WO2009089948A1 - System and method for determining rfid tagged items encompassed in a given area - Google Patents

System and method for determining rfid tagged items encompassed in a given area Download PDF

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Publication number
WO2009089948A1
WO2009089948A1 PCT/EP2008/065719 EP2008065719W WO2009089948A1 WO 2009089948 A1 WO2009089948 A1 WO 2009089948A1 EP 2008065719 W EP2008065719 W EP 2008065719W WO 2009089948 A1 WO2009089948 A1 WO 2009089948A1
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WO
WIPO (PCT)
Prior art keywords
tagged
tagged items
items
item
tagged item
Prior art date
Application number
PCT/EP2008/065719
Other languages
French (fr)
Inventor
Joaquin Picon
Frederic Bauchot
Gerard Marmigere
Jean-Yves Clement
Original Assignee
International Business Machines Corporation
Compagnie Ibm France
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by International Business Machines Corporation, Compagnie Ibm France filed Critical International Business Machines Corporation
Priority to EP08870823A priority Critical patent/EP2235669A1/en
Priority to JP2010538526A priority patent/JP5490016B2/en
Priority to KR1020107012390A priority patent/KR101154702B1/en
Priority to CN2008801207524A priority patent/CN101896924A/en
Publication of WO2009089948A1 publication Critical patent/WO2009089948A1/en

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Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06K—GRAPHICAL DATA READING; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K7/00—Methods or arrangements for sensing record carriers, e.g. for reading patterns
    • G06K7/0008—General problems related to the reading of electronic memory record carriers, independent of its reading method, e.g. power transfer
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06K—GRAPHICAL DATA READING; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K17/00—Methods or arrangements for effecting co-operative working between equipments covered by two or more of main groups G06K1/00 - G06K15/00, e.g. automatic card files incorporating conveying and reading operations
    • G06K17/0022—Methods or arrangements for effecting co-operative working between equipments covered by two or more of main groups G06K1/00 - G06K15/00, e.g. automatic card files incorporating conveying and reading operations arrangements or provisious for transferring data to distant stations, e.g. from a sensing device
    • G06K17/0029—Methods or arrangements for effecting co-operative working between equipments covered by two or more of main groups G06K1/00 - G06K15/00, e.g. automatic card files incorporating conveying and reading operations arrangements or provisious for transferring data to distant stations, e.g. from a sensing device the arrangement being specially adapted for wireless interrogation of grouped or bundled articles tagged with wireless record carriers
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06K—GRAPHICAL DATA READING; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K7/00—Methods or arrangements for sensing record carriers, e.g. for reading patterns
    • G06K7/10—Methods or arrangements for sensing record carriers, e.g. for reading patterns by electromagnetic radiation, e.g. optical sensing; by corpuscular radiation
    • G06K7/10009—Methods or arrangements for sensing record carriers, e.g. for reading patterns by electromagnetic radiation, e.g. optical sensing; by corpuscular radiation sensing by radiation using wavelengths larger than 0.1 mm, e.g. radio-waves or microwaves
    • G06K7/10019—Methods or arrangements for sensing record carriers, e.g. for reading patterns by electromagnetic radiation, e.g. optical sensing; by corpuscular radiation sensing by radiation using wavelengths larger than 0.1 mm, e.g. radio-waves or microwaves resolving collision on the communication channels between simultaneously or concurrently interrogated record carriers.
    • G06K7/10079—Methods or arrangements for sensing record carriers, e.g. for reading patterns by electromagnetic radiation, e.g. optical sensing; by corpuscular radiation sensing by radiation using wavelengths larger than 0.1 mm, e.g. radio-waves or microwaves resolving collision on the communication channels between simultaneously or concurrently interrogated record carriers. the collision being resolved in the spatial domain, e.g. temporary shields for blindfolding the interrogator in specific directions
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
    • G06Q10/087—Inventory or stock management, e.g. order filling, procurement or balancing against orders
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04Q—SELECTING
    • H04Q2213/00—Indexing scheme relating to selecting arrangements in general and for multiplex systems
    • H04Q2213/13095—PIN / Access code, authentication
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04Q—SELECTING
    • H04Q2213/00—Indexing scheme relating to selecting arrangements in general and for multiplex systems
    • H04Q2213/13098—Mobile subscriber

Definitions

  • the present invention relates in general to the field of Pallet Management System (PMS) and packaging supply chain logistic. More particularly, the present invention relates to a system and method for determining RFID items located in a delimited volume.
  • PMS Pallet Management System
  • a major objective of the packaging supply chains logistic is to be able to locate and account for item assets throughout their life cycle and provide transaction visibility across logistic systems.
  • Transaction visibility provides an organisation with timely and accurate information on the location, movement, status and identity for making the overall inventory process performance in improvement. Consequently, for achieving such a process performance most of the organisations must also consider how pallet loads created at the warehouse, especially rainbow pallets (pallets of mixed products ), will be properly identified and tagged and finally tracked.
  • the today's packaging supply chains use the RFID capabilities for opitimiz their overall inventory process in performance.
  • the RFID technology suits the process automation as a ⁇ well as the volumee production and matches various business expectations in sectors where numerous items need to be identified by type or/and by physical characteristics and other differentiatings parameters..
  • a Reader is capable to collect the identification parameters from a series of tags that are assembled together, whether in a box or in a package by avoiding multiple readings as well as by preventing reading collisions.
  • Another concern consists in ensuring that the reading is not affected by close proximity of tags responding to the Reader thereby generating undesirable electromagnetic radiation to the queried tag.
  • a technique that is generally adopted for discriminating tagged items in a delimited vicinity is the use of sophisticated RFID directional antennas in combination with tags that are especially designed to have a high gain in controlled environment and orientation (i.e. squiggle tag or
  • the known solutions are not fully appropriate to identify aggregated tagged items in a delimited vicinity by avoiding reading collision due to the close proximity of tagged items.
  • the existing tools and methods do not allow a reader to get in one shot the identification of a list of tagged items that are considered as adjacent by the reader when scanning pallets/cases all along the packaging supply chain process.
  • the present invention offers a solution to solve the aforementioned problems.
  • Another object of the present invention is to determine the quantity of adjacent tags present in a delimited vicinity and generate a list of tags accordingly.
  • Yet another object of the invention is to provide a RFID Reader with a selective identification of a group of adjacent tags located in different delimited vicinities as well as in a predefined radius.
  • a computer program product comprises a computer usable medium having readable program code and algorithm embodied in the medium and the computer program product includes at least one component or more to operate the steps of the distance computation method as described in the appended claims.
  • FIG.l shows a block diagram of a preferred implementation for practicing the present invention.
  • FIG.2 illustrates in a high level, a Client Application as may be applicable to the preferred environment of the invention.
  • FIG.3 represents a flow chart that outlines the discrimination algorithm of the Application Controller of FIG.2.
  • FIG.4 illustrates a splitting of a tag set into subsets. Additionally, the detailed description is supplemented with Exhibit 1 which contains an implementation of the discrimination algorithm functionally described in Figure 3.
  • the present invention consists in identifying simultaneously a series of tagged items assembled in a case or a pallet, and a method allowing a Pallet Management System (PMS) to capture unambiguously the content of the identified items by using RFID capabilities.
  • PMS Pallet Management System
  • FIG.l illustrates by schematic block diagram the preferred environment (100) for practicing the invention.
  • the preferred environment (100) consists in a Reader (102), a Stocking Environment (104) like a yard comprising several Tagged Item Groups (#1 (106) to #n (108)) like pallet or case, and a Client Application (110) based on RFID system.
  • the RFID system operates at the reader level.
  • the Reader (102) communicates with or interrogates different groups of tagged items that are respectively arranged in Tagged Item Group #1 (106) up to Tagged Item Group #n (108) . It is considered that Tagged Item Group #1 (106) and Tagged Item Group #n (108) do not have relationship together but are located within a same Stocking Environment (104) . For the sake of simplicity, only two groups of tagged items are represented in FIG.l but the person who is skilled in the art can imagine that the RFID system may contain in a packaging supply chain more than the two illustrated groups.
  • the Reader (102) initiates multiple reading shots for targeting the tagged items that correspond exclusively to the Tagged Item Group #1
  • each Tagged Item Group (106, 108) contains a large amount of tagged items
  • the delimited vicinity is configured in the algorithm that suits for the Client
  • the delimited vicinity is determined by the separating distance between a tagged item that belongs to a particular Tagged Item Group (106 or 108) and the Reader
  • a non-responding passive tag is capable to catch and store the information carried by a tag responding to a reader by the use of backscattering technique. A non-responding tag can then restore the loaded information about its separating distance between adjacent tags to the reader when queried.
  • FIG.2 illustrates in a high level, the Client Application (200) as may be applicable to the preferred environment of the invention .
  • the Client Application (200) comprises an Application Controller (202), a Client Control Interface (204), a Client Server (206), a WEB server (208) and a Client System Database (210) that are linked together on a client network (Network) .
  • the Client Application (200) uses a standard network to process data which are collected by the Reader (102 of FIG.l) and exchanges information across the different layers of the packaging supply chain. It is to be noted that depending on the client application a data structure may contain multiple layers to form a client network solution. As an example, one can be used to control the signals streaming all along the supply chain while other ones can be used to handle the operation at the client layer. For the sake of simplicity, the present invention uses a single network (Network) for communicating between different layers.
  • Network Network
  • the Application Controller (202) interacts with the Reader, interprets data gathering and transmits the information collected to the Client System Database (210) to be stored via the client network (Network) .
  • the Application Controller (202) automates the process flow from the reader level to the Client Server (206) .
  • the Client Server (206) collects the information from the Application Controller (202) and sends them to the client's communication system over the Internet via the WEB server (208) .
  • the client network is the backbone of the supply chain and links all the devices of the supply chain (like server, database or personal computer) together.
  • the Client Control Interface (204) monitors the data exchanges between each system all along the client supply chain.
  • the Application Controller (202) contains a software agent for preventing reading collisions and ensuring a proper and timely communication with the tagged items.
  • the software agent runs a discrimination algorithm for determining the distance for all tagged items that are located in the same vicinity.
  • the discrimination algorithm allows the Reader (102 of FIG.l) to initiate multiple reading shots to the tagged items. Thereby, it can identify amongst a large amount of tagged items the aggregated ones that are assembled together in a predefined volume, whether in a box or in a package, in cases or/and pallets.
  • the proposed discrimination algorithm computes at the reader level the encapsulating volume of tagged items by excluding the undesirable response of other tagged items being outside the predefined volume.
  • FIG.3 represents a flow chart (300) that outlines the functional steps of the discrimination algorithm run at the
  • Exhibit 1 shows an operational implementation of the now described discrimination process.
  • the discrimination algorithm firstly starts a polling cycle for calibrating the Application Controller. Then, it instructs the Reader (102 of FIG.l) for screening the tagged items that are located in the range of the reader in order to identify and acquire their characteristics. Such characteristics are the distance between a tagged item responding and the reader, the distance between an adjacent tagged item and the reader and other parameters allowing to determine the reader range limitation as well as the admitted radius distance limit between adjacent tagged items. In addition, other information, like a list of adjacent tagged items with their identification is included in the RFID message when a polling tag responds to the reader. Data about the geographical position between adjacent tagged items can be also provided.
  • the characteristics of the acquired tagged items feed the Application Controller and provide the discrimination algorithm with the necessary parameters for initiating the discrimination process.
  • the discrimination algorithm allow to split a tagged item population into one or more partitions, each containing a set of tagged items (TS) with multiple subsets (SS) . Another aspect is to collect the tagged items that are considered as adjacent when located in the same vicinity and to assemble them in a targeted subset. Meaning by targeted is a group of tagged items that the Application Controller considers as located in the same geographical area or volume.
  • the discrimination algorithm may take different decisions while the tag set remains not void.
  • the discrimination algorithm can identify a new subset to be part of the selected partition.
  • the discrimination algorithm creates the subset accordingly with the not yet allocated tagged items and its adjacent tagged items .
  • the discrimination algorithm can either create a new subset to be included in the partition or enrich an existing one. In specific situation, when a tagged item meets multiple partitions then the discrimination algorithm is able to determine automatically the adequate partition for assigning the tagged item.
  • Step 302 (Process initialization) .
  • the discrimination algorithm initializes the Application Controller and prepares the system for splitting a tagged item population into several distinct partitions, each of them containing a set of tagged items (TS) with multiple subsets (SS) .
  • the Application Controller provides the discrimination algorithm with the amount of set of tagged items (TS) .
  • the amount of set of tagged items (TS) is a function of the tagged item population and a determination of a maximum of allowed partitions at the supply chain configuration step (not shown here) .
  • the Application Controller determines the number of subsets (SS) to be assembled within one set of tagged items.
  • the number of subsets depends on both the tagged item population, the maximum of subsets allowed by the system and the separating distance between each subset when arranged in the same set of tagged items (TS) . Furthermore, the maximum of subsets (SS) allowed is a function of the size of the set of tagged items (TS) .
  • Step 304 (Tagged Item acquisition).
  • the discrimination algorithm interprets the information stored in the tagged items through the Application Controller by looping on each tagged item. It is to be recall here that the information that is stored within each tagged item is collected running the backscattering technique as described in the patent application FR920070079 filed the same day by the Assignee.
  • the discrimination algorithm identifies the tagged items that match the screening criteria as preliminary defined when configuring the Application Controller.
  • screening criteria are the distance limitation or/and the reader range or/and other parameters that inform the Application Controller about tagged item geographical characteristics.
  • the discrimination algorithm is able to sort the tagged items and to label them accordingly. Thereby, each individual tagged item can be aggregated in a convenient way to be included into the adequate set of tagged items (TS) . Then the process goes to step 306 .
  • Step 306 (Central Tagged Item identification).
  • the discrimination algorithm determines the position of each adjacent tagged item with reference to each individual tagged item that is located within the area and/or volume of measurement, previously defined during the configuration step.
  • the discrimination algorithm scans the tagged items the ones after the others for evaluating the number of adjacent tagged items that are located around each tagged item taken individually. Then the process goes to step 308.
  • Step 308 A status determines the completion of the identification of the central tagged item. According to the status, the discrimination algorithm stops the scanning process within the area or volume as soon as an identification of a particular tagged item that has a maximum of adjacent tagged items populated around occurs. Then the process goes to step 310 (branch Yes of the comparator 308) otherwise the discrimination algorithm continues the scanning process (Branch No of the comparator 308) and the process loops back to step 306.
  • Step 310 (Subset instantiation).
  • the discrimination algorithm gets the information related to each central tagged item with its associated adjacent tagged items. Then, the discrimination algorithm selects either a portion of or the entire population of the adjacent tagged items by outlining a virtual boundary range around the selected central tagged item that defines a subset (SS) . It is to be noted that, the virtual boundary range can be adjusted at the configuration step allowing the Reader to collect the tagged items at the various radius parameter settings. Consequently, the system creates and instantiates a subset of adjacent tagged items that is associated to a central tagged item and the process goes to step 312.
  • a status determines the completion of the subset (SS) instantiation within the partition containing some sets of tagged items (TS) . Based on the status, the discrimination algorithm stops after the instantiation process that runs within the area or volume of measurement detects the final central tagged item. Meaning that, several subsets (SS) are identified according to the screening criteria. Each subset (SS) contains a central tagged item with the addition of a population of adjacent tagged items located around in the same vicinity. Then the process goes to step 314 (Branch Yes of the comparator 312) otherwise the subset instantiation is not complete (Branch No of the comparator 312) and the process loops back to step 310.
  • Step 314 A detection of any of the potential missing tagged items is performed at step 314 of the discrimination algorithm.
  • the radius of the Reader range is configured for satisfying a maximum area and/or volume of measurement.
  • the discrimination algorithm uses the information of the tagged items previously gathered for initiating the detection of the presence of a missing tagged item.
  • the discrimination algorithm gets the geographical characteristics of tagged items already assigned within a subset (SS) and generates a virtual boundary range that will serve afterwards as a secondary reference when initiating the distance measurement of the missing tagged items.
  • a status determines the presence of a potential missing tagged item that is out of the virtual boundary range. If a missing tagged item is detected then the process goes to step 316 (branch Yes of the comparator 314) otherwise there exist no missing tagged items anymore (branch No of the comparator 314) and the process goes to step 318.
  • step 316 a status determines that a missing tagged item can be added to an existing subset of tagged items
  • the discrimination algorithm identifies a missing tag that can be a candidate to be included within an existing subset of tagged items (SS) . Then, the discrimination algorithm initiates the Reader for screening the missing tagged items and getting their geographical characteristics. Consequently, the discrimination algorithm determines the separating distance with the aforementioned virtual boundary range. Thereby, the discrimination algorithm identifies which of the distant tagged items that are missed during the subset instantiation can be added into an existing subset. It is to be noted that the maximum distance allowed for determining a separating distance of a missing tagged item with the virtual boundary range is a constraint that is defined during the configuration step within the Application Controller.
  • a new subset (SS) is created for receiving the aforementioned missing tagged item (Branch No of the comparator 316), the missing tagged items is therefore considered as a new central tagged item and the process goes to step 306. Otherwise, the separating distance between the missing tagged item and the virtual boundary range of the selected subset of tagged items (SS) does not exceed the maximum distance allowed (Branch Yes of the comparator 316) then the missing tagged item is added into the existing subset (SS) and the process goes to step 310.
  • Step 318 (Discrimination completion) .
  • the discrimination algorithm is complete.
  • the Reader is able to identify a tagged item population that is aggregated into multiple subset of tagged items (SS) within a set of tagged items (TS) in a partition of the packaging supply chain.
  • FIG.4 a symbolic representation of a split of an initial set of tagged items (Fig. 4A) into four subsets (Fig. 4B) is shown.
  • the discrimination algorithm considers a population of tagged items that need to be respectively aggregated in multiple subsets.
  • Each subset is a part of a set of tagged items that belongs to a partition in the packaging supply chain.
  • the Reader can easily read a group of tagged items that are located in the same vicinity within a subset with no risk of collision with the other adjacent subsets.
  • FIG.4A illustrates a set representing a pallet that is populated with tagged items.
  • 40 tagged items grey dots
  • FIG.4A illustrates a set representing a pallet that is populated with tagged items.
  • 40 tagged items grey dots
  • the set of the tagged items is arranged in four distinct subsets. Each subset represents a box containing several tagged items. By running the discrimination algorithm, each subset is respectively instantiated as NE (North East) , NW
  • FIG.4B illustrates different cases for which the discrimination algorithm operates when sorting the tagged items according to the screening criteria as defined during the configuration step.
  • the discrimination algorithm first determines the central tagged item ⁇ Tio' that has the maximum of adjacent tagged items populated around. For the purpose of the illustration and the sake of clarity, each central tagged item within its current subset (NE, NW, SE and SW) is highlighted by a bold ellipse, while the adjacent tagged items are the free dots.
  • a missing tagged item is a tagged item that is not considered as an adjacent tagged item having a central tagged item.
  • the discrimination algorithm operates by considering the missing tagged item as adjacent to an adjacent tagged item and therefore checks the separating distance in between. If the discrimination algorithm determines that a missing tagged item is over of a predetermined maximum distance, then the missing tagged item is considered as being located to another subset and a new subset (SS) is created for receiving the aforementioned missing tagged item, as pointed by the arrow ⁇ Tag added to a new subset' in screen SW of Fig.4B. Otherwise, the discrimination algorithm adds the missing tagged items into the adequate subset (SS) .
  • the discrimination algorithm may be implemented using various computation variables.
  • One preferred implementation is provided in Exhibit 1.
  • This partition corresponds to a collection of subsets SS k where k varies between 1 and the maximal value of N.
  • the algorithm runs as a loop while the tag set TS remains not void. For each loop iteration, the algorithm either : detects a new subset SS k0 , with members T i , and its neighbors; or adds new members T i and its neighbors to an already defined subset Ss k .
  • the criteria used to identify the best tag candidate for either creating a new subset or for expanding an already defined subset corresponds to the number of tag neighbors. In this particular example where several tags have a neighbor set with the highest size, then the preferred embodiment of the present invention selects randomly one of these tags.
  • the algorithm may discard these tags in the current loop step, and works on the ones showing the immediately largest neighbor population.

Abstract

A system and method are provided to determine RFID tagged items in a delimited area. After polling a plurality of RFID tagged items, a RFID reader operates a discrimination algorithm that allow a partitioning of adjacent RFID tagged items, thereby allowing each tagged item located in a predetermined area to be grouped in one tag set.

Description

System and Method for determining RFID tagged items encompassed in a given area
Technical field
The present invention relates in general to the field of Pallet Management System (PMS) and packaging supply chain logistic. More particularly, the present invention relates to a system and method for determining RFID items located in a delimited volume.
Background of the invention
When faced to the complexity of item inventory, independently of the business sector, the today' s warehouses have a common objective of making their packaging supply chain logistic more robust and more efficient. They have to monitor efficiently the items visibility and keep track of the movements of numerous items before being assembled at the case and palletized.
Furthermore, a major objective of the packaging supply chains logistic is to be able to locate and account for item assets throughout their life cycle and provide transaction visibility across logistic systems. Transaction visibility provides an organisation with timely and accurate information on the location, movement, status and identity for making the overall inventory process performance in improvement. Consequently, for achieving such a process performance most of the organisations must also consider how pallet loads created at the warehouse, especially rainbow pallets (pallets of mixed products ), will be properly identified and tagged and finally tracked. Generally, to meet these objectives, the today's packaging supply chains use the RFID capabilities for opitimiz their overall inventory process in performance. The RFID technology suits the process automation as aε well as the volumee production and matches various business expectations in sectors where numerous items need to be identified by type or/and by physical characteristics and other differentiatings parameters..
Even if there are various RFID possibilities available today for monitoring a packaging supply chain, one difficulty resides in identifying heterogeneous tagged items in large areas such as factory or distribution yard at the same time, ensuring that the reading of each tagged item avoids Reader collision. A Reader collision appears when a signal from one Reader interferes with the signal from another Reader.
It is also desirable for an organisation to implement a robust technique for tracking pallet/case inventories either discretely (i.e. all pallets/cases IDs are recorded and aggregate quantities identified) or more simply quantity by type and to easily identify the content of each pallet either in bulk or as unique IDs.
Independently of the technique, a major concern resides when an organisation needs discriminating among a large variety of heterogeneous tagged items already placed on the pallets/cases or not, the tagged items that have identification parameters allowing a Reader to aggregate them according to their geographical location.
Usually a Reader expects to read tagged items confined in a given volume. The given volume, most of the time, represents the volume of the cases stacked on a pallet. Despite the tuning of the Reader, the reading of the information on multiple tagged items that are located inside a box or package can be polluted by the unexpected tagged items located in a close proximity also answering to the Reader request and therefore introducing errors.
It is also desirable to ensure that a Reader is capable to collect the identification parameters from a series of tags that are assembled together, whether in a box or in a package by avoiding multiple readings as well as by preventing reading collisions.
Another concern consists in ensuring that the reading is not affected by close proximity of tags responding to the Reader thereby generating undesirable electromagnetic radiation to the queried tag.
A technique that is generally adopted for discriminating tagged items in a delimited vicinity is the use of sophisticated RFID directional antennas in combination with tags that are especially designed to have a high gain in controlled environment and orientation (i.e. squiggle tag or
12 tag) . Unfortunately, the use of such technique does not avoid the undesirable radiation of the adjacent tags affecting the tag answering to the reader.
To summarize, prior art tools and methods present several drawbacks, some of the main are recall:
Existing tools and methods do not allow a pallet management system to identify efficiently aggregated tagged items in a delimited vicinity.
- Existing tools and methods do not offer the possibility to read a series of tagged items that are assembled together in a predefined volume, whether in a box or in a package, in cases or/and pallets.
- Existing tools and methods do not allow a supply chain to identify a list of tagged items that are located in a delimited vicinity by reading a tag once.
- Existing tools and methods do not minimize the reading collision when discriminating a unique tagged item that is close to a series of adjacent tags in the same case and/or pallet.
Exiting tools and methods using sophisticated RFID directional antennas in combination with tags especially designed to have a high gain in controlled environment and orientation do not eliminate efficiently reading collision.
As mentioned above, the known solutions are not fully appropriate to identify aggregated tagged items in a delimited vicinity by avoiding reading collision due to the close proximity of tagged items. Furthermore, the existing tools and methods do not allow a reader to get in one shot the identification of a list of tagged items that are considered as adjacent by the reader when scanning pallets/cases all along the packaging supply chain process.
The present invention offers a solution to solve the aforementioned problems.
Summary of the invention
It is a broad object of the present invention to provide a system and method for identifying a series of tagged items that are located in a delimited vicinity.
It is another object of the present invention to discriminate a tagged item from a series of tagged items that are assembled together in a delimited vicinity by avoiding reading collision.
It is another object of the present invention to gather identification of a group of adjacent tags in a predefined radius and generate a compacted identification message accordingly.
Therefore, it is also another object of the present invention to filter undesirable identification of, at least, one or more tags located in a delimited vicinity that are outside of a predefined radius.
It is a further object of the present invention to localize uniquely a tag located in various adjacent delimited vicinities .
Another object of the present invention is to determine the quantity of adjacent tags present in a delimited vicinity and generate a list of tags accordingly.
Yet another object of the invention is to provide a RFID Reader with a selective identification of a group of adjacent tags located in different delimited vicinities as well as in a predefined radius.
Finally, it is an object of the invention to boost the performance of a RFID Reader by regrouping the identification of adjacent tags located in a predefined radius.
In another aspect of the invention, a computer program product is provided. The computer program product comprises a computer usable medium having readable program code and algorithm embodied in the medium and the computer program product includes at least one component or more to operate the steps of the distance computation method as described in the appended claims.
According to the invention, there is provided a system and method as further described in the appended independent claims. Further embodiments are described in the appended dependent claims.
Brief description of the drawings
The above and other items, features and advantages of the invention will be better understood by reading the following more particular description of the invention in conjunction with the accompanying drawings wherein:
FIG.l shows a block diagram of a preferred implementation for practicing the present invention.
FIG.2 illustrates in a high level, a Client Application as may be applicable to the preferred environment of the invention.
FIG.3 represents a flow chart that outlines the discrimination algorithm of the Application Controller of FIG.2.
FIG.4 illustrates a splitting of a tag set into subsets. Additionally, the detailed description is supplemented with Exhibit 1 which contains an implementation of the discrimination algorithm functionally described in Figure 3.
Detailed description of the invention
Embodiments of the invention are described herein after by way of examples with reference to the accompanying figures and drawings .
More specifically, according to a first aspect, the present invention consists in identifying simultaneously a series of tagged items assembled in a case or a pallet, and a method allowing a Pallet Management System (PMS) to capture unambiguously the content of the identified items by using RFID capabilities.
FIG.l illustrates by schematic block diagram the preferred environment (100) for practicing the invention. The preferred environment (100) consists in a Reader (102), a Stocking Environment (104) like a yard comprising several Tagged Item Groups (#1 (106) to #n (108)) like pallet or case, and a Client Application (110) based on RFID system.
The RFID system operates at the reader level. The Reader (102) communicates with or interrogates different groups of tagged items that are respectively arranged in Tagged Item Group #1 (106) up to Tagged Item Group #n (108) . It is considered that Tagged Item Group #1 (106) and Tagged Item Group #n (108) do not have relationship together but are located within a same Stocking Environment (104) . For the sake of simplicity, only two groups of tagged items are represented in FIG.l but the person who is skilled in the art can imagine that the RFID system may contain in a packaging supply chain more than the two illustrated groups. The Reader (102) initiates multiple reading shots for targeting the tagged items that correspond exclusively to the Tagged Item Group #1
(106) or the Tagged Item Group #n (108) . Thereby, each Tagged Item Group (106, 108) contains a large amount of tagged items
(not shown here) that the Reader (102) has targeted as being located in the delimited vicinity. The delimited vicinity is configured in the algorithm that suits for the Client
Application (110). The delimited vicinity is determined by the separating distance between a tagged item that belongs to a particular Tagged Item Group (106 or 108) and the Reader
(102). A full description of the delimited vicinity concept is to be found in patent application FR920070072 filed the same day by the Assignee and which is incorporated herein by reference.
A non-responding passive tag is capable to catch and store the information carried by a tag responding to a reader by the use of backscattering technique. A non-responding tag can then restore the loaded information about its separating distance between adjacent tags to the reader when queried.
Then, by the use of an appropriate algorithm, the Client
Application (110) processes the data collected by the Reader
(102) from the targeted tagged items to be transmitted to either a Pallet Management System (PMS) and/or to a packaging supply chain logistic and /or to other database used by other client systems.
FIG.2 illustrates in a high level, the Client Application (200) as may be applicable to the preferred environment of the invention .
The Client Application (200) comprises an Application Controller (202), a Client Control Interface (204), a Client Server (206), a WEB server (208) and a Client System Database (210) that are linked together on a client network (Network) . The Client Application (200) uses a standard network to process data which are collected by the Reader (102 of FIG.l) and exchanges information across the different layers of the packaging supply chain. It is to be noted that depending on the client application a data structure may contain multiple layers to form a client network solution. As an example, one can be used to control the signals streaming all along the supply chain while other ones can be used to handle the operation at the client layer. For the sake of simplicity, the present invention uses a single network (Network) for communicating between different layers.
The Application Controller (202) interacts with the Reader, interprets data gathering and transmits the information collected to the Client System Database (210) to be stored via the client network (Network) . The Application Controller (202) automates the process flow from the reader level to the Client Server (206) . Thereby, the Client Server (206) collects the information from the Application Controller (202) and sends them to the client's communication system over the Internet via the WEB server (208) . It is to be noted that the client network (Network) is the backbone of the supply chain and links all the devices of the supply chain (like server, database or personal computer) together. Finally, the Client Control Interface (204) monitors the data exchanges between each system all along the client supply chain.
Generally, the Application Controller (202) contains a software agent for preventing reading collisions and ensuring a proper and timely communication with the tagged items. In the present invention, the software agent runs a discrimination algorithm for determining the distance for all tagged items that are located in the same vicinity. The discrimination algorithm allows the Reader (102 of FIG.l) to initiate multiple reading shots to the tagged items. Thereby, it can identify amongst a large amount of tagged items the aggregated ones that are assembled together in a predefined volume, whether in a box or in a package, in cases or/and pallets. Moreover, the proposed discrimination algorithm computes at the reader level the encapsulating volume of tagged items by excluding the undesirable response of other tagged items being outside the predefined volume.
FIG.3 represents a flow chart (300) that outlines the functional steps of the discrimination algorithm run at the
Application Controller (202 of FIG.2) . In addition, Exhibit 1 shows an operational implementation of the now described discrimination process.
The discrimination algorithm firstly starts a polling cycle for calibrating the Application Controller. Then, it instructs the Reader (102 of FIG.l) for screening the tagged items that are located in the range of the reader in order to identify and acquire their characteristics. Such characteristics are the distance between a tagged item responding and the reader, the distance between an adjacent tagged item and the reader and other parameters allowing to determine the reader range limitation as well as the admitted radius distance limit between adjacent tagged items. In addition, other information, like a list of adjacent tagged items with their identification is included in the RFID message when a polling tag responds to the reader. Data about the geographical position between adjacent tagged items can be also provided.
After completion of the polling cycle, the characteristics of the acquired tagged items feed the Application Controller and provide the discrimination algorithm with the necessary parameters for initiating the discrimination process.
The discrimination algorithm allow to split a tagged item population into one or more partitions, each containing a set of tagged items (TS) with multiple subsets (SS) . Another aspect is to collect the tagged items that are considered as adjacent when located in the same vicinity and to assemble them in a targeted subset. Meaning by targeted is a group of tagged items that the Application Controller considers as located in the same geographical area or volume.
More precisely, the discrimination algorithm may take different decisions while the tag set remains not void.
Firstly, the discrimination algorithm can identify a new subset to be part of the selected partition. The discrimination algorithm creates the subset accordingly with the not yet allocated tagged items and its adjacent tagged items .
Secondly, it can add a not yet allocated tagged item with their associated adjacent tagged items to an existing subset.
It is to be noted that depending on the amount of adjacent tagged items assigned to a tagged item the discrimination algorithm can either create a new subset to be included in the partition or enrich an existing one. In specific situation, when a tagged item meets multiple partitions then the discrimination algorithm is able to determine automatically the adequate partition for assigning the tagged item.
As already mentioned the discrimination algorithm firstly starts a polling cycle for calibrating the Application
Controller and instructs the Reader for screening the tagged items. Once the Application Controller has identified and acquired the characteristics of the tagged items then the discrimination algorithm is able to run and the process goes to step 302.
Step 302: (Process initialization) . The discrimination algorithm initializes the Application Controller and prepares the system for splitting a tagged item population into several distinct partitions, each of them containing a set of tagged items (TS) with multiple subsets (SS) . The Application Controller provides the discrimination algorithm with the amount of set of tagged items (TS) . The amount of set of tagged items (TS) is a function of the tagged item population and a determination of a maximum of allowed partitions at the supply chain configuration step (not shown here) . In addition, the Application Controller determines the number of subsets (SS) to be assembled within one set of tagged items. The number of subsets (SS) depends on both the tagged item population, the maximum of subsets allowed by the system and the separating distance between each subset when arranged in the same set of tagged items (TS) . Furthermore, the maximum of subsets (SS) allowed is a function of the size of the set of tagged items (TS) . Once, the discrimination algorithm has determined both the set of tagged items (TS) and the subsets (SS) then the process goes to step 304.
Step 304: (Tagged Item acquisition). The discrimination algorithm interprets the information stored in the tagged items through the Application Controller by looping on each tagged item. It is to be recall here that the information that is stored within each tagged item is collected running the backscattering technique as described in the patent application FR920070079 filed the same day by the Assignee. By iteration of the loop, the discrimination algorithm identifies the tagged items that match the screening criteria as preliminary defined when configuring the Application Controller. Such screening criteria are the distance limitation or/and the reader range or/and other parameters that inform the Application Controller about tagged item geographical characteristics. From the collected information, the discrimination algorithm is able to sort the tagged items and to label them accordingly. Thereby, each individual tagged item can be aggregated in a convenient way to be included into the adequate set of tagged items (TS) . Then the process goes to step 306 .
Step 306: (Central Tagged Item identification). By exploiting the geographical characteristics in conjunction with the reader range, the discrimination algorithm determines the position of each adjacent tagged item with reference to each individual tagged item that is located within the area and/or volume of measurement, previously defined during the configuration step. The discrimination algorithm scans the tagged items the ones after the others for evaluating the number of adjacent tagged items that are located around each tagged item taken individually. Then the process goes to step 308.
Step 308: A status determines the completion of the identification of the central tagged item. According to the status, the discrimination algorithm stops the scanning process within the area or volume as soon as an identification of a particular tagged item that has a maximum of adjacent tagged items populated around occurs. Then the process goes to step 310 (branch Yes of the comparator 308) otherwise the discrimination algorithm continues the scanning process (Branch No of the comparator 308) and the process loops back to step 306.
Step 310: (Subset instantiation). The discrimination algorithm gets the information related to each central tagged item with its associated adjacent tagged items. Then, the discrimination algorithm selects either a portion of or the entire population of the adjacent tagged items by outlining a virtual boundary range around the selected central tagged item that defines a subset (SS) . It is to be noted that, the virtual boundary range can be adjusted at the configuration step allowing the Reader to collect the tagged items at the various radius parameter settings. Consequently, the system creates and instantiates a subset of adjacent tagged items that is associated to a central tagged item and the process goes to step 312.
Going now to step 312 a status determines the completion of the subset (SS) instantiation within the partition containing some sets of tagged items (TS) . Based on the status, the discrimination algorithm stops after the instantiation process that runs within the area or volume of measurement detects the final central tagged item. Meaning that, several subsets (SS) are identified according to the screening criteria. Each subset (SS) contains a central tagged item with the addition of a population of adjacent tagged items located around in the same vicinity. Then the process goes to step 314 (Branch Yes of the comparator 312) otherwise the subset instantiation is not complete (Branch No of the comparator 312) and the process loops back to step 310.
Step 314: A detection of any of the potential missing tagged items is performed at step 314 of the discrimination algorithm. In order to reduce the miss rate of the tagged item discrimination, the radius of the Reader range is configured for satisfying a maximum area and/or volume of measurement. However, due to the intrinsic rounding coverage of the emitted radiation of the Reader some distant tagged items that are out of the radius range can be missed during the subset instantiation. Consequently, the discrimination algorithm uses the information of the tagged items previously gathered for initiating the detection of the presence of a missing tagged item. Thus, the discrimination algorithm gets the geographical characteristics of tagged items already assigned within a subset (SS) and generates a virtual boundary range that will serve afterwards as a secondary reference when initiating the distance measurement of the missing tagged items. Then a status determines the presence of a potential missing tagged item that is out of the virtual boundary range. If a missing tagged item is detected then the process goes to step 316 (branch Yes of the comparator 314) otherwise there exist no missing tagged items anymore (branch No of the comparator 314) and the process goes to step 318.
Going now to step 316 a status determines that a missing tagged item can be added to an existing subset of tagged items
(SS), or not, by the use of the virtual boundary range.
According to the status, the discrimination algorithm identifies a missing tag that can be a candidate to be included within an existing subset of tagged items (SS) . Then, the discrimination algorithm initiates the Reader for screening the missing tagged items and getting their geographical characteristics. Consequently, the discrimination algorithm determines the separating distance with the aforementioned virtual boundary range. Thereby, the discrimination algorithm identifies which of the distant tagged items that are missed during the subset instantiation can be added into an existing subset. It is to be noted that the maximum distance allowed for determining a separating distance of a missing tagged item with the virtual boundary range is a constraint that is defined during the configuration step within the Application Controller. If the discrimination algorithm determines that a missing tagged item is over of the maximum distance allowed, then a new subset (SS) is created for receiving the aforementioned missing tagged item (Branch No of the comparator 316), the missing tagged items is therefore considered as a new central tagged item and the process goes to step 306. Otherwise, the separating distance between the missing tagged item and the virtual boundary range of the selected subset of tagged items (SS) does not exceed the maximum distance allowed (Branch Yes of the comparator 316) then the missing tagged item is added into the existing subset (SS) and the process goes to step 310.
Step 318: (Discrimination completion) . The discrimination algorithm is complete. The Reader is able to identify a tagged item population that is aggregated into multiple subset of tagged items (SS) within a set of tagged items (TS) in a partition of the packaging supply chain.
Going now to FIG.4, a symbolic representation of a split of an initial set of tagged items (Fig. 4A) into four subsets (Fig. 4B) is shown.
As explained before, the discrimination algorithm considers a population of tagged items that need to be respectively aggregated in multiple subsets. Each subset is a part of a set of tagged items that belongs to a partition in the packaging supply chain. Thereby, the Reader can easily read a group of tagged items that are located in the same vicinity within a subset with no risk of collision with the other adjacent subsets.
FIG.4A illustrates a set representing a pallet that is populated with tagged items. In the following example, 40 tagged items (grey dots) are identified in the initial set.
The set of the tagged items is arranged in four distinct subsets. Each subset represents a box containing several tagged items. By running the discrimination algorithm, each subset is respectively instantiated as NE (North East) , NW
(North West), SE (South East) and SW (south West), representing four geographical orientations shown on FIG. 4B.
Thus, FIG.4B illustrates different cases for which the discrimination algorithm operates when sorting the tagged items according to the screening criteria as defined during the configuration step.
As described before with reference to Fig. 3, the discrimination algorithm first determines the central tagged item λTio' that has the maximum of adjacent tagged items populated around. For the purpose of the illustration and the sake of clarity, each central tagged item within its current subset (NE, NW, SE and SW) is highlighted by a bold ellipse, while the adjacent tagged items are the free dots.
Next in the discrimination process, the missing tagged items are searched, and are illustrated on Fig. 4B by simple circle around dots. A missing tagged item is a tagged item that is not considered as an adjacent tagged item having a central tagged item. In such a situation, the discrimination algorithm operates by considering the missing tagged item as adjacent to an adjacent tagged item and therefore checks the separating distance in between. If the discrimination algorithm determines that a missing tagged item is over of a predetermined maximum distance, then the missing tagged item is considered as being located to another subset and a new subset (SS) is created for receiving the aforementioned missing tagged item, as pointed by the arrow λTag added to a new subset' in screen SW of Fig.4B. Otherwise, the discrimination algorithm adds the missing tagged items into the adequate subset (SS) .
Finally, it has to be appreciated that while the invention has been particularly shown and described with reference to a preferred embodiment, various changes in form and detail may be made therein without departing from the spirit, and scope of the invention. Particularly, the discrimination algorithm may be implemented using various computation variables. One preferred implementation is provided in Exhibit 1. The algorithm is run by the Reader to analyze the information collected from all the different tags, and to build a partition of tag set TS=(T1J, where T1 represents a tag with index i varying between the values 1 and N. This partition corresponds to a collection of subsets SSk where k varies between 1 and the maximal value of N.
The algorithm runs as a loop while the tag set TS remains not void. For each loop iteration, the algorithm either : detects a new subset SSk0, with members Ti, and its neighbors; or adds new members Ti and its neighbors to an already defined subset Ssk.
The criteria used to identify the best tag candidate for either creating a new subset or for expanding an already defined subset, corresponds to the number of tag neighbors. In this particular example where several tags have a neighbor set with the highest size, then the preferred embodiment of the present invention selects randomly one of these tags.
However, in an alternate embodiment, the algorithm may discard these tags in the current loop step, and works on the ones showing the immediately largest neighbor population.
Exhibit 1
Figure imgf000021_0001

Claims

Claims
1. A method of partitioning radio frequency identifier (RFID) tagged items comprising the steps of: broadcasting identification requests to poll a plurality of tagged items; acquiring identification and location parameters of each polled tagged item, wherein each polled tagged item further providing identification and location parameters of adjacent tagged items; determining among the polled tagged items, at least one candidate tagged item having the highest number of adjacent tagged items; and creating at least one tag set from the at least one candidate tagged item, the at least one tag set including the at least one candidate tagged item and its adjacent tagged items .
2. The method of claim 1 further comprising after the determining step, the steps of: comparing the at least one candidate tagged item to an existing list of tag sets, each existing tag set including a candidate tagged item and its adjacent tagged items; and adding the at least one candidate tagged item to an existing tag set if the at least one candidate tagged item is listed.
3. The method of claim 1 or 2 wherein the adjacent tagged items are tagged items located within a predefined area around a polled tagged item.
4. The method of anyone of claims 1 to 3 wherein the identification requests are broadcasted by a RFID reader, and each RFID tagged item comprises a passive tag.
5. The method of claim 4 wherein the identification request is in the form of a message having a plurality of information fields comprising at least an identifier field carrying a tagged item identifier, a distance field indicating the distance between the polled tagged item and the RFID reader, and a proximity field defining an area of adjacent tagged items .
6. The method of anyone of claims 1 to 5 wherein the determining step further comprising the step of comparing the number of adjacent tagged items to a minimum threshold.
7. The method of anyone of claims 1 to 6 further comprising after the determining step, the step of discarding the at least one candidate tagged item.
8. A system for partitioning radio frequency identifier (RFID) tagged items comprising means for performing the steps of the method of anyone of claims 1 to 7.
9. The system of claim 8 to be used in a pallet management system to identify a plurality of tagged items.
10. A computer program product stored in a medium readable by a computer machine, the computer program product tangibly embodying readable program means for causing the computer to perform the steps of the method of anyone of claims 1 to 8.
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