METHOD AND APPARATUS FOR ANALYSIS OF USER TRAFFIC WITHIN A PREDEFINED AREA

• US 20140229616A1
• Filed: 04/15/2014
• Published: 08/14/2014
• Est. Priority Date: 08/24/2010
• Status: Active Grant

• Current Assignee: WeWork Companies, Inc.
• Original Assignee: Kenneth Man-Kin Leung, Steve Lawrence Wilhelm, William Tolbert Smith
• Inventors: Leung, Kenneth Man-Kin, Smith, William Tolbert, Wilhelm, Steve Lawrence
• Granted Patent: US 9,438,677 B2
• Time in Patent Office: Days
• US Class Current: 709/224
• 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 in a data processing center, comprising:

receiving a plurality of packets transmitted by a plurality of mobile electronic device sensors located in a predefined area, wherein the plurality of packets include data detected by the plurality of sensors of a plurality of mobile electronic devices;

storing at least a portion of the data collected by the plurality of sensors that is included in the plurality of packets, wherein the stored portion of data includes a plurality of unique device identifiers that belong to the plurality of mobile electronic devices; and

responsive to determining that at least two of the unique device identifiers are sequential, associating a set of values based on the at least two unique device identifiers as belonging to a same first one of the plurality of mobile electronic devices.

2. The method of claim 1, wherein the stored portion of data further includes detection times of the plurality of mobile electronic devices, and wherein prior to associating the at least two unique device identifiers, determining that the at least two unique device identifiers were detected within a predefined period of time.

3. The method of claim 1, wherein the set of values include encrypted versions of the at least two unique device identifiers.

4. The method of claim 1, wherein associating the at least two unique device identifiers includes performing the following:

encrypting each of the at least two unique device identifiers; and

associating each of the at least two encrypted unique device identifiers as belonging to the first mobile electronic device.

5. The method of claim 1, further comprising:

storing those unique identifiers in a device profile created for the first mobile electronic device.

6. The method of claim 4, further comprising:

determining a set of one or more device locations that the first mobile electronic device has been based at least in part on the data detected by one or more of the plurality of sensors for the at least two unique device identifiers; and

assigning attribute information to the device profile based on demographic data of a set of one or more physical locations that correlate to the set of device locations.

7. The method of claim 1, wherein the plurality of sensors are selected from the group consisting of a WiFi detector, a Bluetooth receiver, and a Radio Frequency (RF) receiver.

8. The method of claim 1, wherein the plurality of mobile electronic devices are selected from the group consisting of a WiFi enabled device, a cellular phone, and a Bluetooth enabled device.

9. 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;

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 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; and

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.

10. The method of claim 9, wherein the sensor is selected from the group consisting of a WiFi detector, a Bluetooth receiver, and a Radio Frequency (RF) receiver.

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

12. The method of claim 9, further comprising:

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

13. The method of claim 12, further comprising:

wherein the data in the first set of packets further includes a unique device identifier of the mobile electronic device and a time of detection of 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.

14. The method of claim 13, wherein the value based on the unique device identifier is an encrypted version of the unique device identifier.

15. The method of claim 12, 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.

16. The method of claim 15, 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.

17. An apparatus in a data processing center, 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 plurality of packets transmitted by a plurality of mobile electronic device sensors located in a predefined area, wherein the plurality of packets include data detected by the plurality of sensors of a plurality of mobile electronic devices;

store at least a portion of the data collected by the plurality of sensors that is included in the plurality of packets, wherein the stored portion of data includes a plurality of unique device identifiers that belong to the plurality of mobile electronic devices; and

responsive to a determination that at least two of the unique device identifiers are sequential, associate a set of values based on the at least two unique device identifiers as belonging to a same first one of the plurality of mobile electronic devices.

18. The apparatus of claim 17, wherein the stored portion of data further includes detection times of the plurality of mobile electronic devices, and wherein prior to an association of the at least two unique device identifiers, the set of processors are further to determine that the at least two unique device identifiers were detected within a predefined period of time.

19. The apparatus of claim 17, wherein the set of values include encrypted versions of the at least two unique device identifiers.

20. The apparatus of claim 17, wherein the set of processors is to associate the at least two unique device identifiers by performing the following:

encrypt each of the at least two unique device identifiers; and

associate each of the at least two encrypted unique device identifiers as belonging to the first mobile electronic device.

21. The apparatus of claim 17, further comprising instructions that when executed by the set of processors, cause the set of processors to store those unique identifiers in a device profile created for the first mobile electronic device.

22. The apparatus of claim 21, further comprising instructions that when executed by the set of processors, cause the set of processors to:

determine a set of one or more device locations that the first mobile electronic device has been based at least in part on the data detected by one or more of the plurality of sensors for the at least two unique device identifiers; and

assign attribute information to the device profile based on demographic data of a set of one or more physical locations that correlate to the set of device locations.

23. The apparatus of claim 17, wherein the plurality of sensors are selected from the group consisting of a WiFi detector, a Bluetooth receiver, and a Radio Frequency (RF) receiver.

24. The apparatus of claim 17, wherein the plurality of mobile electronic devices are selected from the group consisting of a WiFi enabled device, a cellular phone, and a Bluetooth enabled device.

25. 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;

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 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; and

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.

26. The apparatus of claim 25, wherein the sensor is selected from the group consisting of a WiFi detector, a Bluetooth receiver, and a Radio Frequency (RF) receiver.

27. The apparatus of claim 25, wherein the mobile electronic devices is one of the group consisting of a WiFi enabled device, a cellular phone, and a Bluetooth enabled device.

28. The apparatus of claim 25, further comprising instructions that when executed by the set of processors, cause the set of processors to:

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

29. The apparatus of claim 28, further comprising:

wherein the data in the first set of packets further includes a unique device identifier of the mobile electronic device and a time of detection of the first signal;

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

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.

30. The apparatus of claim 29, wherein the value based on the unique device identifier is an encrypted version of the unique device identifier.

31. The apparatus of claim 28, 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.

32. The apparatus of claim 31, 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.