Identifying and generating biometric cohorts based on biometric sensor input

• US 9,165,216 B2
• Filed: 02/10/2012
• Issued: 10/20/2015
• Est. Priority Date: 12/12/2008
• Status: Expired due to Fees

• Current Assignee: Daedalus Blue LLC
• Original Assignee: International Business Machines Corporation
• Inventors: Angell, Robert L., Friedlander, Robert R., Kraemer, James R.
• Primary Examiner(s): Chaki, Kakali
• Assistant Examiner(s): Seck, Ababacar
• Application Number:
  US13/370,811
• Publication Number:
  US 20120139697A1
• Time in Patent Office: 1,348 Days
• Field of Search: None
• US Class Current: 1/1
• CPC Class Codes: G06F 18/23 Clustering techniques
• CPC Class Codes: G06F 21/32 using biometric data, e.g. fingerprints, iris scans or voiceprints
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: G06N 5/04 Inference or reasoning models
• CPC Class Codes: G06V 10/762 using clustering, e.g. of similar faces in social networks
• CPC Class Codes: G06V 40/10 Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands

Abstract

Biometric data, which identifies a set of biometric patterns, is received from a set of biometric sensors. The biometric data is processed to form digital biometric data that identifies attributes of the biometric data. Thereafter, a biometric cohort is generated using the digital biometric data. Each member of the set of biometric cohorts shares at least one biometric attribute in common.

Claims

1. A computer implemented method for generating a biometric cohort, the computer implemented method comprising:

receiving biometric data identifying a set of biometric patterns, wherein the biometric patterns represent a common physiological reaction to a same stimulus by a group of monitored subjects that have a heart rate within a particular range and a specific body shape, wherein the biometric data is received from a set of biometric sensors, wherein the biometric sensors include an image capture device, an audio capture device, an odor detection device, a heart monitor, a blood pressure monitor, a thermometer for measuring body temperature, a fingerprint scanner, a thumbprint scanner, a palm scanner, a retinal scanner, an iris scanner, a breathalyzer, a microphone capable of detecting a heart beat and breath sounds, a respiratory monitor, a fetal heart monitor, and a blood sugar monitor;

processing the biometric data to form digital biometric data, wherein the digital biometric data identifies attributes of the biometric data, wherein the digital biometric data includes metadata describing a set of attributes for one or more monitored subjects, wherein the set of attributes includes behavioral attributes, wherein the digital biometric data further includes a context comprising a time, date and type of location at which the biometric data was collected, wherein biometric data collected from a monitored subject at a first time, date and type of location differs from biometric data collected from the monitored subject at a different second time, data and location; and

generating a biometric cohort using the digital biometric data, wherein each member of the biometric cohort shares at least one biometric attribute in common.

2. The computer implemented method of claim 1, wherein the set of biometric sensors comprises an odor detection device, and wherein the computer implemented method further comprises:

receiving a pheromone level for a specific pheromone emitted from an animal; and

placing the animal in the biometric cohort whose members emit the specific pheromone.

3. The computer implemented method of claim 1, further comprising:

identifying a speech pattern of persons being monitored; and

populating the biometric cohort with persons having a same speech pattern.

4. The computer implemented method of claim 1, further comprising:

identifying a gait of persons observed by the biometric sensors; and

populating the biometric cohort with persons having a same gait.

5. The computer implemented method of claim 1, wherein the biometric data is a first set of biometric data taken at a first time interval, and wherein the computer implemented method further comprises:

receiving a second set of biometric data taken at a second time interval; and

processing the first set of biometric data and the second set of biometric data to generate the digital biometric data, wherein the digital biometric data describes the attributes of a monitored subject.

6. The computer implemented method of claim 1, further comprising:

identifying monitored persons'"'"' reactions to a particular stimulus; and

populating the biometric cohort with persons having a same reaction to the particular stimulus.

7. The computer implemented method of claim 1, wherein generating the biometric cohort further comprises:

analyzing the digital biometric data using cohort criteria and a set of cohort generation data models, by a cohort generation engine, to identify the biometric cohort, wherein the set of cohort generation data models are generated from a statistical model of the biometric cohort that was created from simulation data.

8. The computer implemented method of claim 1, wherein generating the biometric cohort further comprises:

responsive to receiving the biometric data in an analog format, converting the biometric data from the analog format into a digital format.

9. A computer program product for generating a biometric cohort, the computer program product comprising:

a non-transitory computer readable storage device;

first program instructions to receive biometric data identifying a set of biometric patterns, wherein the biometric patterns represent a common physiological reaction to a same stimulus by a group of monitored subjects that have a heart rate within a particular range and a specific body shape, wherein the biometric data is received from a set of biometric sensors, wherein the biometric sensors include an image capture device, an audio capture device, an odor detection device, a heart monitor, a blood pressure monitor, a thermometer for measuring body temperature, a fingerprint scanner, a thumbprint scanner, a palm scanner, a retinal scanner, an iris scanner, a breathalyzer, a microphone capable of detecting a heart beat and breath sounds, a respiratory monitor, a fetal heart monitor, and a blood sugar monitor;

second program instructions to process the biometric data to form digital biometric data, wherein the digital biometric data identifies attributes of the biometric data, wherein the digital biometric data includes metadata describing a set of attributes for one or more monitored subjects, wherein the set of attributes includes behavioral attributes, wherein the digital biometric data further includes a context comprising a time, date and type of location at which the biometric data was collected, wherein biometric data collected from a monitored subject at a first time, date and type of location differs from biometric data collected from the monitored subject at a different second time, data and location;

third program instructions to generate a biometric cohort using the digital biometric data, wherein each member of the biometric cohort is a place that is populated with a form of living organism that shares at least one biometric attribute in common; and

wherein the first program instructions, the second program instructions, and the third program instructions are stored on the non-transitory computer readable storage device.

10. The computer program product of claim 9, wherein the set of biometric sensors comprises at least one of an image capture device, an audio capture device, an odor detection device, and a sampling device.

11. The computer program product of claim 9, further comprising:

fourth program instructions to identify a monitored subject from the attributes of the biometric data, wherein the fourth program instructions are stored in the non-transitory computer readable storage device.

12. The computer program product of claim 9, further comprising:

fourth program instructions to identify at least one of a behavioral attribute and a physical attribute of a monitored subject, wherein the fourth program instructions are stored in the non-transitory computer readable storage device.

13. The computer program product of claim 9, wherein the biometric data is a first set of biometric data generated at a first time interval, and wherein the computer program product further comprises:

fourth program instructions to receive a second set of biometric data taken at a second time interval; and

fifth program instructions to process the first set of biometric data and the second set of biometric data to generate the digital biometric data, wherein the digital biometric data describes the attributes of a monitored subject; and

wherein the fourth program instructions and the fifth program instructions are stored in the non-transitory computer readable storage device.

14. The computer program product of claim 9, further comprising:

fourth program instructions to receive the biometric cohort by an inference engine; and

fifth program instructions to process the biometric cohort, by the inference engine, to generate a set of inferences; and

wherein the fourth program instructions and the fifth program instructions are stored on the non-transitory computer readable storage device.

15. The computer program product of claim 9, wherein the third program instructions for generating the biometric cohort further comprise:

program instructions to analyze the digital biometric data using cohort criteria, by a cohort generation engine, to identify the biometric cohort.

16. The computer program product of claim 9, wherein the third program instructions for generating the biometric cohort further comprises:

program instructions to analyze the digital biometric data in a set of cohort generation data models, by a cohort generation engine, to identify the biometric cohort.

17. A system for generating biometric cohorts, the system comprising:

a set of biometric sensors, wherein the set of biometric sensors captures biometric data, and wherein the biometric data comprises a set of biometric patterns, wherein the biometric patterns represent a common physiological reaction to a same stimulus by a group of persons that have a heart rate within a particular range and a specific body shape, and wherein the biometric sensors include an image capture device, an audio capture device, an odor detection device, a heart monitor, a blood pressure monitor, a thermometer for measuring body temperature, a fingerprint scanner, a thumbprint scanner, a palm scanner, a retinal scanner, an iris scanner, a breathalyzer, a microphone capable of detecting a heart beat and breath sounds, a respiratory monitor, a fetal heart monitor, and a blood sugar monitor;

a biometric pattern processing engine, wherein the biometric pattern processing engine utilizes a processor to form digital biometric data from the biometric data, wherein the digital biometric data includes metadata describing a set of attributes for one or more monitored subjects, wherein the set of attributes includes behavioral attributes, wherein the digital biometric data further includes a context comprising a time, date and location at which the biometric data was collected, wherein biometric data collected from a monitored subject at a first time, date and type of location differs from biometric data collected from the monitored subject at a different second time, data and location; and

a cohort generation engine, wherein the cohort generation engine utilizes a processor to generate a biometric cohort from the digital biometric data by use of the digital biometric data, wherein all of the members of the biometric cohort share at least one biometric attribute in common.

18. The system of claim 17, wherein the set of biometric sensors comprises at least one of an image capture device, an audio capture device, an odor detection device, and a sampling device.

19. The system of claim 17, further comprising:

an identification engine for identifying a monitored subject from the attributes of the biometric data.

20. The system of claim 19, further comprising:

an inference engine, wherein the inference engine generates inferences from the biometric cohort.