Crowdsourcing method to detect broken WiFi indoor locationing model

1. A method, comprising:

determining a set of neighboring access points from scans of network access points in a space, wherein each neighboring access point occurs together in a scan of a particular level of the space;

receiving wireless data from a plurality of mobile devices moving through the space;

identifying a set of all access points for the space based on the wireless data; and

deriving, using a processor, a ratio based on the size of a difference between the set of neighboring access points and the set of all access points, the ratio representing a percentage of missing access points for the particular level of the space.

2. The method of claim 1 , wherein the scans of network access points are used for creating a model of the space.

3. The method of claim 1 , wherein the wireless data includes information identifying current access points on different levels of the space, the wireless data is collected over a period of time.

4. The method of claim 3 , further comprising identifying access point neighbors of a given access point on a given level of the space, the access point neighbors appear together most often with the given access point in the information.

5. The method of claim 4 further comprising determining whether the given access point has moved to a different level of the space based on the access point neighbors.

6. The method of claim 1 , further comprising determining a number of users to visit a level of the space based on a positioning system.

7. The method of claim 6 , wherein when the number of users to visit the level is below a threshold level, the method further comprises determining whether the ratio of missing access points applies to that level.

8. A non-transitory computer readable medium comprising instructions that, when executed by a processor, cause the processor to perform a method, the method comprising:

determining a set of neighboring access points from scans of network access points in a space, wherein each neighboring access point occurs together in a scan of a particular level of the space;

receiving wireless data from a plurality of mobile devices moving through the space;

identifying a set of all access points for the space based on the wireless data; and

deriving, using a processor, a ratio based on the size of a difference between the set of neighboring access points and the set of all access points, the ratio representing a percentage of missing access points for the particular level of the space.

9. The non-transitory computer readable medium of claim 8 , wherein the wireless data includes information identifying current access points on different levels of the space, the wireless data is collected over a period of time.

10. The non-transitory computer readable medium of claim 9 , wherein the method further comprises identifying access point neighbors of a given access point on a given level of the space, the access point neighbors appear together most often with the given access in the information.

11. The non-transitory computer readable medium of claim 10 , wherein the method further comprises determining whether the given access point has moved to a different level of the space based on the access point neighbors.

12. The non-transitory computer readable medium of claim 8 , wherein the method further comprises determining a number of users to visit a level of the space based on a positioning system.

13. The non-transitory computer readable medium of claim 12 , wherein when the number of users to visit the level is below a threshold level, the method further comprises determining whether the ratio of missing access points applies to that level.

14. A system, comprising:

a memory; and

a processor coupled to the memory, the processor being configured to:

determine a set of neighboring access points from scans of network access points in a space, wherein each neighboring access point occurs together in a scan of a particular level of the space;

receive wireless data from a plurality of mobile devices moving through the space;

identify a set of all access points for the space based on the wireless data; and

derive a ratio based on the size of a difference between the set of neighboring access points and the set of all access points, the ratio representing a percentage of missing access points for the particular level of the space.

15. The system of claim 14 , wherein the scans of network access points are used for creating a model of the space.

16. The system of claim 15 , wherein the wireless data includes information identifying current access points on different levels of the space, the wireless data is collected over a period of time.

17. The system of claim 16 , wherein the processor is further configured to identify access point neighbors of a given access point on a given level of the space, the access point neighbors appear together most often with the given access point in the information.

18. The system of claim 17 , wherein the processor is further configured to determine whether the given access point has moved to a different level of the space based on the access point neighbors.

19. The system of claim 14 , wherein the processor is further configured to determine a number of users to visit a level of the space based on a positioning system.

20. The system of claim 19 , wherein when the number of users to visit the level is below a threshold level the processor is further configured to determine whether the ratio of missing access points applies to that level.