Use of peer maintained file to improve beacon position tracking utilizing spatial probabilities

• US 8,393,532 B2
• Filed: 06/30/2006
• Issued: 03/12/2013
• Est. Priority Date: 06/30/2006
• Status: Expired due to Fees

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Cato, Robert Thomas, Zimmerman, Thomas Guthrie
• Primary Examiner(s): Lee, Michael G
• Assistant Examiner(s): Gudorf, Laura
• Application Number:
  US11/427,939
• Publication Number:
  US 20080000961A1
• Time in Patent Office: 2,447 Days
• Field of Search: 235/375, 235/449, 235/492, 235/376, 340/10.1, 340/539.13, 342385-386
• US Class Current: 235/376
• CPC Class Codes: G01S 5/0027 of actual mobile position, i.e. position determined on mobile
• CPC Class Codes: G01S 5/0045 Transmission from base station to mobile station G01S5/009 takes precedence
• CPC Class Codes: G01S 5/0294 Trajectory determination or predictive filtering, e.g. target tracking or Kalman filtering

Abstract

A method for improving position beacon tracking using spatial probabilities is provided. A beacon identity recognition device receives a central probability file from a remote data processing system to form a local probability file. The device receives a current position beacon identity. The device compares current position beacon identity to a previous beacon identity stored in the local probability file to form a comparison. The device determines if the current position beacon identity is valid based on the comparison. The device transmits a valid position beacon identity to the remote data processing system. The device updates the local probability file and then combines a weighted version of the local probability file with a new copy of the probability file from the remote data processing system to form a combined probability file. The combined probability file is then sent to the remote data processing system and replaces the existing probability file.

Claims

1. A computer implemented method for improving position beacon tracking using spatial probabilities, the computer implemented method comprising:

a computer receiving a copy of a central probability file from a remote data processing system to form a local probability file;

the computer receiving a current position beacon identity;

the computer checking the local probability file to find an entry for a previously received position beacon identity;

the computer, responsive to finding the entry for the previously received position beacon identity, finding a sub-entry for the current position beacon identity in a previously received position beacon identity;

the computer, responsive to finding the sub-entry, determining a number of occurrences for the current position beacon identity;

the computer comparing the number of occurrences for the current position beacon identity to a maximum number of occurrences for the previously received position beacon identity;

the computer, responsive to determining that the number of occurrences of the current position beacon identity is within a range of a maximum number of occurrences for the previously received position beacon identity, determining that the currently received position beacon identity is valid;

the computer, responsive to determining that the currently received position beacon identity is valid, updating the local probability file to form an updated local probability file;

the computer receiving a new copy of the central probability file from the remote data processing system;

the computer combining the updated local probability file with the new copy of the central probability file to form an updated central probability file; and

the computer transmitting the updated central probability file to the remote data processing system.

2. The computer implemented method of claim 1, further comprising:

the computer replacing the central probability file in the remote data processing system with the updated central probability file.

3. The computer implemented method of claim 1, further comprising:

the computer replacing the central probability file stored in a local device with the updated central probability file.

4. The computer implemented method of claim 1, further comprising:

the computer transmitting a valid position beacon identity to the remote data processing system.

5. The computer implemented method of claim 1, further comprising:

the computer receiving spatial aware services from the remote data processing system based on the valid position beacon identity.

6. The computer implemented method of claim 1, further comprising:

the computer normalizing the updated local probability file.

7. The computer implemented method of claim 1, wherein the local probability file comprises a plurality of rows and wherein each row of the plurality of rows corresponds to a position beacon identity and wherein the computer updating the local probability file comprises the computer increasing a number of occurrences for the current position beacon identity in a row of the previous position beacon identity.

8. The computer implemented method of claim 2, wherein the updated local probability file is a weighted updated local probability file.

9. The computer implemented method of claim 2, further comprising:

the computer receiving, at a remote data processing system, a plurality of updated central probability files;

the computer combining, by the remote data processing system, the plurality of updated central probability files with a common central probability file, wherein each updated central probability file out of the plurality of updated central probability files is weighted to be of a predetermined value to each other updated central probability file out of the plurality of updated central probability files.

10. The computer implemented method of claim 1, wherein the steps of the computer receiving the new copy of the central probability file;

the computer combining the updated local probability file with the new copy of the central probability file to form the updated central probability file; and

the computer transmitting the updated central probability file to a remote data processing system are performed periodically.

11. A non-transitory computer program product comprising a computer readable medium including computer usable program code for improving position beacon tracking using spatial probabilities, the computer program product comprising:

computer usable program code for receiving a central probability file from a remote data processing system to form a local probability file;

computer usable program code for receiving a current position beacon identity;

computer usable program code for checking the local probability file to find an entry for a previously received position beacon identity;

computer usable program code for, responsive to finding the entry for the previously received position beacon identity, finding a sub-entry for the current position beacon identity in a previously received position beacon identity;

computer usable program code for, responsive to finding the sub-entry, determining a number of occurrences for the current position beacon identity;

computer usable program code for comparing the number of occurrences for the current position beacon identity to a maximum number of occurrences for the previously received position beacon identity;

computer usable program code for, responsive to determining that the number of occurrences of the current position beacon identity is within a range of a maximum number of occurrences for the previously received position beacon identity, determining that the currently received position beacon identity is valid;

computer usable program code for, responsive to determining that the currently received position beacon identity is valid, updating the local probability file to form an updated local probability file;

computer usable program code for receiving a new copy of the central probability file from the remote data processing system;

computer usable program code for combining the updated local probability file with the new copy of the central probability file to form an updated central probability file; and

computer usable program code for transmitting the updated central probability file to a remote data processing system.

12. The non-transitory computer program product of claim 11, further comprising:

computer usable program code for replacing the central probability file in the remote data processing system with the updated central probability file.

13. The non-transitory computer program product of claim 11, further comprising:

computer usable program code for replacing the central probability file stored in a local device with the updated central probability file.

14. The non-transitory computer program product of claim 11, further comprising:

computer usable program code for transmitting a valid position beacon identity to the remote data processing system.

15. The non-transitory computer program product of claim 11, further comprising:

computer usable program code for receiving spatial aware services from the remote data processing system based on the valid position beacon identity.

16. The non-transitory computer program product of claim 11, further comprising:

computer usable program code for normalizing the updated local probability file.

17. The non-transitory computer program product of claim 11, wherein the local probability file comprises a plurality of rows and wherein each row of the plurality of rows corresponds to a position beacon identity and wherein the computer usable program code for updating the local probability file comprises computer usable program code for increasing a number of occurrences for the current position beacon identity in the row of the previous position beacon identity.

18. The non-transitory computer program product of claim 11, wherein the updated local probability file is a weighted updated local probability file.

19. The non-transitory computer program product of claim 11, further comprising:

computer usable program code for receiving, at a remote data processing system, a plurality of updated central probability files;

computer usable program code for combining, by the remote data processing system, the plurality of updated central probability files in a common central probability file, wherein each updated central probability file out of the plurality of updated central probability files is weighted to be of a predetermined value to each other updated central probability file out of the plurality of updated central probability files.

20. A data processing system for improving position beacon tracking using spatial probabilities, the data processing system comprising:

a storage device, wherein the storage device stores computer usable program code; and

a processor, wherein the processor executes the computer usable program code to;

receive a central probability file from a remote data processing system to form a local probability file;

receive a current position beacon identity;

check the local probability file to find an entry for a previously received position beacon identity;

responsive to finding the entry for the previously received position beacon identity, find a sub-entry for the current position beacon identity in a previously received position beacon identity;

responsive to finding the sub-entry, determine a number of occurrences for the current position beacon identity;

compare the number of occurrences for the current position beacon identity to a maximum number of occurrences for the previously received position beacon identity;

responsive to determining that the number of occurrences of the current position beacon identity is within a range of a maximum number of occurrences for the previously received position beacon identity, determine that the currently received position beacon identity is valid;

responsive to determining that the currently received position beacon identity is valid, update the local probability file to form an updated local probability file;

receive a new copy of the central probability file from the remote data processing system;

combine the updated local probability file with the new copy of the central probability file to form an updated central probability file; and

transmit the updated central probability file to a remote data processing system.