VIRTUAL RFID-BASED TAG SENSOR

• US 20080042830A1
• Filed: 06/21/2007
• Published: 02/21/2008
• Est. Priority Date: 12/30/2005
• Status: Abandoned Application

• Current Assignee: GSI Group Corporation (Novanta Inc.)
• Original Assignee: SkyeTek, Inc. (RFID Holdings, Inc.)
• Inventors: Chakraborty, Sayan, McKinney, Brian
• Application Number:
  US11/766,588
• Publication Number:
  US 20080042830A1
• Time in Patent Office: Days
• US Class Current: 340/540
• CPC Class Codes: G06K 19/0717 the sensor being capable of sensing environmental conditions such as temperature history or pressure
• CPC Class Codes: G06K 7/0008 General problems related to the reading of electronic memory record carriers, independent of its reading method, e.g. power transfer
• CPC Class Codes: G08B 21/14 Toxic gas alarms G08B21/16 takes precedence
• CPC Class Codes: G08B 31/00 Predictive alarm systems characterised by extrapolation or other computation using updated historic data

Abstract

A method for implementing a virtual sensor in an RFID tag reading system, including an RFID reader and at least one RFID tag having tag memory in which sensor data is stored. Initially, sensor data is read from the tag memory. The sensor data is then stored in sensor cache memory in the reader. Sensor data is accordingly read and stored at a predetermined interval. The sensor data in sensor cache memory is periodically updated, via predictive modeling software stored in and executed by the reader, to determine a present or future estimated value for the sensor data from observed changes in the data.

Claims

1. A method for implementing a virtual sensor in an RFID tag reading system including an RFID reader and at least one RFID tag including tag memory in which sensor data, read from a sensor, is stored, the method comprising:

(a) reading the sensor data from the tag memory;

(b) storing the sensor data in sensor cache memory in the reader;

(c) repeating steps (a) and (b) at a predetermined interval; and

(d) periodically updating the sensor data in the sensor cache memory, via predictive modeling software stored in and executed by the reader, to determine an estimated value for the sensor data from observed changes in the data.

2. The method of claim 1, wherein the RFID tag samples a sensor at a predetermined rate and accordingly updates, in the tag memory, the sensor data thus sampled.

3. The method of claim 2, wherein the step of periodically updating the sensor data in the sensor cache includes collecting trending data, comprising multiple time-stamped samples of sensor data, to determine a present estimated value for the sensor data.

4. The method of claim 3, wherein the interval in step (c) is based on the trending data.

5. The method of claim 1, wherein the RFID tag samples the sensor at a modifiable rate based on a rate-of-change analysis of the sensor data, and accordingly updates, in the tag memory, the sensor data thus sampled.

6. The method of claim 2, wherein the step of periodically updating the sensor data in the sensor cache includes collecting trending data, comprising multiple time-stamped samples of the sensor data, to determine a present estimated value for the sensor data and a rate of change of the sensor data.

7. The system of claim 1, including providing the sensor data, stored in the sensor cache memory, to a requesting entity, without again reading the sensor data presently stored in the tag.

8. The method of claim 1, wherein the reader sends, to a tag processing system, the data updated in the sensor cache, without again reading the sensor data presently stored in the tag.

9. The method of claim 1, wherein the sensor data stored in the sensor cache includes data associated with the tag, but not stored thereon.

10. The method of claim 1, including:

determining that the tag is moving toward a second RFID reader; and

sending the second reader at least part of the sensor data stored in sensor cache in advance of the tag'"'"'s arrival at the second reader.

11. The method of claim 1, wherein the estimated value for the sensor data is a present estimated value.

12. The method of claim 1, wherein the estimated value for the sensor data is a future estimated value.

13. The method of claim 1, wherein the estimated value for the sensor data is a mathematical model based on outputs of multiple sensors presented as the output of a single simulated sensor.

19. The method of claim 4, wherein the RFID tag samples a sensor at a modifiable rate based on a rate-of-change analysis of the sensor data, and accordingly updates, in the tag memory, the sensor data thus sampled.

20. The method of claim 19, wherein the step of periodically updating the sensor data in the sensor cache includes collecting trending data, comprising multiple time-stamped samples of the sensor data, to determine a present estimated value for the sensor data as well as a rate of change of that data.

21. The method of claim 1, wherein the estimated value for the sensor data is a mathematical model based on the outputs of multiple sensors presented as the output of a single simulated sensor.

14. A method for implementing a virtual sensor in an RFID tag reading system including an RFID reader and at least one RFID tag including tag memory in which sensor data, read from a sensor, is stored, the method comprising:

(a) periodically sampling sensor data and storing the data in the tag memory;

(b) reading the sensor data from the tag memory;

(c) storing the data thus read in sensor cache memory in the reader;

(d) periodically updating sensor data in the sensor cache memory using a predictive modeling technique;

(e) after a delay period has expired, again reading sensor data stored in the tag memory; and

(f) repeating steps (b) through (e) at a predetermined interval.

15. The method of claim 14, including:

determining that the tag is moving toward a second RFID reader; and

sending the second reader at least part of the sensor data in the sensor cache in advance of the tag'"'"'s arrival at the second reader.

16. The method of claim 14, wherein the step of periodically updating the sensor data in the sensor cache includes:

collecting trending data, comprising multiple time-stamped samples of sensor data, to determine a future estimated value for the sensor data.

17. The system of claim 16, including providing the future estimated value to a requesting entity, without again reading the sensor data presently stored in the tag.

18. The method of claim 14, wherein the reader sends, to a tag processing system, the data updated in the sensor cache, without again reading the sensor data presently stored in the tag.

22. A method for implementing a virtual sensor in an RFID tag reading system including an RFID reader and a plurality of RFID tags, each of which periodically samples an associated sensor and stores sensor data thus sampled in a respective RFID tag memory, the method comprising:

systematizing the plurality of RFID tags to form a grid;

reading the sensor data from the tag memory in each of the tags in the grid;

storing the sensor data thus read in sensor cache memory in the reader; and

periodically updating the sensor data in the sensor cache memory, using a predictive modeling technique, to determine an estimated value for the sensor data from observed changes in the data read from the sensors.

23. The method of claim 22, wherein the estimated value for the sensor data is a present estimated value, calculated without again reading the sensor data presently stored in the tag.

24. The method of claim 22, wherein the estimated value for the sensor data is a future estimated value, calculated without again reading the sensor data presently stored in the tag.

25. The method of claim 22, wherein the RFID tag samples the sensor at a modifiable rate based on a rate-of-change analysis of the sensor data, and accordingly updates, in the tag memory, the sensor data thus sampled.

26. The method of claim 25, wherein the step of periodically updating the sensor data in the sensor cache includes collecting trending data, comprising multiple time-stamped samples of the sensor data, to determine a present estimated value for the sensor data and a rate of change of the sensor data.

27. The method of claim 22, wherein the sensor data is read from the tag memory is based on the trending data.

28. The method of claim 22, wherein the estimated value for the sensor data is a mathematical model based on the outputs of multiple sensors presented as the output of a single simulated sensor

29. The method of claim 22, wherein the step of periodically updating the sensor data in the sensor cache includes:

collecting trending data, comprising multiple time-stamped samples of sensor data, to determine a future estimated value for the sensor data;

generating a sensor data map indicating the location of each said sensor in the grid and the sensor data associated therewith; and

extrapolating the sensor data in the map, using the trending data, to indicate a future state of sensor data relative to the sensor grid.

30. A system for implementing a virtual sensor in an RFID tag reading system including an RFID tag that periodically samples a sensor and stores sampled sensor data in tag memory, the system comprising:

an RFID reader including cache memory; and

predictive modeling software stored in the reader;

wherein the sensor data is;

read from the memory of the RFID tag by the reader;

stored in the cache memory in the reader; and

periodically updated in the cache memory, using the predictive modeling software executed by the reader.

31. The system of claim 30, wherein the tag reading system includes a plurality of RFID tags, each of which periodically samples an associated sensor and stores sensor data thus sampled in a respective RFID tag memory, the system further including:

trending data, stored in the cache memory, comprising multiple time-stamped samples of the sensor data; and

a sensor data map, stored in the cache memory, indicating the location of each said sensor in the system and the sensor data associated therewith;

wherein estimated future values for the sensor data stored in the sensor data map are determined by the predictive modeling software using the trending data.