UNIQUE COHORT DISCOVERY FROM MULTIMODAL SENSORY DEVICES

• US 20090240695A1
• Filed: 03/18/2008
• Published: 09/24/2009
• Est. Priority Date: 03/18/2008
• Status: Abandoned Application

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Kraemer, James R., Angell, Robert Lee, Friedlander, Robert R.
• Application Number:
  US12/050,537
• Publication Number:
  US 20090240695A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/70 of video data
• CPC Class Codes: G06F 16/75 Clustering; Classification
• CPC Class Codes: G06F 16/907 Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
• CPC Class Codes: G06Q 10/10 Office automation; Time management

Abstract

According to one embodiment of the present invention, a computer implemented method, apparatus, and computer-usable program product for generating unique cohort groups using multimodal sensory device. Multimodal sensory data is received from a set of multimodal sensors in a public environment. The set of multimodal sensors are associated with a network. The multimodal sensory data is received from the set of multimodal sensors over the network. The multimodal sensory data is processed to generate a plurality of attributes to form cohort attributes. A plurality of unique cohort groups is generated using the cohort attributes and the multimodal sensory data. Each member of the cohort group shares at least one common attribute.

Claims

1. A computer implemented method for generating unique cohort groups using multimodal sensory device, the computer implemented method comprising:

receiving multimodal sensory data from a set of multimodal sensors in a public environment, wherein the set of multimodal sensors are associated with a network, and wherein the multimodal sensory data is received from the set of multimodal sensors over the network;

processing the multimodal sensory data to generate a plurality of attributes to form cohort attributes; and

generating a plurality of unique cohort groups using the cohort attributes and the multimodal sensory data, wherein each member of the cohort group shares at least one common attribute.

2. The computer implemented method of claim 1 wherein the plurality of unique cohort groups further comprises a plurality of sub-cohort groups associated with a set of cohort groups in the plurality of cohort groups.

3. The computer implemented method of claim 1 wherein the set of multimodal sensors comprises a set of radio frequency identification tag readers and further comprising:

receiving information from radio frequency identification tags associated with a set of cohorts by the set of radio frequency identification tag readers, and

transmitting the information over the network to a central data processing system by the radio frequency identification tag readers.

4. The computer implemented method of claim 1 wherein the set of multimodal sensors comprises a set of digital video cameras, wherein the set of digital video cameras captures a stream of video data associated with a set of objects, and wherein the stream of video data is transmitted to a central data processing system in real time as the stream of video data is generated, and further comprising:

analyzing the stream of video data by a video analytics engine associated with the central data processing system to generate video metadata describing the set of objects in the stream of video data; and

identifying the plurality of attributes associated with the set of objects using the video metadata.

5. The computer implemented method of claim 1 wherein the set of multimodal sensors comprises at least one of a set of global positioning satellite receivers, a set of infrared sensors, a set of microphones, a set of motion detectors, a set of chemical sensors, a set of biometric sensors, a set of pressure sensors, a set of temperature sensors, a set of metal detectors, a set of radar detectors, a set of photosensors, a set of seismographs, and a set of anemometers.

6. The computer implemented method of claim 1 wherein the set of multimodal sensors comprises a set of transmitters for transmitting multimodal sensory data over a network connection to a central data processing system for analysis and a set of network protocols for enabling disparate sensors in the set of multimodal sensors to exchange data over the network.

7. The computer implemented method of claim 1 wherein the set of multimodal sensors comprises an array of sensory devices strategically located within the public environment.

8. The computer implemented method of claim 1 further comprising:

aggregating data gathered by each sensor in the set of multimodal sensors using multimodal sensory data processing, wherein the data comprises information associated with a set of objects, and wherein aggregating the data further comprises;

identifying a type of sensor gathering given data received from each sensor in the set of multimodal sensors;

processing the given data received from each sensor based on the type of sensor gathering the given data; and

analyzing the given data to identify a plurality of attributes associated with the set of objects.

9. The computer implemented method of claim 1 wherein the plurality of unique cohort groups is accessible over the network, and further comprising:

accessing the plurality of unique cohort groups by a plurality of disparate entities from a plurality of disparate client devices over the network.

10. The computer implemented method of claim 2 wherein the plurality of sub-cohort groups associated with a set of cohort groups in the plurality of cohort groups further comprises a set of sub-subcohort groups associated with the plurality of sub-cohort groups.

11. A computer program product for generating unique cohort groups using multimodal sensory device, the computer program product comprising:

a computer readable medium;

program code stored on the computer readable medium for receiving multimodal sensory data from a set of multimodal sensors in a public environment, wherein the set of multimodal sensors are associated with a network, and wherein the multimodal sensory data is received from the set of multimodal sensors over the network;

program code stored on the computer-readable medium for processing the multimodal sensory data to generate a plurality of attributes to form cohort attributes; and

program code stored on the computer-readable medium for generating a plurality of unique cohort groups using the cohort attributes and the multimodal sensory data, wherein each member of the cohort group shares at least one common attribute.

12. The computer program product of claim 11 wherein the set of multimodal sensors comprises a set of radio frequency identification tag readers and further comprising:

program code stored on the computer-readable medium for receiving information from radio frequency identification tags associated with a set of cohorts by the set of radio frequency identification tag readers, and program code stored on the computer-readable medium for transmitting the information over the network to a central data processing system by the radio frequency identification tag readers.

13. The computer program product of claim 11 wherein the set of multimodal sensors comprises a set of digital video cameras, wherein the set of digital video cameras captures a stream of video data associated with a set of objects, and wherein the stream of video data is transmitted to a central data processing system in real time as the stream of video data is generated, and further comprising:

program code stored on the computer-readable medium for analyzing the stream of video data by a video analytics engine associated with the central data processing system to generate video metadata describing the set of objects in the stream of video data; and

program code stored on the computer-readable medium for identifying the plurality of attributes associated with the set of objects using the video metadata.

14. The computer program product of claim 11 wherein the set of multimodal sensors comprises at least one of a set of global positioning satellite receivers, a set of infrared sensors, a set of microphones, a set of motion detectors, a set of chemical sensors, a set of biometric sensors, a set of pressure sensors, a set of temperature sensors, a set of metal detectors, a set of radar detectors, a set of photosensors, a set of seismographs, and a set of anemometers.

15. The computer program product of claim 11 further comprising:

program code stored on the computer-readable medium for aggregating data gathered by each sensor in the set of multimodal sensors using multimodal sensory data processing, wherein the data comprises information associated with a set of objects, and wherein aggregating the data further comprises;

program code stored on the computer-readable medium for identifying a type of sensor gathering given data received from each sensor in the set of multimodal sensors;

program code stored on the computer-readable medium for processing the given data received from each sensor based on the type of sensor gathering the given data; and

program code stored on the computer-readable medium for analyzing the given data to identify a plurality of attributes associated with the set of objects.

16. An apparatus comprising:

a bus system;

a communications system coupled to the bus system;

a memory connected to the bus system, wherein the memory includes computer usable program code; and

a processing unit coupled to the bus system, wherein the processing unit executes the computer-usable program code to receive multimodal sensory data from a set of multimodal sensors in a public environment, wherein the set of multimodal sensors are associated with a network, and wherein the multimodal sensory data is received from the set of multimodal sensors over the network;

process the multimodal sensory data to generate a plurality of attributes to form cohort attributes; and

generate a plurality of unique cohort groups using the cohort attributes and the multimodal sensory data, wherein each member of the cohort group shares at least one common attribute.

17. The apparatus of claim 16 wherein the set of multimodal sensors comprises a set of radio frequency identification tag readers, wherein the set of radio frequency identification tag readers receives information from radio frequency identification tags associated with one or more members of the plurality of cohort groups, and wherein the radio frequency identification tag readers transmit the information over the network to a central data processing system.

18. The apparatus of claim 16 wherein the set of multimodal sensors comprises a set of digital video cameras, wherein the set of digital video cameras captures a stream of video data associated with a set of objects, and wherein the stream of video data is transmitted to a central data processing system in real time as the stream of video data is generated, and wherein the processor unit further executes the computer-usable program code to analyze the stream of video data by a video analytics engine associated with the central data processing system to generate video metadata describing the set of objects in the stream of video data;

and identify the plurality of attributes associated with the set of objects using the video metadata.

19. The apparatus of claim 16 wherein the set of multimodal sensors comprises at least one of a set of global positioning satellite receivers, a set of infrared sensors, a set of microphones, a set of motion detectors, a set of chemical sensors, a set of biometric sensors, a set of pressure sensors, a set of temperature sensors, a set of metal detectors, a set of radar detectors, a set of photosensors, a set of seismographs, and a set of anemometers.

20. A data processing system for generating unique cohort groups using multimodal sensory device comprising:

a set of multimodal sensors, wherein each sensor in the set of multimodal sensors comprises a network device that enables the each sensor to communicate using a connection to a wireless network, wherein the each sensor transmits sensor data gathered by the sensor to one or more devices connected to the wireless network, and wherein the each sensor is capable of receiving information from the one or more devices on the wireless network using the network device;

the sensory data processing component, wherein the sensory data processing component multimodal sensory data is received from the set of multimodal sensors over the network, wherein the sensory data processing component processes the multimodal sensory data to generate a plurality of attributes to form cohort attributes; and

a cohort generation engine, wherein the cohort generation engine generates a plurality of unique cohort groups using the cohort attributes and the multimodal sensory data, wherein each member of the cohort group shares at least one common attribute.

21. The data processing system of claim 20 wherein the one or more devices connected to the wireless network comprises at least one sensor in the set of multimodal sensors, and wherein each sensor in the set of multimodal sensors transmits information to the at least one sensor in the set of multimodal sensors using the network device, and wherein the each sensors receives information from the at least one sensor in the set of multimodal sensors using the network device.

22. The data processing system of claim 20 further comprising:

the set of multimodal sensors, wherein the set of multimodal sensors comprises a set of digital video cameras, and wherein the set of multimodal sensors transmits a stream of video data associated with the cohort group to the sensory data processing engine in real time as the stream of video data is captured by the set of digital video cameras to form the sensory data.

23. The data processing system of claim 20 further comprising:

the set of multimodal sensors, wherein the set of multimodal sensors comprises a set of radio frequency identification tag receivers.

24. The data processing system of claim 20 wherein the sensory data processing engine further comprises:

a video analysis system, wherein the video analysis system analyzes a stream of video data received from at least one digital video camera in the set of multimodal sensors, wherein the video analysis system generates metadata describing contents of the stream of video data, and wherein the sensory data processing engine identifies events associated with behavior of cohorts using the metadata.

25. The data processing system of claim 20 further comprising:

the set of multimodal sensors, wherein the set of multimodal sensors comprises at least one of a set of global positioning satellite receivers, a set of infrared sensors, a set of microphones, a set of motion detectors, a set of chemical sensors, a set of biometric sensors, a set of pressure sensors, a set of temperature sensors, a set of metal detectors, a set of radar detectors, a set of photosensors, a set of seismographs, and a set of anemometers.