Multiple meter detection and processing using motion data

• US 9,696,336 B2
• Filed: 11/30/2012
• Issued: 07/04/2017
• Est. Priority Date: 11/30/2011
• Status: Active Grant

• Current Assignee: The Nielsen Company LLC (MOOD Media Corporation)
• Original Assignee: The Nielsen Company LLC (MOOD Media Corporation)
• Inventors: Jain, Anand, Stavropoulos, John, Neuhauser, Alan, Kuznetsov, Vladimir, Crystal, Jack, Lynch, Wendell
• Primary Examiner(s): Le, Toan
• Application Number:
  US13/691,166
• Publication Number:
  US 20130138388A1
• Time in Patent Office: 1,677 Days
• CPC Class Codes: G01P 15/00 Measuring acceleration; Measuring deceleration; Measuring shock, i.e. sudden change of acceleration
• CPC Class Codes: G01P 15/18 in two or more dimensions
• CPC Class Codes: G06F 17/00 Digital computing or data processing equipment or methods, specially adapted for specific functions information retrieval, database structures or file system structures therefor G06F16/00
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data

Abstract

Systems and methods are disclosed for identifying users of portable user devices according to one or more accelerometer profiles created for a respective user. During a media session, the portable computing device collects media exposure data, while at the same time, collects data from the accelerometer and compares it to the user profile. The comparison authenticates the user and determines the physical activity the user is engaged in. Additional data may be collected from the portable computing device to determine one or more operational conditions of the device itself, including the detection of multiple devices being physically carried by one user. Gross motion strings may also be generated by devices and compared to see if strings match, thus suggesting multiple devices are being carried by one user.

Claims

1. A computer-implemented method for determining multiple portable computing devices being physically carried by one person, comprising:

receiving media exposure data over a data network from at least one of a plurality of portable computing devices;

receiving motion strings over the data network respectively from each of the plurality of portable computing devices, the motion strings including a successive binary representation of motion over a first period of time, the first period of time divided into a plurality of sub-periods of time, the successive binary representation including a series of values representing motion of respective portable computing devices for each of the sub-periods of time;

comparing the motion strings in a processor to determine if at least two motion strings match within a predetermined threshold; and

identifying the devices that produced matching motion strings as being physically carried by a same person.

2. The computer-implemented method of claim 1, wherein each of the series of values is formed by determining if the gross motion within the sub-period of time exceeded a motion threshold.

3. The computer-implemented method of claim 2, wherein a binary “

1”

is generated if the gross motion within the sub-period of time meets or exceeds the motion threshold, and a binary “

0”

is generated if the gross motion within the sub-period of time does not meet or exceed the motion threshold.

4. The computer implemented method of claim 1, further including comparing a sub-string of each motion strings in a processor to determine if at least two motion sub-strings match within a predetermined threshold.

5. The computer implemented method of claim 4, further including determining if identified devices provided media exposure data.

6. The computer-implemented method of claim 1, wherein only one of the devices identified as being carried by the same person is credited with media exposure, thereby reducing inaccurate media measurement results.

7. A system for detecting multiple portable computing devices being physically carried by one person, comprising:

an input for receiving media exposure data over a data network from at least one of a plurality of portable computing devices;

the input to receive motion strings over the data network respectively from each of the plurality of portable computing devices, each of the strings including a successive binary representation of motion over a first period of time, the first period of time divided into a plurality of sub-periods of time, the successive binary representation including a series of values representing motion of respective portable computing devices for each of the sub-periods of time; and

a processor, operatively coupled to the input, the processor being configured to compare the motion strings to determine if at least two motion strings match within a predetermined threshold, and identify the devices that produced matching motion strings as being physically carried by a same person.

8. The system of claim 7, wherein each of the series of values are formed by determining if the gross motion within the sub-period of time exceeded a motion threshold.

9. The system of claim 8, wherein a binary “

1”

is generated if the gross motion within the sub-period of time meets or exceeds the motion threshold, and a binary “

0”

is generated if the gross motion within the sub-period of time does not meet or exceed the motion threshold.

10. The system of claim 7, further including comparing a sub-string of each motion strings in a processor to determine if at least two motion sub-strings match within a predetermined threshold.

11. The system of claim 7, further including determining if identified devices provided media exposure data.

12. The system of claim 7, wherein only one of the devices identified as being carried by the same person is credited with media exposure, thereby reducing inaccurate media measurement results.