System and method for dynamically tracking and state forecasting tagged entities

• US 7,675,412 B2
• Filed: 02/27/2007
• Issued: 03/09/2010
• Est. Priority Date: 02/27/2006
• Status: Active Grant

• Current Assignee: Createasoft Incorporated
• Original Assignee: Hosni I. Adra
• Inventors: Adra, Hosni I.
• Primary Examiner(s): Goins; Davetta W
• Assistant Examiner(s): Lau; Hoi C
• Application Number:
  US11/679,514
• Publication Number:
  US 20070203768A1
• Time in Patent Office: 1,106 Days
• Field of Search: 340/572.1, 340/539.13, 340/539.21, 340/539.23, 340/825.36, 340/825.49, 340/573.1, 340/573.4, 340/10.1, 340/5.1, 340/522, 705/7, 235/376, 235/382, 235/384, 235/451, 235/375
• US Class Current: 340/539.13
• 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 2013/466 by Trilateration, i.e. two antennas or two sensors determine separately the distance to a target, whereby with the knowledge of the baseline length, i.e. the distance between the antennas or sensors, the position data of the target is determined
• CPC Class Codes: G01S 5/0294 Trajectory determination or predictive filtering, e.g. target tracking or Kalman filtering
• CPC Class Codes: G06Q 10/04 Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem" market predictions or forecasting for commercial activities G06Q30/0202
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: G06Q 10/08 Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
• CPC Class Codes: G08B 13/14 by lifting or attempted removal of hand-portable articles

Abstract

A method is provided for dynamically tracking a plurality of entities progressing through an operation each having an electronic tagging device associated therewith. The method includes sensing signals emitted by each of the plurality of tagging devices, at predetermined instances or when triggered by external events, by a plurality of sensors located at predetermined sites with respect to the operation, each signal including information uniquely identifying the corresponding tagging device, communicating the sensed signals and corresponding energy levels at which they were sensed by each of the plurality of sensors to a data processor, processing the unique identification information provided by the signals and their energy levels to determine a location of each tagging device relatively to the predetermined sites of the sensors, and dynamically updating a path of each tagging device and the associated entity based on the determined location with respect to at least a portion of a displayed map of the operation.

Claims

1. A method for dynamically tracking a plurality of entities progressing through an operation each having an electronic tagging device associated therewith, said method comprising:

sensing signals emitted by each of the plurality of tagging devices, at predetermined instances or when triggered by external events, by a plurality of sensors located at predetermined sites with respect to the operation, each signal including information uniquely identifying the corresponding tagging device;

communicating the sensed signals and corresponding energy levels at which they were sensed by each of the plurality of sensors to a data processor;

processing the unique identification information provided by the signals and their energy levels to determine a location of each tagging device relatively to the predetermined sites of the sensors;

dynamically updating a path of each tagging device and the associated entity based on the determined location with respect to at least a portion of the operation;

determining that a first of the plurality of tagging devices and a second one of the plurality of tagging devices are progressing in close proximity to each other through the operation, when a distance between the dynamically updated paths of each of the first and second tagging devices remains smaller than a predetermined physical dimension during a segment of time; and

determining whether the first tagging device and the second tagging device are correlated to one another based on corresponding unique identification information, and utilizing the determined correlation to improve a forecast of a flow of the operation; and

synchronizing internal clocks of the tagging devices with internal clocks of the sensors to improve the accuracy of the signal time-stamps and minimize noise; and

time-stamping the emitted signals via the internal clocks internal of the tagging devices.

2. The method for dynamically tracking a plurality of entities as in claim 1, wherein determining the location of each tagging device relatively to the predetermined sites of the sensors comprises:

performing a triangulation computation by intersecting at least three spheres centered at corresponding sensors and having each a radius distancing the tagging device to one of the sensors.

3. The method for dynamically tracking plurality of entities as in claim 2, further comprising:

determining an elevation of the location of each tagging device based on results of the triangulation computation.

4. The method for dynamically tracking plurality of entities as in claim 3, wherein the determined elevation of the location of each tagging device corresponds to a floor, a sub-floor, a stack or a shelve on the stack associated with a structure utilized in the operation.

5. The method for dynamically tracking a plurality of entities as in claim 1, further comprising:

dynamically connecting consecutively determined locations of the plurality of entities on a displayed map thereby displaying paths taken by the plurality of entities during the operation as continuous lines.

6. The method for dynamically tracking a plurality of entities as in claim 1, further comprising:

storing all data indicative of properties of the plurality of tagged entities and of their historical progress through the operation; and

replaying the historical progress of any individual entity or of a select subset of the plurality of entities.

7. The method for dynamically tracking a plurality of entities as in claim 6, further comprising:

performing a statistical analysis using stored data to evaluate a performance of the operation.

8. The method for dynamically tracking a plurality of entities as in claim 6, further comprising:

performing a historical analysis using stored data to analyze problems or issues encountered during the recorded life of the operation.

9. The method for dynamically tracking a plurality of entities as in claim 6, further comprising:

retrieving stored properties, constraints, and historical data corresponding to both the plurality of entities and the operation; and

simulating a flow of the operation based the retrieved stored data to forecast a behavior of each of the plurality of entities through the operation and of the operation.

10. The method for dynamically tracking a plurality of entities as in claim 9, further comprising:

storing dynamically data collected during the simulation; and

analyzing the simulation data to determine problems related to the flow of the operation and to the behavior of each of the plurality of entities during the simulation.

11. The method for dynamically tracking a plurality of entities as in claim 10, further comprising:

determining at least one modification to the properties and constraints to mitigate at least one of the problems determined during the simulation of the flow of the operation.

12. The method for dynamically tracking a plurality of entities as in claim 10, further comprising:

determining at least one modification to the properties and constraints to optimize the flow of the operation.

16. A computer system comprising one or more computers configured to perform the method of claim 1.

13. A method for dynamically tracking a plurality of entities progressing through an operation each having an electronic tagging device associated therewith, the operation having a plurality of processing stations configured to process the plurality of tagged entities, and each of the stations and each of the plurality of entities is attributed a corresponding set of value stream metrics, said method comprising:

sensing signals emitted by each of the plurality of tagging devices, at predetermined instances or when triggered by external events, by a plurality of sensors located at predetermined sites with respect to the operation, each signal including information uniquely identifying the corresponding tagging device;

communicating the sensed signals and corresponding energy levels at which they were sensed by each of the plurality of sensors to a data processor;

processing the unique identification information provided by the signals and their energy levels to determine a location of each tagging device relatively to the predetermined sites of the sensors;

dynamically updating a path of each tagging device and the associated entity based on the determined location with respect to at least a portion of the operation; and

determining that one of the plurality of entities is progressing through the operation within physical dimensions of another one of the plurality of entities, which is also progressing through the operation, when a distance between the tracked locations of the two entities remains smaller than one of the physical dimensions of the another one of the plurality of the entities;

dynamically updating the value stream metrics to provide a dynamic value stream map of the operation.

14. The method for dynamically tracking a plurality of entities as in claim 13, further comprising:

forecasting the dynamic value stream map based on collected data.

15. The method for dynamically tracking a plurality of entities as in claim 13, further comprising:

dynamically displaying multiple dynamic stream values at selected stations to provide a dynamic value network map.