AUTOMATIC, ADAPTIVE AND OPTIMIZED SENSOR SELECTION AND VIRTUALIZATION

• US 20130096831A1
• Filed: 10/18/2011
• Published: 04/18/2013
• Est. Priority Date: 10/18/2011
• Status: Abandoned Application

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Chan, Hoi Yeung, Das, Rajarshi, Lenchner, Jonathan
• Application Number:
  US13/275,827
• Publication Number:
  US 20130096831A1
• Time in Patent Office: Days
• US Class Current: 702/1
• CPC Class Codes: G06Q 10/00 Administration; Management
• 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: H04W 4/38 for collecting sensor information

Abstract

A system, method and computer program product for managing sensors. One example of embodiment includes a data reader to receive sensor measurements from sensors. A user value collector receives user values from users representing a user'"'"'s measurement of an abstract concept. A data store saves the sensor measurements and the user values in computer readable memory. The system further includes a virtual sensor generator. The virtual sensor generator determines a mapping function based on the stored sensor measurements and user values. Furthermore, given a new set of sensor measurements from the sensors, the virtual sensor generator employs the mapping function to generate a new virtual sensor value.

Claims

1. A system for managing sensors, the system comprising:

a data reader to receive sensor measurements from physical sensors;

a user value collector to receive user values from users representing a user'"'"'s measurement of an abstract concept; and

a data store to store the sensor measurements and the user values; and

a virtual sensor generator to;

determine a mapping function based on the stored sensor measurements and user values; and

generate a virtual sensor using the mapping function and the sensor measurements from the sensors.

2. The system of claim 1, wherein the sensor measurements received by the data reader includes measurements from at least one of a physical sensor and a previously generated virtual sensor.

3. The system of claim 1, wherein the virtual sensor is generated by assigning computational weights to a least one of physical component sensors and virtual component sensors derived by optimizing the ability of the physical and virtual component sensors to predict the value of the virtual sensor.

4. The system of claim 1, wherein the virtual sensor generator is further configured to automatically update the mapping function when new information is stored in the data store, the new information including at least one of a new measurement from the sensors and a new user value.

5. The system of claim 1, wherein the virtual sensor generator is further configured to use a distance metric to generate the virtual sensor.

6. The system of claim 5, wherein the distance metric is based on a user'"'"'s assignment of values to the abstract concept measured by the virtual sensor and is automatically adjusted to derive maximum predictive power for the user or group of users assignment of value to the abstract concept over time.

7. The system of claim 1, wherein the virtual sensor generator is further configured to:

transform the sensor measurements within a multidimensional space;

select the sensors providing nearest points in the multidimensional space relative to the mapping function; and

assign computational weights to the sensors.

8. The system of claim 7, wherein, for each sensor, the set of possible sensor readings represents a separate dimension in the multidimensional space.

9. A method for managing sensors, the method comprising:

receiving sensor measurements from sensors; and

receiving user values from users representing a user'"'"'s measurement of an abstract concept; and

storing the sensor measurements and the user values; and

determining a mapping function based on the stored sensor measurements and user values; and

generating a virtual sensor using the mapping function and the stored sensor measurements from the sensors.

10. The method of claim 9, wherein receiving sensor measurements from the sensors includes receiving the sensor measurements from at least one of a physical sensor and a previously generated virtual sensor.

11. The method of claim 9, wherein generating the virtual sensor includes assigning a computational weight to each of the sensors.

12. The method of claim 9, further comprising automatically updating the mapping function when new information is stored in a database, the new information including at least one of a new sensor measurement from the sensors and a new user value.

13. The method of claim 9, wherein generating the virtual sensor includes using a distance metric.

14. The system of claim 13, wherein the distance metric is based on a user'"'"'s assignment of value to the abstract concept to be predicted by the virtual sensor and is automatically adjusted to drive maximum predictive capability for the user or group of users over time.

15. The method of claim 14, further comprising:

transforming the sensor measurements within a multidimensional space;

selecting the sensors providing nearest points in the multidimensional space relative to the mapping function; and

assigning computational weights to the sensors.

16. The method of claim 15, wherein, for each sensor, the set of possible sensor readings represents a separate dimension in the multidimensional space.

17. A computer program product for managing sensors comprising:

a computer readable storage medium having computer readable program code embodied therewith, the computer readable program code configured to;

receive sensor measurements from sensors; and

receive user values from users representing a user'"'"'s measurement of an abstract concept; and

store the sensor measurements and the user values; and

determine a mapping function based on the stored sensor measurements and user values; and

generate a virtual sensor using the mapping function and the sensor measurements from the sensors.

18. The computer program product of claim 17, wherein the computer readable program code for receiving the sensor measurements includes computer readable program code for receiving the sensor measurements from at least one of a physical sensor and a previously generated virtual sensor.

19. The computer program product of claim 17, wherein the computer readable program code for generating the virtual sensor includes the computer readable program code for assigning a computational weight to each of the sensors.

20. The computer program product of claim 17, further comprising computer readable program code for automatically updating the mapping function when new information is stored in a data store, the new information including at least one of a new sensor measurement from sensors and a new user value.

21. The computer program product of claim 17, wherein the computer readable program code for generating the virtual sensor includes the computer readable program code for using a distance metric.

22. The computer program product of claim 21, wherein the distance metric is based on a user'"'"'s utility and is automatically adjusted to drive maximum utility for the users over time.

23. The computer program product of claim 17, wherein the computer readable program code for generating the virtual sensor includes the computer readable program code for:

transforming the sensor measurements within a multidimensional space;

selecting the sensors providing nearest points in the multidimensional space relative to the mapping function; and

assigning computational weights to the sensors.