Method and system for WiFi-based identification of person tracks

• US 8,989,775 B2
• Filed: 02/28/2013
• Issued: 03/24/2015
• Est. Priority Date: 02/29/2012
• Status: Active Grant

• Current Assignee: RetailNext, Inc.
• Original Assignee: RetailNext, Inc.
• Inventors: Shaw, George
• Primary Examiner(s): Prez-Gutirrez, Rafael
• Assistant Examiner(s): Fang, Keith
• Application Number:
  US13/780,964
• Publication Number:
  US 20130225199A1
• Time in Patent Office: 754 Days
• US Class Current: 455/456.1
• CPC Class Codes: G01S 11/06 using intensity measurements
• CPC Class Codes: G01S 5/0294 Trajectory determination or predictive filtering, e.g. target tracking or Kalman filtering
• CPC Class Codes: G01S 5/06 Position of source determined by co-ordinating a plurality of position lines defined by path-difference measurements G01S5/12 takes precedence
• CPC Class Codes: G01S 5/14 Determining absolute distances from a plurality of spaced points of known location
• CPC Class Codes: G06Q 10/0833 Tracking
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data
• CPC Class Codes: G06T 7/246 using feature-based methods, e.g. the tracking of corners or segments
• CPC Class Codes: G06T 7/292 Multi-camera tracking
• CPC Class Codes: G06T 7/77 using statistical methods
• CPC Class Codes: G06V 20/52 Surveillance or monitoring of activities, e.g. for recognising suspicious objects recognising microscopic objects G06V20/69
• CPC Class Codes: G06V 2201/10 Recognition assisted with metadata
• CPC Class Codes: G06V 40/20 Movements or behaviour, e.g. gesture recognition recognition of facial expressions G06V40/16
• CPC Class Codes: H04W 24/00 Supervisory, monitoring or testing arrangements
• CPC Class Codes: H04W 4/021 Services related to particular areas, e.g. point of interest [POI] services, venue services or geofences
• CPC Class Codes: H04W 64/00 Locating users or terminals or network equipment for network management purposes, e.g. mobility management

Abstract

In an implementation, techniques are provided for tracking the location of a device that transmits wireless signal. The wireless signal can be received at a set of receivers. Distances to the device are determined based on signal strength. From the distances, boundaries encompassing possible locations of the device are defined. Boundary intersections are analyzed in order to determine the location of the device.

Claims

1. A method comprising:

detecting at each access point of a plurality of access points a strength of a signal from a mobile client;

determining for each access point a distance between an access point and the mobile client based on the strength of the signal detected at the access point;

defining for each access point a boundary encompassing possible locations for the mobile client, the boundary comprising a dimension based on the determined distance between the access point and the mobile client;

identifying pairs of intersections formed by each boundary crossing another boundary;

grouping the intersections into a plurality of clusters, each cluster comprising a single intersection from each of the pairs of intersections;

analyzing the plurality of clusters to identify a cluster having a smallest size; and

using the cluster having the smallest size to determine a location of the mobile client.

2. The method of claim 1 wherein the intersections of the clusters form vertices of polygons, and the analyzing the plurality of clusters to identify a cluster having a smallest size comprises:

calculating areas of the polygons; and

comparing the areas to identify a polygon having a smallest area, wherein the polygon having the smallest area is the cluster having the smallest size.

3. The method of claim 1 wherein the intersections comprise x-coordinate values, and y-coordinate values, and the method comprises:

averaging x-coordinate values for intersections of the cluster having the smallest size to calculate an average x-coordinate value; and

averaging y-coordinate values for intersections of the cluster having smallest size to calculate an average y-coordinate value, wherein the location of the mobile client is specified by the average x-coordinate value and the average y-coordinate value.

4. The method of claim 1 wherein the plurality of access points comprises at least three access points.

5. The method of claim 1 wherein the plurality of access points are capable of receiving Wi-Fi signals.

6. The method of claim 1 wherein the dimension is a radius having a length equal to the determined distance.

7. The method of claim 1 wherein the dimension is a radius having a length equal to or greater than the determined distance.

8. The method of claim 1 wherein the determining for each Wi-Fi access point a distance between a Wi-Fi access point and the mobile client based on the strength of the signal detected at the Wi-Fi access point comprises:

consulting a database that stores information correlating the strength of the signal detected at the Wi-Fi access point to a probability of a specific distance being between the Wi-Fi access point and the mobile client.

9. A method comprising:

detecting at each of at least three Wi-Fi access points a strength of a signal from a mobile client;

determining for each Wi-Fi access point a distance between a Wi-Fi access point and the mobile client based on the strength of the signal detected at the Wi-Fi access point;

defining for each access point a circular boundary encompassing possible locations for the mobile client, the circular boundary comprising a radius having a length based on the determined distance between the Wi-Fi access point and the mobile client;

identifying pairs of intersections formed by each circular boundary crossing another circular boundary;

grouping the intersections into a plurality of clusters, each cluster comprising a single intersection from each of the pairs of intersections;

analyzing the plurality of clusters to identify a cluster having a smallest size; and

determining a location of the mobile client using the cluster having the smallest size.

10. The method of claim 9 wherein the intersections of the clusters comprise x-coordinates and y-coordinates, and define vertices of polygons, and the method comprises:

calculating areas of the polygons;

comparing the areas to identify a polygon having a smallest area;

averaging the x-coordinates of the polygon having the smallest area to calculate an average x-coordinate value; and

averaging the y-coordinates of the polygon having the smallest area to calculate an average y-coordinate value, wherein the average x-coordinate value and the average y-coordinate value specify the location of the mobile client.

11. The method of claim 9 wherein the length of the radius is equal to or greater than the determined distance between the Wi-Fi access point and the mobile client.

12. The method of claim 9 wherein the determining for each Wi-Fi access point a distance between a Wi-Fi access point and the mobile client based on the strength of the signal detected at the Wi-Fi access point comprises:

consulting a database that stores information correlating the strength of the signal detected at the Wi-Fi access point to a probability of a specific distance being between the Wi-Fi access point and the mobile client.

13. A method comprising:

detecting at each of a plurality of access points a strength of a signal from a mobile client;

determining for each access point a distance between an access point and the mobile client based on the strength of the signal detected at the access point;

defining for each access point a circular boundary comprising a radius having a length based on the determined distance between the access point and the mobile client;

identifying pairs of intersections formed by each circular boundary crossing another circular boundary;

grouping the intersections into a plurality of clusters, each cluster comprising a single intersection from each of the pairs of intersections;

analyzing the plurality of clusters to identify a cluster having a smallest size; and

determining a location of the mobile client using the cluster having the smallest size.

14. The method of claim 13 wherein the plurality of access points comprises at least three access points.

15. The method of claim 13 wherein an access point is capable of receiving a Wi-Fi signal transmitted from the mobile client.

16. The method of claim 13 wherein the intersections are specified by x-coordinates and y-coordinates.

17. The method of claim 13 comprising at least three pairs of intersections.