Patent Publication Number: US-2023140194-A1

Title: Augmented reality (ar) self checkout attendant

Description:
BACKGROUND 
     Self-Service (SS) transactions via Self-Service Terminals (SSTs) or Self-Checkouts (SCOs) are increasingly being deployed with greater frequency in retail stores. One reason for this deployment bonanza is because customers are becoming more accustomed to SS transactions via SCOs, but another reason is because retail stores are significantly under staffed and the pandemic exacerbated this issue for retailers. 
     With SS transactions, the retailer utilizes a management terminal operated by an attendant to monitor the SS transactions for purposes of customer assistance and fraud detection. Fraud remains a significant concern for the retailers during SS transactions. 
     Typically, a single attendant is responsible for monitoring multiple SCOs. At any given moment in time an attendant can be responsible for monitoring several concurrent transactions from the management terminal, visually inspecting the SCO areas where the the customers are checking out, and potentially and simultaneously responding to a customer that has a question of the attendant. In this chaotic environment, the attendant needs to know where to optimally place their focus in order to ensure that any customer in need of assistance is not waiting too long for assistance and in order to ensure that the retailer does not experience any loss through customer theft. 
     A customer that waits too long may provide negative social media reviews for the retailer and may not return to the retail store with future business. Moreover, lines form behind the customer waiting on assistance for access to the customer&#39;s SST, such that the displeasure of one customer can quickly become retailer dissatisfaction of many customers who are also waiting to checkout of the store. 
     Unfortunately, attendants are human and a prone to making decisions that are less than optimal largely because the attendants lack the ability to quickly evaluate all the available information for all the concurrent checkouts and and to calculate in real-time risks associated with a chaotic checkout environment in order to focus their attentions on the most pressing situations. 
     SUMMARY 
     In various embodiments, a system and methods for an Augmented Reality (AR)-based self checkout attendant management service are provided. 
     According to an embodiment, a method for providing an AR-based self checkout attendant management service is presented. Transaction data and video data are collected for a transaction being processed at a Self-Service Terminals (SST) within a transaction area of the SST. Objects are tracked from the video data as a customer, a cart, the SST, at least one item, and zero or more bags. At least one intervention is identified that is required of an attendant for a particular object based on a particular event associated with one or more of the transaction data and the video data. A distinctive visual feature for the particular object or a message for the particular event is rendered within an Augmented Reality (AR) interface being viewed and operated by the attendant based on the intervention identified. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG.  1    is a diagram of a system for providing an AR-based self checkout attendant management service, according to an example embodiment. 
         FIG.  2    is a diagram of a method for providing an AR-based self checkout attendant management service, according to an example embodiment. 
         FIG.  3    is a diagram of another method for providing an AR-based self checkout attendant management service, according to an example embodiment. 
     
    
    
     DETAILED DESCRIPTION 
       FIG.  1    is a diagram of a system/platform  100  for providing an AR-based self checkout attendant management service, according to an example embodiment. It is to be noted that the components are shown schematically in greatly simplified form, with only those components relevant to understanding of the embodiments being illustrated. 
     Furthermore, the various components (that are identified in system/platform  100 ) are illustrated and the arrangement of the components are presented for purposes of illustration only. It is to be noted that other arrangements with more or less components are possible without departing from the teachings of providing an AR-based self checkout attendant management service, presented herein and below. 
     System/platform  100  (herein after just “system  100 ”) provides a processing environment by which customers, transaction devices, carts, and items are monitored in real time within transaction areas associated with a plurality of Self-Service Terminals (SSTs) during self-checkouts by the customers while being monitored by an attendant who is responsible for overseeing the self-checkouts of the SSTs. 
     A variety of data is collected from the SSTs, the transactions, and video feeds of the transaction areas. Objects representing the customers, the transaction devices (including SSTs), carts of the customers, and items in possession of the customers or in the carts are identified and tracked from the video feeds. Movements and activity of the objects are tracked and identified via unique activity identifiers from the video feeds. The data collected from the SSTs and the transactions are grouped and correlated together for each transaction as a group of selective objects. When an action is required of the attendant for a given group, the type of action and the action itself are identified. 
     Visual information that identifies the group, the action type, the action, and one or more specific objects that are the subject of the action are rendered within an AR interface on an attendant-operated device for performance by the attendant. 
     In some instances, the attendant can perform the identified action remotely though speech or a gesture identified by the AR interface through a microphone of the attendant-operated device and/or through a camera of the attendant-operated device. 
     In some instances, actions requiring verification by the attendant can be performed by the attendant with additional information supplied by a given customer or attested to by the attendant through the AR interface. 
     As used herein, the terms “customer” and/or “consumer,” may be used interchangeably and synonymously herein and below. This refers to an individual who is engaged in a Self-Service (SS) transaction at an SST. 
     As used herein, the terms “attendant” and/or a “clerk” may be used interchangeably and synonymously herein and below. This refers to an individual who is operating a management terminal or a mobile management device as oversight of the SS transactions being processed at the SSTs. This may also refer to any employee or agent of a retail store that is tasked with monitoring the transaction areas associated with the SSTs. 
     As used herein, “transaction data” comprises transaction details for the SS transaction, device statuses of the SSTs or peripherals of the SSTs, transaction interrupts, security events, and video feeds captured of the transaction areas during the SS transactions at the SSTs. 
     System  100  comprises a cloud/server  110 , one or more management terminals/mobile devices  120 , a plurality of SSTs  130 , one or more retail servers  140 , and one or more overhead cameras  150  situated above the SSTs  130  and capturing video of the SST transaction areas during the SS transactions. 
     Cloud/Server  110  comprises at least one processor  111  and a non-transitory computer-readable storage medium  112 . Medium  112  comprises executable instructions for a transaction/status tracker  113 , video tracker  114 , and attendant assistance manager  115 . The executable instructions when provided to and executed by processor  111  from medium  112  cause processor  111  to perform the processing discussed herein and below for transaction/status tracker  113 , video tracker  114 , and attendant assistance manager  115 . 
     Each management terminal/mobile device  120  (hereinafter just “management terminal  120 ”) comprises at least one processor  121  and a non-transitory computer-readable storage medium  122 . Medium  122  comprises executable instructions for transaction monitor  123 , an Application Programming Interface (API)  123 , and an AR interface  125 . The executable instructions when provided to and executed by processor  121  from medium  122  cause processor  121  to perform the processing discussed herein and below for transaction monitor  123 , API  124 , and AR interface  125 . 
     Each SST  130  comprises at least one processor  131  and a non-transitory computer-readable storage medium  132 . Medium  132  comprises executable instructions for a transaction manager  133 . The executable instructions when provided to and executed by processor  131  from medium  132  cause processor  131  to perform the processing discussed herein and below for transaction manager  133 . 
     Each retail server  140  comprises at least one processor  141  and a non-transitory computer-readable storage medium  142 . Medium  142  comprises executable instructions for a transaction system  143  and security system  144 . The executable instructions when provided to and executed by processor  141  from medium  142  cause processor  141  to perform the processing discussed herein and below for transaction system  143  and security system  144 . 
     Cameras  150  are dispersed through a retail store located in a variety of locations. Some of the cameras  150  can be three-dimensional (3D) cameras, Lidar-capable cameras, or two-dimensional (2D) stereo vision cameras. Some cameras  150  may be integrated peripheral devices of the SSTs  130  or cameras associated with integrated item barcode scanners of the SSTs  130 . Each camera comprises an identifier that is mapped to a specific physical location within the store and mapped to a specific field of view or area that images at the specific location are associated with, Cameras  150  streams image frames of video into a network accessible storage location and/or in-memory storage buffer which is accessible to cloud/server  110  along with metadata associated with each image frame, such as time and date stamp, camera identifier, field-of-view or area identifiers, etc. 
     It is to be noted for the discussion and examples that follow that a single attendant may operate more than 1 management terminal  120  while monitoring the transaction areas of SSTs  130 . For example, the attendant may be monitoring the transactions of the transaction areas via a terminal  120  while simultaneously operating a user mobile device  120 . The mobile device  120  may be AR-enabled glasses  120  or an AR headset or the mobile device  120  may be a tablet  120 , a phone  120 , or a watch  120 . In some cases, the attendant may operate a standalone terminal  120  while wearing AR-enabled glasses  120  and while simultaneously operating a phone  120  (three devices  120 ). Each of the various types of devices may comprises monitor  123 , API  124 , and AR interface  125 , In some instances, any mobile device  120  worn and/or operated by the attendant may comprise just AR interface  125  or just API  124  and AR interface  125 . 
     It is within this context that  FIG.  1    of system  100  is now discussed. 
     Transaction data (transaction details for the SS transactions, device statuses of the SSTs  130  or peripherals of the SSTs, transaction interrupts, security events, and video feeds captured of the transaction areas during the SS transactions at the SSTs  130 ) is captured or collected by attendant assistance manager  115  for real-time evaluation. 
     Transaction/status tracker  113  reports the transaction details to attendant assistance manager  115  in real time as the corresponding transaction manager  133  processes each SS transaction. Transaction details comprise a transaction identifier for a given transaction, an SST identifier associated with the transaction identifier on a given SST  130 , time of day that the given transaction was started by the corresponding transaction manager  133 , calendar date of the given transaction, any customer identifier for a customer (if available for the given transaction), item identifiers for items already scanned or entered during the customer transaction at a corresponding SST  130  and recorded by the corresponding transaction manager  133 , item details, item quantities, and item pricing for the items. 
     Transaction/status tracker  113  also provides any interrupts generated by the corresponding transaction manager  133 , transaction system  143 , and/or security system  144  during any given transaction to attendant assistance manager  115 . Interrupts may comprise an event (security or non-security event) associated with an event type and any available event information associated with the event. 
     An event type comprises events for age verification for purchase of a restricted item (such as alcohol or tobacco), quantity of a particular item exceeding what is permitted (this can be related to a type of drug being purchased or any item whose quantity is being restricted (perhaps due to supply shortages or demand for the item), the value of an item exceeding a predefined threshold (a high-value item), a randomly generated or security generated audit on the transaction, m is-scanning of an item, weight mismatch for an item that was weighed, security to check that a container being purchased is actually empty (such as a cooler), device status indicating a SST  130  is out of media (such a receipt paper, ink, etc.) or indicating the SST has a receipt printer jam (or any other device status type of event), security indicating an item was never scanned that remains in a cart of the customer when a payment was initiated by the corresponding transaction manager  133 , and other types of events. 
     Video tracker  114  uniquely identifies each object (customer, SST  130 , cart, item, bags) from the video feeds of cameras  150 . The metadata associated with the video feeds allow video tracker  114  to determine a location of each object relative to remaining objects within the transaction areas. Features associated with each object type (customer, SST  130 , cart, item, bags) are used to quickly identify each object and object time from image frames of the video feeds. Each object&#39;s relationship is determined by video tracker  114  based on that object&#39;s distance or location relative to remaining objects available in a given image frame. The object&#39;s relationship is carried as metadata with each object. Some relationships may include a given item is in a given cart, a given item is on a counter of the SST  130 , a given item is in a hand of a given customer, a given item is associated with a given bag, a given item is on a weigh scale of a given SST  130 , a given cart exceeds a threshold number of items indicating that the cart is full, etc. The relationship may also include movement metadata, such as a given item was moved to a bottom of a cart by a customer, a given item was placed in a purse or within clothing of a customer, a customer is moving away from a given SST  130 , a customer is detected as turning away from the given SST  130  for several elapsed image frames that exceeds a given amount of time, a customer is exhibiting a behavior or facial feature indicating help or assistance is needed (based on predefined behaviors or facial features), the customer made a gesture indicating help is needed based on the predefined behaviors), etc. Any behavior or gesture made by a customer is identified by video tracker  114  via a unique behavior or facial feature identifier and carried with the customers object. 
     Attendant assistance manager  115  receives the transaction data from transaction/status tracker  113  and video tracker  114  and correlates the objects, transaction details, device status, and events into a single group for each ongoing SST transaction. A single group object comprises one SST object for a single SST  130 . A single croup object may comprise at least one customer object but may also include multiple customer objects. A single group object may include, no cart objects, one cart object, or multiple cart objects. A single group object may include a single item object or multiple item objects. A single group object may include a single bag object, multiple bag objects, or no bag objects. 
     Each group object&#39;s transaction data is tracked for events or interrupts raised by corresponding transaction manager  133 , transaction system  143 , and/or security system  144 . Rules are evaluated to determine when an intervention is needed by the attendant for any given group object and its corresponding transaction. In some cases, interventions are raised independently of evaluation of the rules by transaction monitor  123  and when this occurs the intervention is communicated to attendant assistance manager  115  through API  124 . Each intervention is associated with one or more actions required of the attendant (the one or more actions may also be defined in the rules). Unique visual features or visual effects are assigned to each intervention type and/or actions required by the attendant. 
     An intervention is an action taken by the attendant, and action can be paying attention or watching a transaction remotely from the management terminal  120 ; visiting a given SST  130  to perform a price or item verification, an override, a void, a price override, request a price check, perform a transaction audit; and/or can be remotely (while the attendant remains at the management terminal  120 ) performing an override, a void, a price override, a request a price check, etc. 
     AR interface  125  provides an attendant live field-of-view video of the transaction areas comprising the groups and the objects of each group. The attendant views the transaction areas within the AR interface  125  and overlaid on top of any object requiring an intervention is its unique visual feature assigned by attendant assistance manager  115 . Attendant assistance manager  115  provides the locations of each object along with the visual features or effects to AR interface  125  and AR interface  125  overlays the visual features or effects onto the corresponding object(s) within the live field-of-view video being watched by the attendant. Optionally, a specific message for an action item is also displayed in a corner of the display that informs the attendant that a specific SST  130  requires a specific intervention. 
     For example, when the mobile device  120  is AR-enabled glasses  120 , when the attendant looks at the transaction areas a message is displayed in a corner of one or more of the lenses of the glasses  120  that indicates lane  8  requires date of birth or age verification, lane  6  has an item weight mismatch, lane  3  has a full cart of items, lane  2  has a non-scanned item when payment was initiated that remains in the cart, lane  2  customer needs assistance, lane  5  includes a high-value item, lane  9  (SST  9   130 ) has a receipt paper jam, etc. The specific objects associated with each intervention can be colored or highlighted (visual feature) within the field-of-view to pinpoint its location and SST  130  for the attendant without obstructing other objects within the field-of-view of AR-enabled glasses  120 . 
     AR interface  125  may also be operated through voice or through gestures for the attendant to clear or override some of the interrupts or to perform some of the required attendant actions for a given interrupt. For example, for age verification the attendant can place a government issued identification card in the field of view of the AR-enabled glasses  120  and blink to snap an image, then blink to capture the face of the customer; API  124  is activated to perform Optical Character Recognition (OCR) on the date of birth on the card image and perform facial comparison analysis on the customer facial image and the image on the card. When verified, API  124  records the necessary verification information for the attendant for auditing and performs the operation with monitor  123  to clear the age verification. 
     In another case, a container that needs to be checked to ensure it is empty based on a security event raised can allow the attendant to open the container and look inside the container with glasses  120  and blink to take an image. An image is taken and confirms the container is empty, any manual entry required of the attendant through monitor  123  is performed by API  124  once the image taken by the glasses  120  is confirmed to be devoid of any other items. An item present in the container may further cause API  124  to perform a machine-learning item recognition process to identify the item and report to the attendant. 
     Other types of interrupts such as item weight mismatch, high-value item, and item quantity restrictions can be cleared without the attendant visiting the corresponding SST  130  by using a gesture (thumbs up, thumbs down, waving) in front of the glasses  120  field of view once the attendant visual verifies from the attendant remote location or through transaction details reported to assistance manager  115 . 
     Item void interrupts require the attendant to collect the item that was voided by a customer from the corresponding lane or SST  130 . Here, the attendant can simply use the glasses take the item within the field of view and API  124  dears the interrupt from the transaction. 
     Double scans can be fixed by the attendant using the glasses  120  to view an item count on the receipt and view the item count with the cart or bags and initiating a thumbs up to clear the errant scan from the transaction. 
     The glasses  120  may also be equipped with a microphone such that overrides and actions can be performed by the attendant through speech commands while wearing the glasses  120 , such as clear the item weight mismatch on lane  2 , clear the high-value item on lane  3  as the transaction details indicate it was scanned and recorded for the transaction, etc. 
     API  124  permits the actions and verifications needed by an attendant for a given interrupt to be performed through the attendant&#39;s gesture-based actions in front of an integrated camera (facing inward at the eyes of the attendant or outward toward the transaction areas or both inward and outward) of an AR-enabled device  120  or through speech detected by a microphone of the AR-enabled device  120 . API  124  can translate the gestures and voice with the necessary captured audit data (images when needed) and process with monitor  123  on behalf of the attendant. 
     A variety of machine-learning algorithms or Artificial Intelligence (AI) algorithms can be integrated with API  124  for purposes of item recognition, item quantity recognition, facial recognition and verification, etc. Such that monitor  123  can be assured that the proper verifications were made by the attendant as reported by API  124  without the attendant having to access a user-facing interface of monitor  123  and providing audit information for the verification. 
     In fact, a variety of situations and additional attendant workflows that require an attendant to intervene and perform one or more actions can be completely automated using system  100  (all such situations and workflows are intended to fall within embodiments of the teachings presented herein). This permits a single attendant to manage a busy pool of SSTs  130  simultaneously and with an efficiency and a quality that have heretofore been incapable in the industry. This is particularly important in view of current labor shortages and the increased overall usage of SSTs  130  by customers in the industry. 
     The above-referenced embodiments and other embodiments are now discussed within  FIGS.  2 - 3   . 
       FIG.  2    is a diagram of a method  200  for providing an AR-based self checkout attendant management service, according to an example embodiment. The software module(s) that implements the method  200  is referred to as an “AR-based self checkout attendant.” The AR-based self checkout attendant is implemented as executable instructions programmed and residing within memory and/or a non-transitory computer-readable (processor-readable) storage medium and executed by one or more processors of one or more devices. The processor(s) of the device that executes the AR-based self checkout attendant are specifically configured and programmed to process the AR-based self checkout attendant. The AR-based self checkout attendant may have access to one or more network connections during its processing. The network connections can be wired, wireless, or a combination of wired and wireless. 
     In an embodiment, the device that executes the AR-based self checkout attendant is cloud  110 . Cloud  110  comprises a plurality of servers logically cooperating and accessible as a single server  110  (cloud  110 ). 
     In an embodiment, the device that executes the AR-based self checkout attendant is a server  110  that is separate from any given retail server  140 . 
     In an embodiment, the device that executes the AR-based self checkout attendant is retail server  140 . 
     In an embodiment, the AR-based self checkout attendant is all or some combination of  113 ,  114 , and/or  115 . 
     At  210 , the AR-based self checkout attendant collects transaction data and video data for a transaction being processed at an SST  130  within a transaction area proximate to the SST  130 . 
     In an embodiment, at  211 , the AR-based self checkout attendant identifies the transaction data as transaction details for the transaction, transaction events raised during the transaction (by transaction manager  133  or transaction system  143 ), and security events raised during the transaction (by security system  144 ). 
     At  220 , the AR-based self checkout attendant tracks objects from the video data as a customer, the SST  130 , at least one item, zero or more carts, and zero or more bags. 
     In an embodiment of  211  and  220 , at  221 , the AR-based self checkout attendant maintains a current location of each object with a mapping of a corresponding physical location of the corresponding object within a live video feed of the transaction area. 
     At  230 , the AR-based self checkout attendant identifies at least one intervention required of an attendant for a particular object based on a particular event associated with one or more of the transaction data and the video data. 
     At  240 , the AR-based self checkout attendant renders a distinctive visual feature for the particular object or a message for the particular event within an AR interface  125  being viewed and operated by the attendant based on  230 . 
     In an embodiment of  221  and  240 , at  241 , the AR-based self checkout attendant superimposes the distinctive visual feature over the live video feed that is rendered through the AR interface  125  using the mapping at the corresponding location of the particular object. 
     In an embodiment, at  250 , the AR-based self checkout attendant translates gestures or speech provided by the attendant as input to the AR interface  125  into a verification action or an audit action that is being requested by the attendant while operating the AR interface  125 . 
     In an embodiment of  250  and at  251 , the AR-based self checkout attendant instructs the AR interface  125  to capture an image of the particular object within a field-of-view of a camera based on a first gesture. 
     In an embodiment of  251  and at  252 , the AR-based self checkout attendant processes an API  124  to perform facial recognition or item recognition on the image and provide results to a transaction monitor  123  on behalf of the attendant. 
     In an embodiment of  251  and at  253 , the AR-based self checkout attendant processes an API  124  to perform OCR on a date-of-birth (DOB) portion of the image and provide a text version of the DOB portion as audit and verification information to a transaction monitor  123  on behalf of the attendant. 
     In an embodiment of  250  and at  260 , the AR-based self checkout attendant processes an API  124  to interact with a transaction monitor  123  and clear the intervention based on a first gesture. 
     In an embodiment of  250  and at  270 , the AR-based self checkout attendant identifies a first gesture as a hand gesture made by the attendant in front of an outward or forward-facing camera and provided by the outward or forward-facing camera to the AR interface  125 . 
     In an embodiment of  270  and at  271 , the AR-based self checkout attendant identifies a second gesture as an eye gesture, or a facial gesture made by the attendant to an attendant-facing camera and provided by the attendant-facing camera to the AR interface  125 . 
       FIG.  3    is a diagram of another method  300  for providing an AR-based self checkout attendant management service, according to an example embodiment. The software module(s) that implements the method  300  is referred to as an “AR checkout monitor.” The AR checkout monitor is implemented as executable instructions programmed and residing within memory and/or a non-transitory computer-readable (processor-readable) storage medium and executed by one or more processors of a device. The processors that execute the AR checkout monitor are specifically configured and programmed for processing the AR checkout monitor. The AR checkout monitor may have access to one or more network connections during its processing. The network connections can be wired, wireless, or a combination of wired and wireless. 
     In an embodiment, the device that executes the AR checkout monitor is device  120 . In an embodiment, device  120  is a management terminal. In an embodiment, device  120  is an AR-enabled mobile device, such as a phone, a tablet, glasses, a watch, or a laptop. 
     In an embodiment, the AR checkout monitor is all of or some combination of  123 ,  124 , and  125 . 
     The AR checkout monitor interacts with cloud/server  110  as discussed with system  100  and as discussed with method  200  discussed above with  FIGS.  1  and  2   , respectively. 
     At  310 , the AR checkout monitor receives object identifiers for objects presenting within a transaction area of an SST  130 . 
     At  320 , the AR checkout monitor receives object locations that maps the objects into corresponding location of a live video feed of the transaction area. 
     At  330 , the AR checkout monitor receives a distinctive visual feature for a particular object indicating that an intervention by an attendant is needed for a transaction being processed at the SST  130 . 
     At  340 , the AR checkout monitor renders the live video feed through an attendant-facing interface with the distinctive visual features presented over the corresponding location of the particular object within the live video feed. 
     In an embodiment, at  350 , the AR checkout monitor renders a text description of the intervention and an SST identifier for the SST  130  within a corner of a screen in the attendant-facing interface. 
     In an embodiment, at  360 , the AR checkout monitor captures gestures detected from the attendant while the attendant is operating the attendant-facing interface. 
     In an embodiment of  360  and at  361 , the AR checkout monitor provides the gestures to an API  124  to translate the gestures into input operations requested by the attendant through the attendant-facing interface. 
     In an embodiment of  361  and at  362 , the AR checkout monitor activates a front-facing or a rear-facing camera to capture an image from the attendant-facing interface in response to a first translated operation. 
     In an embodiment of  362  and at  363 , the AR checkout monitor provides the image to an OCR algorithm, a facial-recognition algorithm, or an item recognition algorithm in response to a second translated operation. 
     In an embodiment of  363  and at  364 , the AR checkout monitor instructs a transaction monitor  123  to override or clear the intervention based on a third translated operation. 
     It should be appreciated that where software is described in a particular form (such as a component or module) this is merely to aid understanding and is not intended to limit how software that implements those functions may be architected or structured. For example, modules are illustrated as separate modules, but may be implemented as homogenous code, as individual components, some, but not all of these modules may be combined, or the functions may be implemented in software structured in any other convenient manner. 
     Furthermore, although the software modules are illustrated as executing on one piece of hardware, the software may be distributed over multiple processors or in any other convenient manner. 
     The above description is illustrative, and not restrictive. Many other embodiments will be apparent to those of skill in the art upon reviewing the above description. The scope of embodiments should therefore be determined with reference to the appended claims, along with the full scope of equivalents to which such claims are entitled. 
     In the foregoing description of the embodiments, various features are grouped together in a single embodiment for the purpose of streamlining the disclosure. This method of disclosure is not to be interpreted as reflecting that the claimed embodiments have more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive subject matter lies in less than all features of a single disclosed embodiment. Thus, the following claims are hereby incorporated into the Description of the Embodiments, with each claim standing on its own as a separate exemplary embodiment.