IP Library Granted Patent US 10,251,049
Granted Patent B2
US 10,251,049 · App. 15/987,746 · Granted Apr 2, 2019

Method and apparatus for identifying a mobile user in a site

Inventors: Glenn R. Seidman (Woodside, CA); Nader Fathi (Sunnyvale, CA); Klaus ten Hagen (Gorlitz, DE); Sebastian Andreatta (Palo Alto, CA)
Assignee: KIANA ANALYTICS INC.
H04W8/005G06K9/00335G06K9/00758G06K9/00771G06K9/2054G06K9/78H04W4/029H04W8/22G06K2009/00738H04W24/08
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 10,251,049
App. No.
15/987,746
Granted
Apr 2, 2019
Kind
B2
Abstract

A system and method for identifying mobile users in a site includes: receiving, in real time, data packets from wireless access points; identifying unique device identifications from the received data packets, and time stamping each identified unique device identification; determining repetitive or false unique device identifications in the identified unique device identification; and eliminating the repetitive or false unique device identifications in the identified unique device identification to obtain a plurality of accurate unique device identifications.

Claims (40)

1. A method for identifying a mobile user in a site, the method comprising:

receiving, in real time and via a wireless network, a plurality of data packets from a wireless access point;

determining a plurality of different device identifications for a mobile device used by the mobile user, from the received data packets;

determining repetitive or false device identifications in the determined plurality of different device identifications;

eliminating the repetitive or false device identifications in the determined plurality of different device identification to obtain an accurate device identification;

using the accurate device identification to uniquely identify the mobile device associated with the accurate device identification; and

predicting what the mobile user will do or where the mobile user will go within the site.

2. The method of claim 1 , wherein the plurality of different device identifications are one or more of media access control (MAC) addresses, International Mobile Equipment Identity (IMEI) and Bluetooth Identifiers.

3. The method of claim 1 , further comprising time stamping a first-seen and a last-seen device identification from the plurality of different device identifications.

4. The method of claim 1 , further comprising storing the repetitive or false unique device identifications; and verifying the accurate device identification against the stored repetitive or false unique device identifications.

5. The method of claim 1 , wherein said predicting includes one or more of future paths of the mobile user, next websites that the mobile user may access on the mobile device, next products that the mobile user may look at or purchase, and next physical locations that the mobile user may go to.

6. The method of claim 1 , wherein said predicting is utilized by one or more of merchants, advertisers, government agencies, and law enforcements.

7. The method of claim 1 , wherein said predicting is utilized to uniquely identify the mobile user as the mobile user moves in the site or in another site.

8. The method of claim 1 , wherein said determining a plurality of different device identifications and said determining repetitive or false unique device identifications comprises a dwell-time filter based on a threshold value.

9. The method of claim 8 , wherein said dwell-time filter includes one or more of a recency-time filter, an odd-behavior filter, an Organizationally Unique Identifier (OUI) filter, a locally administered device identification and a predetermined device identification pattern.

10. A system for identifying a mobile user in a site, the mobile user using a mobile device in communication with a wireless network in the site, the system comprising:

a wireless access point for receiving data packets from the mobile device attempting to access the wireless network, the data packets including a plurality of different identifications for the mobile device; and

a server in communication with the computer network for

receiving, in real time and via the wireless network, a plurality of data packets from the wireless access point,

determining a plurality of different device identifications for the mobile device used by the mobile user, from the received data packets,

determining repetitive or false device identifications in the determined plurality of different device identifications,

eliminating the repetitive or false device identifications in the determined plurality of different device identification to obtain an accurate device identification,

using the accurate device identification to uniquely identify the mobile device associated with the accurate device identification, and

predicting what the mobile user will do or where the mobile user will go within the site.

11. The system of claim 10 , wherein the plurality of different device identifications are one or more of media access control (MAC) addresses, International Mobile Equipment Identity (IMEI) and Bluetooth Identifiers.

12. The system of claim 10 , wherein the server further time stamps a first-seen and a last-seen device identification from the plurality of different device identifications.

13. The system of claim 10 , further comprising a dwell-time filter for identifying the plurality of different device identifications and determining repetitive or false device identifications, based on a threshold value.

14. The system of claim 13 , wherein said dwell-time filter includes one or more of a recency-time filter, an odd-behavior filter, an Organizationally Unique Identifier (OUI) filter, a locally administered device identification and a predetermined device identification pattern.

15. The system of claim 13 , wherein said dwell-time filter dynamically changes based on system parameters or a number of false-positives in a given time period or per a given number of observations.

16. The system of claim 10 , wherein said predicting information is utilized by one or more of merchants, advertisers, government agencies, and law enforcements to uniquely identify the mobile user as the mobile user moves in the site or in another site.

17. A non-transitory computer storage medium including a plurality of instructions, the instructions when executed by one or more processors performing a method for identifying a mobile user in a site, the site including a wireless access point, the method comprising:

receiving, in real time and via a wireless network, a plurality of data packets from the wireless access point;

determining a plurality of different device identifications for the mobile device used by the mobile user, from the received data packets;

determining repetitive or false device identifications in the determined plurality of different device identifications;

eliminating the repetitive or false device identifications in the determined plurality of different device identification to obtain an accurate device identification;

using the accurate device identification to uniquely identify the mobile device associated with the accurate device identification; and

predicting what the mobile user will do or where the mobile user will go within the site.

18. The non-transitory computer storage medium of claim 17 , wherein the plurality of different device device identifications are one or more of media access control (MAC) addresses, International Mobile Equipment Identity (IMEI) and Bluetooth Identifiers.

19. The non-transitory computer storage medium of claim 17 , wherein said predicting what the mobile user will do or where the mobile user will go includes one or more of future paths of the mobile user, next websites that the mobile user may access on their mobile devices, next products that the mobile user may look at or purchase, and next physical locations that the mobile user may access.

20. The non-transitory computer storage medium of claim 17 , wherein said predicting information is utilized by one or more of merchants, advertisers, government agencies, and law enforcements to uniquely identify the mobile user as the mobile user moves in the site or in another site.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded May 23, 2018
From: SEIDMAN, GLENN R.; FATHI, NADER; HAGEN, KLAUS TEN; ANDREATTA, SEBASTIAN
To: KIANA ANALYTICS INC.
Reel/Frame 045887/0213 →
Continuity (4)
Continuation 15658309 · Jul 24, 2017
Provisional Application 62376064 · Aug 17, 2016
Provisional Application 62366276 · Jul 25, 2016
Related Publication 20180270645A1 · Sep 20, 2018
Cited By (3)
US 12,388,782 US 12,402,064 US 12,640,995