Method and system for autonomous correlation of sensed environmental attributes with entities

• US 20060061476A1
• Filed: 09/23/2004
• Published: 03/23/2006
• Est. Priority Date: 09/23/2004
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Cole, Alan George, Munson, Jonathan Paul, Chen, Han, Wood, David, Moskowitz, Paul Andrew, Patil, Abhishek
• Granted Patent: US 7,271,702 B2
• Time in Patent Office: Days
• US Class Current: 340/572.400
• CPC Class Codes: G01S 13/878 Combination of several spaced transmitters or receivers of known location for determining the position of a transponder or a reflector G01S13/874 takes precedence
• CPC Class Codes: G01S 5/0027 of actual mobile position, i.e. position determined on mobile
• CPC Class Codes: G01S 5/0284 Relative positioning
• CPC Class Codes: G06K 7/10079 the collision being resolved in the spatial domain, e.g. temporary shields for blindfolding the interrogator in specific directions
• CPC Class Codes: G06Q 10/08 Logistics, e.g. warehousing, loading or distribution; Inventory or stock management

Abstract

A method for determining attributes of entities within a physical space. More specifically, the location of the entities in the physical space are determined using this invention. A reader automatically moves throughout the space and takes measurements of the attributes of corresponding entities when it detects the presence of these entities in the physical space. The attributes of the entities could be the location, temperature and so forth. The reader could be an RF detection device for reading signals from the tags attached to the entities.

Claims

1. A method for determining a corresponding attribute for each of a plurality of entities within a physical space, said method comprising:

detecting the presence of entities in said physical space by detecting the presence of beaconing devices associated with said entities using a reader which automatically moves throughout said space;

taking measurements of a variable in response to the detection of the presence of any of said entities in said physical space as said reader moves in said space; and

processing said measurements of said variable, wherein each of corresponding set of said processed measurements represents a corresponding attribute of a corresponding one of said entities.

2. A method as recited in claim 1, wherein said variable is a location of a reader, which is used to detect the presence of said entities.

3. A method as recited in claim 1, wherein said corresponding attribute is a location of a corresponding one of said entities.

4. A method as recited in claim 1, wherein said processing comprises using an algorithm that is automatically applied to said measurements using a computer processor.

5. A method as recited in claim 4, wherein, for each of said entities, said algorithm automatically processes said measurements of said variable to generate corresponding circles, each circle representing an area which, with high probability, contains said each entity, and said algorithm estimates the position of said each entity to be the center of an intersecting area of said circles.

6. A method as recited in claim 1, wherein said reader automatically moves in said space by attaching it to a robot which is programmed to automatically move in said space.

7. A method as recited in claim 1, wherein the identity of any of said beaconing devices and a corresponding value of said variable is recorded in a detection record for a corresponding one of said entities when said any of said beaconing devices is detected in said space.

8. A method as recited in claim 1, in which said algorithm comprises statistically averaging the location estimates of said reader along the two spatial dimensions separately.

9. A method as recited in claim 1, wherein said entities are at least one of the following:

a museum exhibits, a cars in a parking lot, an inventory items in a warehouse, shipping containers in a port facility, people within a meeting space, and animals within an enclosure, books within a library.

10. A method as recited in claim 4, wherein said algorithm comprises taking a weighted average of the positions of the reader as moves in said physical space, where the weight of each position is inversely proportional to the second power of the reader location estimate'"'"'s error radius.

11. A system for determining a corresponding attribute for each of a plurality of entities within a physical space, said system comprising:

a beaconing device associated with each of said entities;

a reader which automatically moves throughout said space, said reader for detecting the presence of any one of said beaconing devices associated with a corresponding one of said entities;

a measuring device for measuring a variable in response to the detection of the presence of any of said entities in said physical space as said reader moves in said space; and

a processor for processing said measurements of said variable, wherein each of corresponding set of said processed measurements represents a corresponding attribute of a corresponding one of said entities.

12. A system as recited in claim 11, wherein said beaconing device is an RFID tag.

13. A system as recited in claim 11, wherein said measuring device is an RFID tag reader.

14. A system as recited in claim 13, wherein said reader is attached to a robot which is programmed to automatically move in said physical space.

15. A system as recited in claim 11, wherein said measuring device is a bar code reader.

16. A system as recited in claim 11, wherein said attribute of a corresponding one of said entities is the location of said entity.

17. A system as recited in claim 11, wherein said variable is the location of said measuring device.

18. A system as recited in claim 11, wherein said measuring device is at least one of the following:

a triangulation apparatus, and a pulse delay triangulation apparatus.

19. A method for determining a corresponding location for each of a plurality of entities within a physical space, said method comprising:

detecting the presence of entities in said physical space by detecting the presence of beaconing devices associated with said entities using a reader which automatically moves throughout said space;

taking measurements corresponding to a location of said reader in response to the detection of the presence of any of said entities in said physical space as said reader moves in said space; and

processing said measurements, wherein each of corresponding set of said processed measurements represents a corresponding location of a corresponding one of said entities.

20. A method as recited in claim 19, wherein said step of taking measurements comprises measuring signal strengths from wireless access points in said space and wherein said signal strength measurements are processed to determine a corresponding location of said reader and to then determine locations of corresponding entities in said space.

21. A method as recited in claim 20, wherein said step of taking measurements is repeated for a number of different locations of said reader as it moves in said space, wherein said measurements for said different locations are further processed to more accurately determine said corresponding locations of said entities in said space.

22. A method as recited in claim 21, wherein said step of further processing said measurements comprises taking the intersection of circles about said determined locations of said reader, wherein said intersections of said circles correspond to the location of a corresponding entity in said space.

23. A method as recited in claim 19, wherein processing said measurements comprises

computing the statistical average of locations of said reader when a corresponding entity was detected in said space.

24. A method as recited in claim 19, wherein processing said measurements comprises

computing a weighted average of locations of said reader when a corresponding entity was detected in said space.

25. A method as recited in claim 24, wherein said weighted average is computed by using a corresponding inverse square of an error radius of corresponding ones of said circles for each weight factor for each location.

26. A method as recited in claim 19, wherein processing said measurements comprises computing the mean of each of the coordinates of the locations of said reader when a corresponding entity was detected in said space.