Dynamic scan context determination for asset reconciliation background

• US 9,934,486 B2
• Filed: 04/28/2016
• Issued: 04/03/2018
• Est. Priority Date: 05/01/2012
• Status: Active Grant

• Current Assignee: Hand Held Products Incorporated (Honeywell International Inc.)
• Original Assignee: Hand Held Products Incorporated (Honeywell International Inc.)
• Inventors: Vargas, Joseph, Plocher, Tom, Wang, Ynjiun Paul
• Primary Examiner(s): Backer, Firmin
• Assistant Examiner(s): Aziz, Adnan
• Application Number:
  US15/140,804
• Publication Number:
  US 20160239797A1
• Time in Patent Office: 705 Days
• Field of Search: None
• CPC Class Codes: B62B 3/1424 Electronic display devices
• CPC Class Codes: G06K 19/072 the record carrier comprising a plurality of integrated circuit chips
• CPC Class Codes: G06K 19/0723 the record carrier comprising an arrangement for non-contact communication, e.g. wireless communication circuits on transponder cards, non-contact smart cards or RFIDs
• CPC Class Codes: G06K 19/0727 the arrangement being a circuit facilitating integration of the record carrier with a hand-held device such as a smart phone of PDA
• CPC Class Codes: G06Q 10/08 Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
• CPC Class Codes: G06Q 10/0833 Tracking
• CPC Class Codes: G06Q 10/087 Inventory or stock management, e.g. order filling, procurement or balancing against orders
• CPC Class Codes: G06Q 20/203 Inventory monitoring
• CPC Class Codes: H04B 5/45 Transponders
• CPC Class Codes: H04B 5/77 for interrogation

Abstract

Asset reconciliation is facilitated by dynamically determining and applying a scan context to asset-describing tag data. Tag data representative of assets are received from RFID tags. A working scan context defining a scope of coverage of assets to be included in an asset reconciliation is dynamically determined based on the received tag data. Additional tag data representative of additional assets are received, and the dynamically determined working scan context is applied to the additional tag data to automatically identifying which assets of the additional assets are to be included in the asset reconciliation. Assets included in the scope of coverage of the working scan context are included in the asset reconciliation, and assets not included in the scope of coverage of the working scan context are not included in the asset reconciliation.

Claims

1. A method for asset reconciliation, comprising:

receiving tag data from a plurality of radio frequency identification tags carrying the tag data, the tag data representative of a plurality of assets;

identifying characteristics about each of the plurality of assets based on at least a portion of each respective tag data;

grouping a first plurality of assets based on a common characteristic of the first plurality of assets identified in each respective tag data;

receiving additional tag data from one or more additional radio frequency identification tags associated with one or more additional assets having at least one characteristic; and

identifying which assets of the one or more additional assets are to be included in the first plurality of assets when the common characteristic is included within the additional tag data of the one or more additional assets; and

dynamically switching the first plurality of assets to a different grouping of assets, based on the received tag data from the one or more additional radio frequency identification tags, the dynamically switching being responsive to satisfying a condition for switching the first plurality of assets.

2. The method of claim 1, wherein responsive to the tag data of another radio frequency identification tag of the one or more additional radio frequency identification tags being representative of an asset not within a scope of coverage defined by the first plurality of assets, the asset is excluded from inclusion in the asset reconciliation.

3. The method of claim 1, wherein tag data of each radio frequency identification tag of the plurality of radio frequency identification tags comprises indications of asset properties of the asset represented by the tag data of the respective radio frequency identification tag, and wherein identifying characteristics about each of the plurality of assets comprises identifying, based on the indications of asset properties in the tag data of the plurality of radio frequency identification tags, commonality between multiple assets of the plurality of assets.

4. The method of claim 3, wherein the identifying commonality comprises:

performing data mining on the tag data from the plurality of radio frequency identification tags to identify the indications of asset properties thereof;

clustering tag data from radio frequency identification tags of the plurality of radio frequency identification tags according to at least one matching indication of asset properties, to form at least one cluster of tag data from radio frequency identification tags of the plurality of radio frequency identification tags; and

selecting a cluster from the at least one cluster, wherein the first plurality of assets comprises the selected cluster.

5. The method of claim 4, wherein the matching indication of asset properties comprises a matching global trade item number encoded in the tag data.

6. The method of claim 4, wherein the matching indication of asset properties includes matching information determined from a global trade item number encoded in the tag data, wherein the matching information indicates at least one of:

a matching Universal Product Code, a matching European Article Number, a matching asset manufacturer, or a matching product type.

7. The method of claim 4, wherein the selected cluster comprises a cluster of the at least one cluster having a greatest number of assets represented by tag data therein.

8. The method of claim 4, further comprising, subsequent to the identifying which assets of the one or more additional assets are to be included in the first plurality of assets:

receiving tag data from further radio frequency identification tags;

performing data mining on the tag data from the further radio frequency identification tags and clustering tag data from radio frequency identification tags of the further radio frequency identification tags according to at least one matching identified indication of asset properties, wherein the received tag data from the further radio frequency identification tags are added to at least one of;

a cluster of the one or more clusters or a newly formed cluster; and

dynamically switching the first plurality of assets to a different grouping of assets, based on the received tag data from the further radio frequency identification tags, the dynamically switching being responsive to satisfying a condition for switching the first plurality of assets.

9. The method of claim 8, wherein the condition for switching the first plurality of assets comprises reaching a threshold amount of time since tag data from a radio frequency identification tag was added to the selected cluster, wherein the dynamically switching comprises switching the first plurality of assets responsive to determining that no tag data was added to the selected cluster within the threshold amount of time, and wherein the different grouping of assets comprises a different cluster than the selected cluster, the different cluster being a cluster of the one or more clusters or the newly formed cluster.

10. The method of claim 8, wherein the condition for switching the first plurality of assets comprises a growth rate of a different cluster than the selected cluster exceeding a growth rate of the selected cluster by a threshold difference in growth rates, the different cluster being a cluster of the one or more clusters or the newly formed cluster, wherein the dynamically switching comprises switching the first plurality of assets responsive to determining that the growth rate of the different cluster exceeds the growth rate of the selected cluster by at least the threshold difference in growth rates, and wherein the different grouping of assets comprises the different cluster.

11. The method of claim 1, further comprising determining a confidence level for the first plurality of assets, the confidence level indicating a level of confidence about the grouping of the first plurality of assets, and automatically grouping the first plurality of assets responsive to the confidence level exceeding a predefined threshold confidence level.

12. The method of claim 1, further comprising presenting to a user the first plurality of assets for approval, and receiving input from the user indicating that the first plurality of assets is approved.

13. The method of claim 1, further comprising:

receiving a predefined asset reconciliation list comprising a list of assets to be included in the asset reconciliation; and

predefining, based on the received predefined asset reconciliation list, a working scan context prior to receiving the tag data of the plurality of radio frequency identification tags, the predefined working scan context based on assets reflected in the predefined asset reconciliation list, the assets in the predefined asset reconciliation list being assets in a database against which the asset reconciliation is to be performed, wherein the predefined working scan context defines a scope of coverage of assets reflected in the database, and wherein the first plurality of assets is grouped based, at least in part, on the predefined working scan context.

14. A system for asset reconciliation, the system comprising:

a processor configured to perform;

receiving tag data from a plurality of radio frequency identification tags carrying the tag data, the tag data representative of a plurality of assets;

identifying characteristics about each of the plurality of assets based on at least a portion of each respective tag data;

grouping a first plurality of assets based on a common characteristic of the characteristics of the first plurality of assets identified in each respective tag data;

receiving additional tag data from one or more additional radio frequency identification tags carrying the additional tag data, the additional tag data representative of one or more additional assets and including at least one characteristic of the one or more additional assets;

identifying which assets of the one or more additional assets are to be included in the first plurality of assets when the common characteristic is included within the additional tag data of the one or more additional assets; and

dynamically switching the first plurality of assets to a different grouping of assets, based on the received tag data from the one or more additional radio frequency identification tags, the dynamically switching being responsive to satisfying a condition for switching the first plurality of assets.

15. The system of claim 14, wherein tag data of each radio frequency identification tag of the plurality of radio frequency identification tags comprises indications of asset properties of the asset represented by the tag data of the respective radio frequency identification tag, and wherein identifying characteristics about each of the plurality of assets comprises identifying, based on the indications of asset properties in the tag data of the plurality of radio frequency identification tags, commonality between multiple assets of the plurality of assets, wherein the identifying commonality comprises:

performing data mining on the tag data from the plurality of radio frequency identification tags to identify the indications of asset properties thereof;

clustering tag data from radio frequency identification tags of the plurality of radio frequency identification tags according to at least one matching indication of asset properties, to form at least one cluster of tag data from radio frequency identification tags of the plurality of radio frequency identification tags; and

selecting a cluster from the at least one cluster, wherein the first plurality of assets comprises the selected cluster.

16. The system of claim 15, wherein the matching indication of asset properties comprises at least one of:

a matching global trade item number encoded in the tag data, a matching Universal Product Code derived from the global trade item number encoded in the tag data, a matching European Article Number derived from the global trade item number encoded in the tag data, a matching asset manufacturer derived from the global trade item number encoded in the tag data, or a matching product type derived from the global trade item number encoded in the tag data.

17. The system of claim 15, wherein the system is further configured to perform, subsequent to the identifying which assets of the one or more additional assets are to be included in the first plurality of assets:

receiving tag data from further radio frequency identification tags;

performing data mining on the tag data from the further radio frequency identification tags and clustering tag data from radio frequency identification tags of the further radio frequency identification tags according to at least one matching identified indication of asset properties, wherein the received tag data from the further radio frequency identification tags are added to at least one of;

a cluster of the one or more clusters or a newly formed cluster; and

dynamically changing the first plurality of assets to a different grouping of assets, based on the received tag data from the further radio frequency identification tags, the dynamically changing being responsive to satisfying a condition for changing the first plurality of assets.

18. A method for asset reconciliation, the method comprising:

receiving tag data which identifies characteristics about each of a plurality of assets;

determining, by at least one processor, a first plurality of assets based on a common characteristic of the identified characteristics of the first plurality of assets identified in each respective tag data;

after the determining, receiving additional tag data from one or more radio frequency identification tags carrying the tag data, the additional tag data representative of one or more additional assets; and

identifying which assets of the one or more assets are to be included in the first plurality of assets when the common characteristic is included within the additional tag data of the one or more additional assets;

dynamically switching the first plurality of assets to a second grouping of assets having a common characteristic, based on the received tag data from the one or more additional radio frequency identification tags, the dynamically switching being responsive to satisfying a condition for switching the first plurality of assets; and

displaying, on a display screen, the second grouping of assets rather than the first plurality of assets responsive to satisfying a condition for switching the first plurality of assets.

19. The method of claim 18, wherein determining the first plurality of assets comprises defining at least one cluster for performing clustering on the received tag data based on a matching indication of asset properties indicated in tag data, wherein the matching indication of asset properties comprises at least one of:

a global trade item number encoded in the tag data, a Universal Product Code derived from the global trade item number encoded in the tag data, a European Article Number derived from the global trade item number encoded in the tag data, an asset manufacturer derived from the global trade item number encoded in the tag data, or a product type derived from the global trade item number encoded in the tag data.

20. The method of claim 18, wherein determining the first plurality of assets comprises defining at least one cluster for performing clustering of the received tag data based on a matching indication of asset properties indicated in received tag data, wherein the matching indication of asset properties comprises at least one of:

a manager number encoded in the tag data, an object class encoded in the tag data, a Universal Product Code derived from the manager number and object class encoded in the tag data, a European Article Number derived from the manager number and object class encoded in the tag data, an asset manufacturer derived from the manager number encoded in the tag data, or a product type derived from the object class encoded in the tag data.