format and has changes;

identify a destination dataset for the aeronautical information, wherein the destination dataset is in the common data format;

determine an overlap between the source dataset and the destination dataset;

identify the changes present in the overlap between the source dataset and the destination dataset;

identify the changes in the source dataset, wherein identifying the changes comprises:

creating a source tree for source features in the source dataset in the common data format,

creating a baseline tree for baseline features in a baseline dataset in the common data format,

comparing nodes between the source tree and the baseline tree to form a comparison, and

determining the changes in the source features in the source dataset and the baseline features in the baseline dataset based on the comparison,

generate a destination change dataset in a destination format specific to the destination dataset, wherein the destination change dataset comprises the changes present in the overlap; and

send the destination change dataset in the destination format to a destination database storing the destination dataset in the destination format.

11 . The change detection system of claim 10 , Wherein the change detector is configured to:

update the destination dataset in the destination database using the destination change dataset in the destination format.

12 . The change detection system of claim 10 , the change detector is configured to:

generate a change report identifying the changes for the destination dataset in the destination database.

13 . The change detection system of claim 10 , wherein in determining the overlap, the change detector is configured to:

determine the overlap between source features in the source dataset and destination features in the destination dataset.

14 . The change detection system of claim 10 , wherein in determining the overlap, the change detector is configured to:

receive the source dataset in a source format;

convert the source dataset from the source format to the common data format;

convert the destination dataset from the destination format to the common data format; and

compare the source dataset in the common data format to the destination dataset in the common data format to determine the overlap between the source dataset and the destination dataset.

15 . The change detection system of claim 10 , wherein in comparing the nodes, the change detector is configured to:

compare the nodes between the source tree and the baseline tree using a comparison system selected from at least one of a machine learning model, genetic algorithm, and a hash comparison process to form the comparison.

16 . The change detection system of claim 10 , wherein the common data format is a common extensible markup language schema and the destination format is a destination extensible markup language schema.

17 . The change detection system of claim 10 , wherein a source format is based on an implementation of a model selected from a group comprising an Aeronautical Information Exchange Model, a Flight Information Exchange Model (FIXM), and an International Civil Aviation Organization Meteorological Information Exchange model (IWXXM).

18 . The change detection system of claim 10 , wherein the destination database is selected from one of an aviation database, a chart database, a pilot operation manual database, and an airport mapping database.

19 . A computer program product for automated distribution of aeronautical information, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a computer system to cause the computer system to:

identify a source dataset for the aeronautical information, wherein the source dataset is in a common data format and has changes;

identify a destination dataset for the aeronautical information, wherein the destination dataset is in the common data format;

determine an overlap between the source dataset and the destination dataset;

identify the changes present in the overlap between the source dataset and the destination dataset;

identify the changes in the source dataset, wherein identifying the changes comprises:

creating a source tree for source features in the source dataset in the common data format,

creating a baseline tree for baseline features in a baseline dataset in the common data format,

comparing nodes between the source tree and the baseline tree to form a comparison, and

determining the changes in the source features in the source dataset and the baseline features in the baseline dataset based on the comparison;

generate a destination change dataset in a destination format specific to the destination dataset, wherein the destination change dataset comprises the changes present in the overlap; and

send the destination change dataset in the destination format to a destination database storing the destination dataset in the destination format.

Assignments (4)

Priority Claims (1)

Continuity (2)

References Cited (11)