Method and apparatus for analysis of user traffic within a predefined area

• US 8,699,370 B2
• Filed: 08/23/2011
• Issued: 04/15/2014
• Est. Priority Date: 08/24/2010
• Status: Active Grant

• Current Assignee: WeWork Companies, Inc.
• Original Assignee: Euclid Chemical Company (RPM International Incorporated)
• Inventors: Leung, Kenneth Man-Kin, Smith, William Tolbert, Wilheim, Steve Lawrence
• Primary Examiner(s): Ton, Dang T
• Assistant Examiner(s): Aung, Sai
• Application Number:
  US13/216,201
• Publication Number:
  US 20120163206A1
• Time in Patent Office: 966 Days
• Field of Search: 370100-402, 370/471, 3703952-3954, 340/3.1, 340/10.2, 340/539.13, 455/67.11, 455/404
• US Class Current: 370/252
• CPC Class Codes: G01S 11/06 using intensity measurements
• CPC Class Codes: G01S 3/023 Monitoring or calibrating
• CPC Class Codes: G01S 5/0009 Transmission of position information to remote stations involving assistance data G01S5/0236
• CPC Class Codes: G01S 5/0284 Relative positioning
• CPC Class Codes: G01S 5/0294 Trajectory determination or predictive filtering, e.g. target tracking or Kalman filtering
• CPC Class Codes: G06Q 10/063 Operations research, analysis or management
• CPC Class Codes: G06Q 50/40 Business processes related to the transportation industry shipping G06Q10/083
• CPC Class Codes: H04B 17/318 Received signal strength
• CPC Class Codes: H04B 17/373 Predicting channel quality or other radio frequency [RF] parameters
• CPC Class Codes: H04L 63/0428 wherein the data content is protected, e.g. by encrypting or encapsulating the payload
• CPC Class Codes: H04L 67/12 specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
• CPC Class Codes: H04L 67/303 Terminal profiles
• CPC Class Codes: H04L 67/535 Tracking the activity of the user network monitoring arrangements H04L43/00; recording of computer activity G06F11/34
• CPC Class Codes: H04W 12/02 Protecting privacy or anonymity, e.g. protecting personally identifiable information [PII]
• CPC Class Codes: H04W 12/71 Hardware identity
• CPC Class Codes: H04W 4/02 Services making use of location information
• 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 4/023 using mutual or relative location information between multiple location based services [LBS] targets or of distance thresholds
• CPC Class Codes: H04W 4/025 using location based information parameters
• CPC Class Codes: H04W 4/38 for collecting sensor information
• CPC Class Codes: H04W 4/80 : Services using short range communication, e.g. near-field communication [NFC], radio-frequency identification [RFID] or low energy communication
• CPC Class Codes: H04W 64/00 : Locating users or terminals or network equipment for network management purposes, e.g. mobility management

Abstract

Multiple packets are received that were transmitted by multiple mobile electronic device sensors located in a predefined area. The packets each include data detected by the sensors of multiple mobile electronic devices. At least a portion of the collected data is stored including multiple unique device identifiers that belong to multiple mobile electronic devices. Responsive to determining that at least two of the unique device identifiers are sequential, a set of values based on the at least two unique devices identifiers are associated as belonging to a same one of the mobile electronic devices.

Claims

1. A method for determining distance between a mobile electronic device and a sensor detecting the mobile electronic device, comprising:

receiving a first set of one or more packets transmitted by the sensor that include data associated with a first signal of the mobile electronic device detected by the sensor, wherein the data includes a signal strength value of the first signal, and wherein the data in the first set of packets includes a unique device identifier of the mobile electronic device and a time of detection of the first signal;

receiving a second set of a plurality of packets transmitted by the sensor that include data associated with a plurality of second signals from a set of one or more access points in proximity to the sensor, wherein the data includes a signal strength value for each of the second signals;

determining a variation of signal strength value for the second signals over a period of time;

associating relative distance and signal strength based on the variations of signal strength value for the second signals;

determining a distance value between the mobile electronic device and the sensor using the associated relative distance and signal strength and based on the signal strength value of the first signal;

determining a location of the mobile electronic device based at least in part on the distance value between the mobile electronic device and the first signal;

receiving an indication that an online identity has performed an online activity at a time and location in a predefined area bound by the sensor and a set of one or more other sensors, wherein the online identity is identified with a unique online identifier; and

responsive to determining that the location and time of the indicated online activity substantially matches the location of the mobile electronic device at the time of detection of the first signal, associating the unique online identifier with a value based on the unique device identifier.

2. The method of claim 1, wherein the sensor is selected from the group consisting of a WiFi detector, a Bluetooth receiver, and a Radio Frequency (RF) receiver.

3. The method of claim 1, wherein the mobile electronic device is one of the group consisting of a WiFi enabled device, a cellular phone, and a Bluetooth enabled device.

4. The method of claim 1, wherein the value based on the unique device identifier is an encrypted version of the unique device identifier.

5. The method of claim 1, further comprising:

correlating the location of the mobile electronic device with a physical location that is associated with demographic data;

assigning a set of one or more demographic attributes to a device profile associated with the mobile electronic device based on the demographic data.

6. The method of claim 5, further comprising:

determining an object of interest based on the set of demographic attributes; and

causing the object of interest to be presented through an interface in an area proximate to the location of the mobile electronic device.

7. An apparatus for determining distance between a mobile electronic device and a sensor detecting the mobile electronic device, comprising:

a set of one or more processors;

a non-transitory machine-readable storage medium that stores instructions, that when executed by the set of processors, cause the set of processors to perform the following;

receive a first set of one or more packets transmitted by the sensor that include data associated with a first signal of the mobile electronic device detected by the sensor, wherein the data includes a signal strength value of the first signal, and wherein the data in the first set of packets includes a unique device identifier of the mobile electronic device and a time of detection of the first signal;

receive a second set of a plurality of packets transmitted by the sensor that include data associated with a plurality of second signals from a set of one or more access points in proximity to the sensor, wherein the data includes a signal strength value for each of the second signals;

determine a variation of signal strength value for the second signals over a period of time;

associate relative distance and signal strength based on the variations of signal strength value for the second signals;

determine a distance value between the mobile electronic device and the sensor using the associated relative distance and signal strength and based on the signal strength value of the first signal;

determine a location of the mobile electronic device based at least in part on the distance value between the mobile electronic device and the first signal;

receive an indication that an online identity has performed an online activity at a time and location in a predefined area bound by the sensor and a set of one or more other sensors, wherein the online identity is identified with a unique online identifier; and

responsive to a determination that the location and time of the indicated online activity substantially matches the location of the mobile electronic device at the time of detection of the first signal, associate the unique online identifier with a value based on the unique device identifier.

8. The apparatus of claim 7, wherein the sensor is selected from the group consisting of a WiFi detector, a Bluetooth receiver, and a Radio Frequency (RF) receiver.

9. The apparatus of claim 7, wherein the mobile electronic device is one of the group consisting of a WiFi enabled device, a cellular phone, and a Bluetooth enabled device.

10. The apparatus of claim 7, wherein the value based on the unique device identifier is an encrypted version of the unique device identifier.

11. The apparatus of claim 7, further comprising instructions that when executed by the set of processors, cause the set of processors to perform the following:

correlate the location of the mobile electronic device with a physical location that is associated with demographic data;

assign a set of one or more demographic attributes to a device profile associated with the mobile electronic device based on the demographic data.

12. The apparatus of claim 11, further comprising instructions that when executed by the set of processors, cause the set of processors to perform the following:

determine an object of interest based on the set of demographic attributes; and

cause the object of interest to be presented through an interface in an area proximate to the location of the mobile electronic device.

13. A method for determining a location of a mobile electronic device, the method comprising:

receiving a first set of one or more packets transmitted by a single sensor that include data associated with a first signal of the mobile electronic device detected by the single sensor, wherein the data includes a signal strength value of the first signal, and wherein the single sensor is located in a predefined area;

determining a first distance value between the mobile electronic device and the single sensor based on the signal strength value of the first signal;

determining a first location of the mobile electronic device based at least in part on the first distance value between the mobile electronic device and the first signal;

correlating the first location of the mobile electronic device with a first physical location;

receiving a second set of one or more packets transmitted by the single sensor that include data associated with a second signal of the mobile electronic device detected by the single sensor, wherein the data associated with the second signal includes a signal strength value of the second signal;

determining a second distance value between the mobile electronic device and the single sensor based on the signal strength value of the second signal;

determining a second location of the mobile electronic device based at least in part on the second distance value between the mobile electronic device and the second signal;

correlating the second location of the mobile electronic device with a second physical location; and

calculating movement of the mobile electronic device from the first physical location to the second physical location.

14. The method of claim 13, wherein the first physical location is relative to a retail establishment.

15. The method of claim 13, wherein correlating the first location of the mobile electronic device with the first physical location includes assigning the mobile electronic device to a zone based on the determined first location of the mobile electronic device.

16. The method of claim 13, wherein determining the first distance value between the mobile electronic device and the single sensor based on the signal strength value of the first signal is based on a history of distances correlated with signal strength.

17. The method of claim 13, further comprising:

wherein the data further includes an identifier that can be used to determine a manufacturer of the mobile electronic device;

determining, based on the identifier, a manufacturer of the mobile electronic device; and

wherein determining the first distance value between the mobile electronic device and the single sensor based on the signal strength value of the first signal is based on relative signal strength known for mobile electronic devices manufactured by the manufacture of the mobile electronic device.

18. The method of claim 13, wherein the single sensor is one of the group consisting of a WiFi detector, a Bluetooth receiver, and a Radio Frequency (RF) receiver.

19. The method of claim 13, wherein the mobile electronic device is one of the group consisting of a WiFi enabled device, a cellular phone, and a Bluetooth enabled device.

20. The method of claim 13, wherein the first physical location is associated with demographic data, and wherein the method further comprises assigning a set of one or more demographic attributes based on the demographic data to a device profile associated with the mobile electronic device.