Airline flight departure and arrival prediction based upon historical and real-time data

• US 20020002548A1
• Filed: 02/15/2001
• Published: 01/03/2002
• Est. Priority Date: 02/14/2000
• Status: Abandoned Application

• Current Assignee: Action Engine Corp. (MobUI, Inc.)
• Original Assignee: Action Engine Corp. (MobUI, Inc.)
• Inventors: Roundtree, Brian
• Application Number:
  US09/783,215
• Publication Number:
  US 20020002548A1
• Time in Patent Office: Days
• US Class Current: 707/1
• CPC Class Codes: G06F 16/748 Hypervideo linking data to content, e.g. by linking an URL to a video object in the context of video distribution systems H04N21/858
• CPC Class Codes: G06F 16/94 Hypermedia Hyperlinking G06F40/134
• CPC Class Codes: G06F 16/9537 Spatial or temporal dependent retrieval, e.g. spatiotemporal queries
• CPC Class Codes: G06F 16/9558 Details of hyperlinks; Management of linked annotations
• CPC Class Codes: G06F 16/957 Browsing optimisation, e.g. caching or content distillation
• CPC Class Codes: G06F 16/9577 Optimising the visualization of content, e.g. distillation of HTML documents
• CPC Class Codes: G06Q 10/04 Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem" market predictions or forecasting for commercial activities G06Q30/0202
• CPC Class Codes: G06Q 10/109 Time management, e.g. calendars, reminders, meetings or time accounting
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data
• CPC Class Codes: G06Q 30/0203 Market surveys; Market polls
• CPC Class Codes: G06Q 30/06 Buying, selling or leasing transactions
• CPC Class Codes: G10L 15/26 Speech to text systems G10L15/08 takes precedence
• CPC Class Codes: H04L 67/51 Discovery or management thereof, e.g. service location protocol [SLP] or web services
• CPC Class Codes: H04W 4/12 Messaging; Mailboxes; Announcements
• CPC Class Codes: H04W 8/005 Discovery of network devices, e.g. terminals

Abstract

Use of neural network technology to predict the actual arrival and departure times of scheduled airline flights based upon historical and real-time data. Based upon a scheduled airline flight, the system retrieves historical data related to the flight such as information concerning previous delays involving the same flight or delaying involving the departure and arrival airports. The system also retrieves real-time data that may affect the scheduled flight such as weather information or current news involving flight delays. The historical and real-time data is formatted into structured sets and optionally weighted. A neural network processes the structured historical and real-time data based upon the received flight information and provides predicted actual departure and arrival times along with corresponding confidence levels.

Claims

1. A method for predicting arrival and departure times of scheduled airline flights, comprising:

receiving from a requestor a query relating to a particular scheduled airline flight;

accessing historical data related to the flight;

accessing real-time data related to the flight;

using the historical data and the real-time data to predict actual departure and arrival times related to the flight; and

providing an indication of the predicted actual departure and arrival times.

2. The method of claim 1 wherein the receiving step includes receiving the following information for the flight:

an airline company, an aircraft type, an airport of departure, an airport of arrival, and a current time.

3. The method of claim 1 wherein the accessing the historical data step includes retrieving data from at least one of the following:

a flow control database, a computerized reservation system, a global distribution system, a statistical database relating to airport performance, or a statistical database relating to airline performance.

4. The method of claim 1 wherein the accessing the real-time data step includes retrieving data from at least one of the following:

a news-related database, a weather database, a date database, an airport delays database, or an airline dispatcher database.

5. The method of claim 1, further including updating the historical data.

6. The method of claim 5, further including maintaining the historical data based upon a time parameter.

7. The method of claim 1, further including updating the real-time data.

8. The method of claim 1 wherein:

the using step includes generating a confidence level for the predicted departure and arrival times; and

the providing step includes providing an indication of the confidence level.

9. The method of claim 1 wherein the accessing the real-time data step includes:

constructing search parameters based upon the query;

executing the search parameters within one or more information sources; and

receiving results of the search parameters.

10. The method of claim 1, further including:

receiving raw historical data; and

converting the raw historical data into a structured set of data, according to particular criteria, in order to provide the accessed historical data.

11. The method of claim 1, further including:

receiving raw real-time data; and

converting the raw real-time data into a structured set of data, according to particular criteria, in order to provide the accessed real-time data.

12. The method of claim 1, further including storing the predicated departure and arrival times as part of the historical data.

13. An apparatus for predicting arrival and departure times of scheduled airline flights, comprising:

a receive module for receiving from a requestor a query relating to a particular scheduled airline flight;

an historical module for accessing historical data related to the flight;

a real-time module for accessing real-time data related to the flight;

a use module for using the historical data and the real-time data to predict actual departure and arrival times related to the flight; and

a provide module for providing an indication of the predicted actual departure and arrival times.

14. The apparatus of claim 13 wherein the receive module includes a module for receiving the following information for the flight:

an airline company, an aircraft type, an airport of departure, an airport of arrival, and a current time.

15. The apparatus of claim 13 wherein the historical module includes a module for retrieving data from at least one of the following:

a flow control database, a computerized reservation system, a global distribution system, a statistical database relating to airport performance, or a statistical database relating to airline performance.

16. The apparatus of claim 13 wherein the real-time module includes a module for retrieving data from at least one of the following:

a news-related database, a weather database, a date database, an airport delays database, or an airline dispatcher database.

17. The apparatus of claim 13, further including a module for updating the historical data.

18. The apparatus of claim 17, further including a module for maintaining the historical data based upon a time parameter.

19. The apparatus of claim 13, further including a module for updating the real-time data.

20. The apparatus of claim 13 wherein:

the use module includes a module for generating a confidence level for the predicted departure and arrival times; and

the providing step includes providing an indication of the confidence level.

21. The apparatus of claim 13 wherein the real-time module includes:

a module for constructing search parameters based upon the query;

a module for executing the search parameters within one or more information sources; and

a module for receiving results of the search parameters.

22. The apparatus of claim 13, further including:

a module for receiving raw historical data; and

a module for converting the raw historical data into a structured set of data, according to particular criteria, in order to provide the accessed historical data.

23. The apparatus of claim 13, further including:

a module for receiving raw real-time data; and

a module for converting the raw real-time data into a structured set of data, according to particular criteria, in order to provide the accessed real-time data.

24. The apparatus of claim 13, further including a module for storing the predicated departure and arrival times as part of the historical data.