DETAILED ACTION
Status of Claims
Claims 1-20 submitted on 10/27/2025 are pending and have been examined. Claims 1, 11, and 20 have been amended.
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Priority
Acknowledgment is made of applicant’s continuation in part of Application No. 18/299,854, filed on 04/13/2023.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception without significantly more. The claims recite an abstract idea. This judicial exception is not integrated into a practical application. The claim(s) do not include additional elements that are sufficient to amount to significantly more than the judicial exception.
Step 1
Claims 1-10 and 20 are directed to a machine, and claims 11-19 are directed to a process (see MPEP 2106.03).
Step 2A, Prong 1
Claim 1 recites at least the following limitations that recite an abstract idea:
optimizing availability of products for display comprising:
receiving one or more scan events associated with a plurality of products;
retrieving, information associated with each product of the plurality of products;
determining, based on the retrieved information, whether one or more products of the plurality of products are associated with a first category;
in response to determining that a first subset of products of the plurality of products is associated with a second category different from the first category:
transmitting a first message to at least one user to cause the first subset of products to be moved to a first location for inspection, wherein transmitting the first message to the at least one user causes to move the first subset of products to the first location, and
in response to receiving a second message confirming that the first subset of products has been inspected and received, updating to indicate that the first subset of products is available for sale;
in response to determining that a second subset of products of the plurality of products is associated with the first category, validating the second subset of products by determining whether a time of at least one scan event associated with the second subset of products is within a preset time range, wherein the preset time range is determined by one or more lead times for the second subset of products;
based on validation of the second subset of products, updating to indicate that the second subset of products is available for sale;
generating a graphical user interface based on the updated, comprising a product availability for each product of a plurality of products; and
transmitting the graphical user interface to at least one customer.
Claim 20 recites at least the following limitations that recite an abstract idea:
optimizing availability of products for display comprising:
receiving one or more scan events associated with a plurality of products;
determining whether one or more products of the plurality of products are associated with a first category;
in response to determining that a first subset of products of the plurality of products is associated with a second category different from the first category:
causing inspection of the first subset of products by transmitting instructions to cause one or more to move the first subset of products to a first location, and
updating to indicate that the first subset of products is available for sale based on at least the inspection;
in response to determining that a second subset of products of the plurality of products is associated with the first category, validating the second subset of products, wherein validating comprises:
determining whether a scan time stored in a received scan event associated with the second subset of products is within a preset time range, wherein the preset time range is determined by one or more lead times for the second subset of products; and
determining whether a product identifier associated with the second subset of products is included in a predetermined list of identifiers;
based on validation of the second subset of products, updating to indicate that the second subset of products is available for sale;
generating a graphical user interface based on the updated, comprising a product availability for each product of a plurality of products; and
transmitting the graphical user interface to at least one customer.
The above limitation, under its broadest reasonable interpretation, falls within the “Certain Methods of Organizing Human Activity” grouping of abstract ideas, enumerated in MPEP 2106.04(a)(2)(II), in that it recites a commercial interaction. Claim 11 recites similar limitations as claim 1.
Thus, under Prong 1 of Step 2A, claims 1, 11, and 20 recite an abstract idea.
Step 2A, Prong 2
Claim 1 includes the following additional elements that are bolded:
a computer-implemented system for optimizing availability of products for display on a graphical user interface, the system comprising:
a memory storing instructions; and
at least one processor configured to execute the instructions to perform steps comprising:
receiving one or more scan events associated with a plurality of products;
retrieving, from a database, information associated with each product of the plurality of products;
determining, based on the retrieved information, whether one or more products of the plurality of products are associated with a first category;
in response to determining that a first subset of products of the plurality of products is associated with a second category different from the first category:
transmitting a first message to at least one user device to cause the first subset of products to be moved to a first location for inspection, wherein transmitting the first message to the at least one user device causes one or more automated transport machines to move the first subset of products to the first location, and
in response to receiving a second message confirming that the first subset of products has been inspected and received, updating the database to indicate that the first subset of products is available for sale;
in response to determining that a second subset of products of the plurality of products is associated with the first category, validating the second subset of products by determining whether a time of at least one scan event associated with the second subset of products is within a preset time range, wherein the preset time range is determined by one or more machine learning models trained to predict one or more lead times for the second subset of products;
based on validation of the second subset of products, updating the database to indicate that the second subset of products is available for sale;
generating a graphical user interface based on the updated database, the graphical user interface comprising a product availability for each product of a plurality of products; and
transmitting the graphical user interface to at least one customer device.
Claim 11 includes the same additional elements as claim 1.
Claim 20 includes the following additional elements that are bolded:
A computer-implemented system for optimizing availability of products for display on a graphical user interface, the system comprising:
a memory storing instructions; and
at least one processor configured to execute the instructions to perform steps comprising:
receiving one or more scan events associated with a plurality of products;
determining whether one or more products of the plurality of products are associated with a first category;
in response to determining that a first subset of products of the plurality of products is associated with a second category different from the first category:
causing inspection of the first subset of products by transmitting instructions to cause one or more automated transport machines to move the first subset of products to a first location, and
updating a database to indicate that the first subset of products is available for sale based on at least the inspection;
in response to determining that a second subset of products of the plurality of products is associated with the first category, validating the second subset of products, wherein validating comprises:
determining whether a scan time stored in a received scan event associated with the second subset of products is within a preset time range, wherein the preset time range is determined by one or more machine learning models trained to predict one or more lead times for the second subset of products; and
determining whether a product identifier associated with the second subset of products is included in a predetermined list of identifiers;
based on validation of the second subset of products, updating the database to indicate that the second subset of products is available for sale;
generating a graphical user interface based on the updated database, the graphical user interface comprising a product availability for each product of a plurality of products; and
transmitting the graphical user interface to at least one customer device.
The additional elements recited in claims 1, 11, and 20 merely invoke such elements as a tool to perform the abstract idea and generally link the use of the abstract idea to a particular technological environment of computers and machine learning models (see MPEP 2106.05(f) and MPEP 2106.05(h). These additional elements are described at a high level in Applicant’s specification without any meaningful detail about their structure or configuration (see Fig. 5 and ¶¶0081-0083).
As such, under Prong 2 of Step 2A, when considered both individually and as a whole, the additional elements do not integrate the judicial exception into a practical application and, thus, claims 1, 11, and 20 are directed to an abstract idea.
Step 2B
As noted above, while the recitation of the additional elements in independent claims 1, 11, and 20 are acknowledged, claims 1, 11, and 20 merely invoke such additional elements as a tool to perform the abstract idea and generally link the use of the abstract idea to a particular technological environment (see MPEP 2106.05(f) and MPEP 2106.05(h)).
Even when considered as an ordered combination, the additional elements of claim 1, 11, and 20 do not add anything that is not already present when they are considered individually. Therefore, under Step 2B, there are no meaningful limitations in claims 1, 11, and 20 that transform the judicial exception into a patent eligible application such that the claims amount to significantly more than the judicial exception itself (see MPEP 2106.05).
As such, independent claims 1, 11, and 20 are ineligible.
Dependent claims 2-9 and 12-18 when analyzed as a whole, are held to be patent ineligible under 35 U.S.C. 101 because they do not add “significantly more” to the abstract idea. More specifically, dependent claims 2-9 and 12-18 merely further define the abstract limitations of claims 1, 11, and 20 or provide further embellishments of the limitations recited in independent claims 1, 11, and 20. Claims 2-9 and 12-18 do not introduce any further additional elements. Thus, dependent claims 2-9 and 12-18 are ineligible.
Furthermore, it is noted that certain dependent claims recite additional elements supplemental to those recited in independent claims 1, 11, and 20: a webpage (claims 10 and 19). However, these elements do not integrate the abstract idea into a practical application because they merely amount to using a computer to apply the abstract idea to a particular technological environment or field of use and thus do not act to integrate the abstract idea into a practical application of the abstract idea. Additionally, the additional elements do not amount to significantly more because they merely amount to using a computer to apply the abstract idea and amount to no more than a general link of the use of the abstract idea to a particular technological environment.
Thus, dependent claims 10 and 19 are ineligible.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1-3, 10-13, 19, and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over High et al. (US 2020/0270106 A1 [previously cited]) in view of Zimet et al. (US 2005/0055286 A1 [previously cited]) in further view of Fernandes et al. (US 2021/0192435 A1).
Regarding Claim 1, High et al., hereinafter, High, discloses a computer-implemented system for optimizing availability of products for display on a graphical user interface, the system comprising (Figs. 1 and 18; ¶0029[Generally speaking, pursuant to various embodiments, systems, devices and methods are provided for assistance of persons at a shopping facility… The shopping facility may be a retail sales facility, or any other type of facility in which products are displayed and/or sold… Various embodiments provide one or more user interfaces to allow various users to interact with the system including the automated mobile devices and/or to directly interact with the automated mobile devices.]):
a memory storing instructions (Fig. 1; ¶0033[In the example of FIG. 1, a shopping assistance system 100 is implemented in whole or in part at a shopping facility 101… having at least one control circuit 108, at least one memory 110 and at least one network interface 112; at least one user interface unit 114]); and
at least one processor configured to execute the instructions to perform steps comprising (Fig. 1; ¶0033 in view of ¶0261[The central computer system 1820 includes a control circuit 1821 and a memory 1822, and may be generally referred to as a processor-based device.]):
receiving one or more scan events associated with a plurality of products (Figs. 1, 10, and 17; ¶0214[The central computer system 106 is configured to receive sensor data, and based on the sensor data identify over time items that are incorrectly located and/or misplaced. Further, the central computer system may categorize and/or identify the items.]; Examiner notes that sensor data is comparable to scan events);
retrieving, from a database, information associated with each product of the plurality of products (Figs. 1, 17 and 18; ¶¶0241-0243[The sensor data is evaluated relative to known data, such as, but not limited to, an item database, index or the like that maintains information about different potential items that may be identified, imaging database that maintains image information corresponding to known items, other such databases, or combination of two or more of such databases... The sensor data may be acquired while a motorized transport unit is performing other tasks or specifically collecting sensor data that can be used to detect potential items… A bar code scanner and/or RFID sensor can be used to obtain identifying information about an item.]);
determining, based on the retrieved information, whether one or more products of the plurality of products are associated with a first category (Fig. 10; ¶0214[The central computer system 106 is configured to receive sensor data, and based on the sensor data identify over time items that are incorrectly located and/or misplaced. Further, the central computer system may categorize and/or identify the items. Based on the categorization and/or identification, the central computer system can determine how to address these items] in view of ¶0241 which discloses the retrieved information);
in response to determining that a first subset of products of the plurality of products is associated with a second category different from the first category (Fig. 1; ¶¶0213-0214[For example… systems, apparatuses, processes and methods are provided herein that allow for addressing incorrectly placed items… In some instances, for example, the central computer system may communicate instructions to cause the item to be retrieved and transported to one of multiple predefined locations.]; Examiner notes that incorrectly placed items are comparable to a second category different from a first category of items that are correctly placed):
transmitting a first message to at least one user device to cause the first subset of products to be moved to a first location for inspection, wherein transmitting the first message to the at least one user device causes one or more automated transport machines to move the first subset of products to the first location (Fig. 1; ¶¶0213-0228[Once categorized, the central computer system can determine how the item is to be addressed. This can include leaving the item where it was identified, transporting the item to a predefined area corresponding to the categorization, or the like. In some instances, for example, the central computer system may contact a shopping facility worker to retrieve the item (e.g., communication to a user interface unit 114 with information specifying where the item is located within the shopping facility, instructions regarding what the worker may need to assist the worker in retrieving the item… the central computer system may communicate instructions to one or more motorized transport units to cause the one or more motorized transport units to retrieve the detected item and transport the item to one of multiple different predefined locations] in view of ¶0029[Generally, the system makes use of automated, robotic mobile devices, e.g., motorized transport units, that are capable of self-powered movement through a space of the shopping facility and providing any number of functions.] and ¶0245[In some instances, such unknown categorized items may be routed to a particular worker, one of one or more predefined bins, or the like that allow a worker to inspect and determine how the item is to be handled (e.g., reviewed to see whether it should be routed to lost and found, recycle bins, waste bin, etc.)]; Examiner notes that a “motorized transport unit” is comparable to an “automated transport machine”), and
that the first subset of products has been inspected and received, updating the database (Fig. 1; ¶0225[The detection of an incorrectly placed item can, in some instances, include determining that an item is not in a place where an item is expected… This mapping and/or scan data can be updated as items are moved and/or products are placed in feature locations… Image data from… workers' user interface units, and/or other such imaging data can be image processed and compared to mappings, scans and/or images of what is expected]; Examiner notes that the mapping and scan data is comparable to a second message, in view of ¶0264[the sensor device 1842 may be include one or more sensors for detecting item characteristic comprising one or more of: item appearance (e.g. color, reflectiveness, pattern, etc.), item shape, item weight, item density, item text, item identifier, item barcode, item condition (e.g. dirty, damaged, etc.), etc.]; Examiner notes that detecting item characteristics is comparable to inspecting the products, and ¶0239[The central computer system typically accesses and evaluates sensor data and/or determined characteristics relative to multiple database sources of various characteristics, images, data, and the like] in view of ¶0039[In some embodiments, the at least one database 126 may store data pertaining to one or more of: shopping facility mapping data, customer data, customer shopping data and patterns, inventory data, product pricing data, and so on.]);
in response to determining that a second subset of products of the plurality of products is associated with the first category, validating the second subset of products by at least one scan event associated with the second subset of products (¶0242[A bar code scanner and/or RFID sensor can be used to obtain identifying information about an item. Some embodiments use different sensor data to confirm and/or further narrow potential categorization and/or identification (e.g., a weight of an item can be compared with known weight associated with a bar code detected to evaluate completeness of the item).]in view of ¶0150[Since an MTU system may have access to item inventory information, the system may locate various items in the store and validate that the inventory count matches what is actually on the shelf]; Examiner notes that confirming categorization of an item is comparable to validating the products);
based on validation of the second subset of products, updating the database to indicate that the second subset of products is available for sale (Fig. 10; ¶0155[FIG. 10 illustrates a block diagram of a system 1000 for determining item availability as configured in accordance with various embodiments of these teachings. The system 1000 includes a central computer system 1010, an inventory database 1020, and an MTU 1030. The system is configured to determine whether an item is out of stock according to the inventory database 1020 and determine whether an item is available for purchase on the shopping floor based on information gathered by the MTU 1030] in view of ¶0239[The central computer system typically accesses and evaluates sensor data and/or determined characteristics relative to multiple database sources of various characteristics, images, data, and the like]);
generating a graphical user interface based on the updated database, the graphical user interface comprising a product availability for each product of a plurality of products (¶0166[In yet another example, the system may determine whether the item is available for purchase online and present the user with an option to purchase the item online (e.g. send a link to the product, add the product to the user's online shopping cart). In some embodiments, the system may select from one or more of the out of stock responses based on one or more of the customer's shopping history, item type, item availability in another store, distance to the alternate store, item availability for online purchase, etc.] in view of ¶0042[In some embodiments, the user interface units 114 may be general purpose computer devices that include computer programming code to allow it to interact with the system 106… user interface units 114 may be operated by customers of the shopping facility or may be operated by workers at the shopping facility, such as facility employees (associates or colleagues), vendors, suppliers, contractors, etc.]; Examiner notes that responses indicating stock levels of an item is comparable to indicating product availability of items); and
transmitting the graphical user interface to at least one customer device (Fig. 1; ¶¶0040-0042[In this illustrative example, the central computer system 106 also wirelessly communicates with a plurality of user interface units 114… These user interface units 114 generally provide a user interface for interaction with the system…. In some embodiments, the user interface units 114 may be general purpose computer devices that include computer programming code to allow it to interact with the system 106… user interface units 114 may be operated by customers of the shopping facility or may be operated by workers at the shopping facility, such as facility employees (associates or colleagues), vendors, suppliers, contractors, etc.]).
Although High discloses the products being inspected, received and updating a database, High does not explicitly disclose in response to receiving a second message confirming that products have been received and updating a database to indicate that the first subset of products is available for sale.
However, Zimet et al., hereinafter, Zimet, teaches indicating that products are available for sale following inspection of the products (¶¶0052-0053[Once received, inventory may be audited, for example. Auditing may include sorting and/or inspecting received physical inventory, such as equipment… Units that pass, and are to be made available for storage or processed for resale, may proceed either to diagnostics, or to storage. Diagnostics may include testing to insure proper functionality of a device, and or to ensure proper security, such as the removal of all identifying information from a computer hard drive. Items that fail the diagnostic stage may proceed to demanufacturing or disposal. Items that pass the diagnostic stage may proceed to staging, where the diagnosed items may be cleared for sale or redeployment. Alternatively, units that pass may proceed to client storage, where equipment or inventory is prepared for storage, and/or stored for reuse, redeployment, or resale.]).
The system of Zimet is applicable to the system of High as they share characteristics and capabilities, namely, they are both targeted to online selling of goods and services. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the inspection process as disclosed by High to include messages confirming that products have been received and are available for sale as taught by Zimet. One of ordinary skill in the art would have been motivated to expand the system of High in order to provide an inventory tracking system that tracks the status of all items within the inventory tracking system, and tracks separately, but in communication with, the inventory tracking system auction items, items for sale, items destroyed, and/or reconditioned items (¶0010).
Although High discloses validating products by scanning, High in view of Zimet does not explicitly teach determining whether a time of at least one scan event associated with the second subset of products is within a preset time range, wherein the preset time range is determined by one or more machine learning models trained to predict one or more lead times for the second subset of products.
However, Fernandes et al., hereinafter, Fernandes, teaches determining whether a time of an event associated with products is within a range and predicting lead times for products using machine learning models (¶0038[In the embodiment of FIG. 3, the computing device 120 also includes or is coupled to a lead time variability generator 324. The lead time variability generator 324 is configured to analyze the electronic data obtained from the at least one electronic database to determine an estimated actual lead time value with respect to the product. In some aspects, the lead time variability generator 324 is programmed to perform one or more of the following functions: calculate a historical lead time for a given interval of time (e.g., 1 year, 2 year, 3 years, etc.) of orders using various dates recorded in the order cycle; predict the lead time for future orders using a probabilistic approach; predict lead time for future orders using a machine learning model incorporating item-, store-, and vendor-based features; and based on the validation methodology, choose the optimal lead time prediction. In some implementations, the lead time variability generator 324 is configured to analyze the historical lead time data to determine the estimated actual lead time value with respect to the product based on: a probabilistic model comprising weighted kernel density, log curve, polynomial curve, univariate spline, cubic spline, and gaussian curve, and/or a machine learning random forest model. In addition, the lead time variability generator 324 may be configured to select the estimated actual lead time value derived via the probabilistic model or the estimated actual lead time value derived via the machine learning random forest model (i.e., best model selection) based on estimated accuracy of the selected model.]).
The system of Fernandes is applicable to the system of High in view of Zimet as they share characteristics and capabilities, namely, they are all targeted to managing product inventory online. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the validation of items as taught by High in view of Zimet to include a machine learning model that predicts time ranges in relation to products as taught by Fernandes. One of ordinary skill in the art would have been motivated to expand the system of High in view of Zimet in order to reduce out-of-stock events and build-up of excess inventory for the products at the retail facility (¶0002).
Regarding Claim 2, High in view of Zimet in view of Fernandes teaches the computer-implemented system of claim 1, High further discloses wherein one or more of the one or more scan events include a current location associated with the plurality of products (¶0215[the motorized transport units are configured to perform numerous different of tasks, such as but not limited to, moving a movable item container, implement scans of products, detect location information… item identification]), and
the at least one processor is further configured to determine whether the current location corresponds to a first zone prior to determining whether one or more products of the plurality of products are associated with a first category (¶0215[the motorized transport units are configured to perform numerous different of tasks, such as… implement scans of products, detect location information, delivery products… interface with customers, shelf facing detection, item identification] in view of ¶0214[The central computer system 106 is configured to receive sensor data, and based on the sensor data identify over time items that are incorrectly located and/or misplaced] in further view of ¶0029[The shopping facility may include one or more of sales floor areas, checkout locations, parking locations, entrance and exit areas, stock room areas, stock receiving areas, hallway areas, common areas shared by merchants, and so on]; Examiner notes that incorrectly placed items is comparable to a category which is determined after determining location).
Regarding Claim 3, High in view of Zimet in view of Fernandes teaches the computer-implemented system of claim 2, High further discloses wherein the first zone is an inbound zone of a destination fulfillment center (¶0029[The shopping facility may include one or more of sales floor areas, checkout locations, parking locations, entrance and exit areas, stock room areas, stock receiving areas, hallway areas, common areas shared by merchants, and so on]; Examiner notes that a stock receiving area is comparable to an inbound zone and a shopping facility is comparable to a fulfilment center).
Regarding Claim 10, High in view of Zimet in view of Fernandes teaches the computer-implemented system of claim 1, High further discloses wherein the product availability comprises a stock amount of each product of the plurality of products (¶0159[In some embodiments, the control circuit 1012 may be further configured to provide an “item out of stock” and/or an item unavailable response to the customer via the user interface device 1035 based on instructions received from the central computer system 1010.]; Examiner notes that an item unavailable response is comparable to a stock amount of zero), and
wherein the graphical user interface comprises a webpage (¶0042[the user interface units 114 may be general purpose computer devices that include computer programming code to allow it to interact with the system 106. For example, such programming may be in the form of an application installed on the user interface unit 114 or in the form of a browser that displays a user interface provided by the central computer system 106 or other remote computer or server (such as a web server)]).
Regarding Claim 11, High discloses a computer-implemented method for optimizing availability of products for display on a graphical user interface, the method comprising (Figs. 1 and 18; ¶0029[Generally speaking, pursuant to various embodiments, systems, devices and methods are provided for assistance of persons at a shopping facility… The shopping facility may be a retail sales facility, or any other type of facility in which products are displayed and/or sold… Various embodiments provide one or more user interfaces to allow various users to interact with the system including the automated mobile devices and/or to directly interact with the automated mobile devices.]):
receiving one or more scan events associated with a plurality of products (Figs. 1, 10, and 17; ¶0214[The central computer system 106 is configured to receive sensor data, and based on the sensor data identify over time items that are incorrectly located and/or misplaced. Further, the central computer system may categorize and/or identify the items.]; Examiner notes that sensor data is comparable to scan events);
retrieving, from a database, information associated with each product of the plurality of products (Figs. 1, 17 and 18; ¶¶0241-0243[The sensor data is evaluated relative to known data, such as, but not limited to, an item database, index or the like that maintains information about different potential items that may be identified, imaging database that maintains image information corresponding to known items, other such databases, or combination of two or more of such databases... The sensor data may be acquired while a motorized transport unit is performing other tasks or specifically collecting sensor data that can be used to detect potential items… A bar code scanner and/or RFID sensor can be used to obtain identifying information about an item.]);
determining, based on the retrieved information, whether one or more products of the plurality of products are associated with a first category (Fig. 10; ¶0214[The central computer system 106 is configured to receive sensor data, and based on the sensor data identify over time items that are incorrectly located and/or misplaced. Further, the central computer system may categorize and/or identify the items. Based on the categorization and/or identification, the central computer system can determine how to address these items] in view of ¶0241 which discloses the retrieved information);
in response to determining that a first subset of products of the plurality of products is associated with a second category different from the first category (Fig. 1; ¶¶0213-0214[For example… systems, apparatuses, processes and methods are provided herein that allow for addressing incorrectly placed items… In some instances, for example, the central computer system may communicate instructions to cause the item to be retrieved and transported to one of multiple predefined locations.]; Examiner notes that incorrectly placed items are comparable to a second category different from a first category of items that are correctly placed):
transmitting a first message to at least one user device to cause the first subset of products to be moved to a first location for inspection, wherein transmitting the first message to the at least one user device causes one or more automated transport machines to move the first subset of products to the first location (Fig. 1; ¶¶0213-0228[Once categorized, the central computer system can determine how the item is to be addressed. This can include leaving the item where it was identified, transporting the item to a predefined area corresponding to the categorization, or the like. In some instances, for example, the central computer system may contact a shopping facility worker to retrieve the item (e.g., communication to a user interface unit 114 with information specifying where the item is located within the shopping facility, instructions regarding what the worker may need to assist the worker in retrieving the item… the central computer system may communicate instructions to one or more motorized transport units to cause the one or more motorized transport units to retrieve the detected item and transport the item to one of multiple different predefined locations] in view of ¶0029[Generally, the system makes use of automated, robotic mobile devices, e.g., motorized transport units, that are capable of self-powered movement through a space of the shopping facility and providing any number of functions.] and ¶0245[In some instances, such unknown categorized items may be routed to a particular worker, one of one or more predefined bins, or the like that allow a worker to inspect and determine how the item is to be handled (e.g., reviewed to see whether it should be routed to lost and found, recycle bins, waste bin, etc.)]; Examiner notes that a “motorized transport unit” is comparable to an “automated transport machine”), and
that the first subset of products has been inspected and received, updating the database (Fig. 1; ¶0225[The detection of an incorrectly placed item can, in some instances, include determining that an item is not in a place where an item is expected… This mapping and/or scan data can be updated as items are moved and/or products are placed in feature locations… Image data from… workers' user interface units, and/or other such imaging data can be image processed and compared to mappings, scans and/or images of what is expected]; Examiner notes that the mapping and scan data is comparable to a second message, in view of ¶0264[the sensor device 1842 may be include one or more sensors for detecting item characteristic comprising one or more of: item appearance (e.g. color, reflectiveness, pattern, etc.), item shape, item weight, item density, item text, item identifier, item barcode, item condition (e.g. dirty, damaged, etc.), etc.]; Examiner notes that detecting item characteristics is comparable to inspecting the products, and ¶0239[The central computer system typically accesses and evaluates sensor data and/or determined characteristics relative to multiple database sources of various characteristics, images, data, and the like] in view of ¶0039[In some embodiments, the at least one database 126 may store data pertaining to one or more of: shopping facility mapping data, customer data, customer shopping data and patterns, inventory data, product pricing data, and so on.]);
in response to determining that a second subset of products of the plurality of products is associated with the first category, validating the second subset of products by at least one scan event associated with the second subset of products (¶0242[A bar code scanner and/or RFID sensor can be used to obtain identifying information about an item. Some embodiments use different sensor data to confirm and/or further narrow potential categorization and/or identification (e.g., a weight of an item can be compared with known weight associated with a bar code detected to evaluate completeness of the item).]in view of ¶0150[Since an MTU system may have access to item inventory information, the system may locate various items in the store and validate that the inventory count matches what is actually on the shelf]; Examiner notes that confirming categorization of an item is comparable to validating the products);
based on validation of the second subset of products, updating the database to indicate that the second subset of products is available for sale (Fig. 10; ¶0155[FIG. 10 illustrates a block diagram of a system 1000 for determining item availability as configured in accordance with various embodiments of these teachings. The system 1000 includes a central computer system 1010, an inventory database 1020, and an MTU 1030. The system is configured to determine whether an item is out of stock according to the inventory database 1020 and determine whether an item is available for purchase on the shopping floor based on information gathered by the MTU 1030] in view of ¶0239[The central computer system typically accesses and evaluates sensor data and/or determined characteristics relative to multiple database sources of various characteristics, images, data, and the like]);
generating a graphical user interface based on the updated database, the graphical user interface comprising a product availability for each product of a plurality of products (¶0166[In yet another example, the system may determine whether the item is available for purchase online and present the user with an option to purchase the item online (e.g. send a link to the product, add the product to the user's online shopping cart). In some embodiments, the system may select from one or more of the out of stock responses based on one or more of the customer's shopping history, item type, item availability in another store, distance to the alternate store, item availability for online purchase, etc.] in view of ¶0042[In some embodiments, the user interface units 114 may be general purpose computer devices that include computer programming code to allow it to interact with the system 106… user interface units 114 may be operated by customers of the shopping facility or may be operated by workers at the shopping facility, such as facility employees (associates or colleagues), vendors, suppliers, contractors, etc.]; Examiner notes that responses indicating stock levels of an item is comparable to indicating product availability of items); and
transmitting the graphical user interface to at least one customer device (Fig. 1; ¶¶0040-0042[In this illustrative example, the central computer system 106 also wirelessly communicates with a plurality of user interface units 114… These user interface units 114 generally provide a user interface for interaction with the system…. In some embodiments, the user interface units 114 may be general purpose computer devices that include computer programming code to allow it to interact with the system 106… user interface units 114 may be operated by customers of the shopping facility or may be operated by workers at the shopping facility, such as facility employees (associates or colleagues), vendors, suppliers, contractors, etc.]).
Although High discloses the products being inspected, received and updating a database, High does not explicitly disclose in response to receiving a second message confirming that products have been received and updating a database to indicate that the first subset of products is available for sale.
However, Zimet teaches indicating that products are available for sale following inspection of the products (¶¶0052-0053[Once received, inventory may be audited, for example. Auditing may include sorting and/or inspecting received physical inventory, such as equipment… Units that pass, and are to be made available for storage or processed for resale, may proceed either to diagnostics, or to storage. Diagnostics may include testing to insure proper functionality of a device, and or to ensure proper security, such as the removal of all identifying information from a computer hard drive. Items that fail the diagnostic stage may proceed to demanufacturing or disposal. Items that pass the diagnostic stage may proceed to staging, where the diagnosed items may be cleared for sale or redeployment. Alternatively, units that pass may proceed to client storage, where equipment or inventory is prepared for storage, and/or stored for reuse, redeployment, or resale.]).
The method of Zimet is applicable to the method of High as they share characteristics and capabilities, namely, they are both targeted to online selling of goods and services. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the inspection process as disclosed by High to include messages confirming that products have been received and are available for sale as taught by Zimet. One of ordinary skill in the art would have been motivated to expand the method of High in order to provide an inventory tracking system that tracks the status of all items within the inventory tracking system, and tracks separately, but in communication with, the inventory tracking system auction items, items for sale, items destroyed, and/or reconditioned items (¶0010).
Although High discloses validating products by scanning, High in view of Zimet does not explicitly teach determining whether a time of at least one scan event associated with the second subset of products is within a preset time range, wherein the preset time range is determined by one or more machine learning models trained to predict one or more lead times for the second subset of products.
However, Fernandes teaches determining whether a time of an event associated with products is within a range and predicting lead times for products using machine learning models (¶0038[In the embodiment of FIG. 3, the computing device 120 also includes or is coupled to a lead time variability generator 324. The lead time variability generator 324 is configured to analyze the electronic data obtained from the at least one electronic database to determine an estimated actual lead time value with respect to the product. In some aspects, the lead time variability generator 324 is programmed to perform one or more of the following functions: calculate a historical lead time for a given interval of time (e.g., 1 year, 2 year, 3 years, etc.) of orders using various dates recorded in the order cycle; predict the lead time for future orders using a probabilistic approach; predict lead time for future orders using a machine learning model incorporating item-, store-, and vendor-based features; and based on the validation methodology, choose the optimal lead time prediction. In some implementations, the lead time variability generator 324 is configured to analyze the historical lead time data to determine the estimated actual lead time value with respect to the product based on: a probabilistic model comprising weighted kernel density, log curve, polynomial curve, univariate spline, cubic spline, and gaussian curve, and/or a machine learning random forest model. In addition, the lead time variability generator 324 may be configured to select the estimated actual lead time value derived via the probabilistic model or the estimated actual lead time value derived via the machine learning random forest model (i.e., best model selection) based on estimated accuracy of the selected model.]).
The method of Fernandes is applicable to the method of High in view of Zimet as they share characteristics and capabilities, namely, they are all targeted to managing product inventory online. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the validation of items as taught by High in view of Zimet to include a machine learning model that predicts time ranges in relation to products as taught by Fernandes. One of ordinary skill in the art would have been motivated to expand the method of High in view of Zimet in order to reduce out-of-stock events and build-up of excess inventory for the products at the retail facility (¶0002).
Regarding Claim 12, High in view of Zimet in view of Fernandes teaches the computer-implemented method of claim 11, High further discloses wherein one or more of the one or more scan events include a current location associated with the plurality of products (¶0215[the motorized transport units are configured to perform numerous different of tasks, such as but not limited to, moving a movable item container, implement scans of products, detect location information… item identification]), and
the method further comprises determining whether the current location corresponds to a first zone prior to determining whether one or more products of the plurality of products are associated with a first category (¶0215[the motorized transport units are configured to perform numerous different of tasks, such as… implement scans of products, detect location information, delivery products… interface with customers, shelf facing detection, item identification] in view of ¶0214[The central computer system 106 is configured to receive sensor data, and based on the sensor data identify over time items that are incorrectly located and/or misplaced] in further view of ¶0029[The shopping facility may include one or more of sales floor areas, checkout locations, parking locations, entrance and exit areas, stock room areas, stock receiving areas, hallway areas, common areas shared by merchants, and so on]; Examiner notes that incorrectly placed items is comparable to a category which is determined after determining location).
Regarding Claim 13, High in view of Zimet in view of Fernandes teaches the computer-implemented method of claim 12, High further discloses wherein the first zone is an inbound zone of a destination fulfillment center (¶0029[The shopping facility may include one or more of sales floor areas, checkout locations, parking locations, entrance and exit areas, stock room areas, stock receiving areas, hallway areas, common areas shared by merchants, and so on]; Examiner notes that a stock receiving area is comparable to an inbound zone and a shopping facility is comparable to a fulfilment center).
Regarding Claim 19, High in view of Zimet in view of Fernandes teaches the computer-implemented method of claim 11, High further discloses wherein the product availability comprises a stock amount of each product of the plurality of products (¶0159[In some embodiments, the control circuit 1012 may be further configured to provide an “item out of stock” and/or an item unavailable response to the customer via the user interface device 1035 based on instructions received from the central computer system 1010.]; Examiner notes that an item unavailable response is comparable to a stock amount of zero), and
wherein the graphical user interface comprises a webpage (¶0042[the user interface units 114 may be general purpose computer devices that include computer programming code to allow it to interact with the system 106. For example, such programming may be in the form of an application installed on the user interface unit 114 or in the form of a browser that displays a user interface provided by the central computer system 106 or other remote computer or server (such as a web server)]).
Regarding Claim 20, High discloses a computer-implemented system for optimizing availability of products for display on a graphical user interface, the system comprising (Figs. 1 and 18; ¶0029[Generally speaking, pursuant to various embodiments, systems, devices and methods are provided for assistance of persons at a shopping facility… The shopping facility may be a retail sales facility, or any other type of facility in which products are displayed and/or sold… Various embodiments provide one or more user interfaces to allow various users to interact with the system including the automated mobile devices and/or to directly interact with the automated mobile devices.]):
a memory storing instructions (Fig. 1; ¶0033[In the example of FIG. 1, a shopping assistance system 100 is implemented in whole or in part at a shopping facility 101… having at least one control circuit 108, at least one memory 110 and at least one network interface 112; at least one user interface unit 114]); and
at least one processor configured to execute the instructions to perform steps comprising (Fig. 1; ¶0033 in view of ¶0261[The central computer system 1820 includes a control circuit 1821 and a memory 1822, and may be generally referred to as a processor-based device.]):
receiving one or more scan events associated with a plurality of products (Figs. 1, 10, and 17; ¶0214[The central computer system 106 is configured to receive sensor data, and based on the sensor data identify over time items that are incorrectly located and/or misplaced. Further, the central computer system may categorize and/or identify the items.]; Examiner notes that sensor data is comparable to scan events);
determining whether one or more products of the plurality of products are associated with a first category (Fig. 10; ¶0214[The central computer system 106 is configured to receive sensor data, and based on the sensor data identify over time items that are incorrectly located and/or misplaced. Further, the central computer system may categorize and/or identify the items. Based on the categorization and/or identification, the central computer system can determine how to address these items] in view of ¶0241 which discloses the retrieved information);
in response to determining that a first subset of products of the plurality of products is associated with a second category different from the first category (Fig. 1; ¶¶0213-0214[For example… systems, apparatuses, processes and methods are provided herein that allow for addressing incorrectly placed items… In some instances, for example, the central computer system may communicate instructions to cause the item to be retrieved and transported to one of multiple predefined locations.]; Examiner notes that incorrectly placed items are comparable to a second category different from a first category of items that are correctly placed):
causing inspection of the first subset of products by transmitting instructions to cause one or more automated transport machines to move the first subset of products to a first location (Fig. 1; ¶¶0213-0228[Once categorized, the central computer system can determine how the item is to be addressed. This can include leaving the item where it was identified, transporting the item to a predefined area corresponding to the categorization, or the like. In some instances, for example, the central computer system may contact a shopping facility worker to retrieve the item (e.g., communication to a user interface unit 114 with information specifying where the item is located within the shopping facility, instructions regarding what the worker may need to assist the worker in retrieving the item… the central computer system may communicate instructions to one or more motorized transport units to cause the one or more motorized transport units to retrieve the detected item and transport the item to one of multiple different predefined locations] in view of ¶0029[Generally, the system makes use of automated, robotic mobile devices, e.g., motorized transport units, that are capable of self-powered movement through a space of the shopping facility and providing any number of functions.] and ¶0245[In some instances, such unknown categorized items may be routed to a particular worker, one of one or more predefined bins, or the like that allow a worker to inspect and determine how the item is to be handled (e.g., reviewed to see whether it should be routed to lost and found, recycle bins, waste bin, etc.)]; Examiner notes that a “motorized transport unit” is comparable to an “automated transport machine”), and
updating a database to indicate that the first subset of products is available for sale (Fig. 1; ¶0225[The detection of an incorrectly placed item can, in some instances, include determining that an item is not in a place where an item is expected… This mapping and/or scan data can be updated as items are moved and/or products are placed in feature locations… Image data from… workers' user interface units, and/or other such imaging data can be image processed and compared to mappings, scans and/or images of what is expected]; Examiner notes that the mapping and scan data is comparable to a second message, in view of ¶0264[the sensor device 1842 may be include one or more sensors for detecting item characteristic comprising one or more of: item appearance (e.g. color, reflectiveness, pattern, etc.), item shape, item weight, item density, item text, item identifier, item barcode, item condition (e.g. dirty, damaged, etc.), etc.]; Examiner notes that detecting item characteristics is comparable to inspecting the products, and ¶0239[The central computer system typically accesses and evaluates sensor data and/or determined characteristics relative to multiple database sources of various characteristics, images, data, and the like] in view of ¶0039[In some embodiments, the at least one database 126 may store data pertaining to one or more of: shopping facility mapping data, customer data, customer shopping data and patterns, inventory data, product pricing data, and so on.]);
in response to determining that a second subset of products of the plurality of products is associated with the first category, validating the second subset of products, wherein validating comprises (¶0242[A bar code scanner and/or RFID sensor can be used to obtain identifying information about an item. Some embodiments use different sensor data to confirm and/or further narrow potential categorization and/or identification (e.g., a weight of an item can be compared with known weight associated with a bar code detected to evaluate completeness of the item).]in view of ¶0150[Since an MTU system may have access to item inventory information, the system may locate various items in the store and validate that the inventory count matches what is actually on the shelf]; Examiner notes that confirming categorization of an item is comparable to validating the products):
determining whether a scan stored in a received scan event associated with the second subset of products (¶0247[Further, in some instances, one or more… scans, and/or video of the item may be maintained in the database and/or references in the database (e.g., link to access a separate memory storage and/or database)] in view of ¶0220[the central computer system accesses and/or maintains one or more databases, indexes, arrays, spreadsheets or the like]); and
determining whether a product identifier associated with the second subset of products is included in a predetermined list of identifiers (Figs. 7 and 11; ¶¶0162-0166[In step 1113, the system queries an inventory database to determine whether the item requested in step 710 is in stock. The inventory database may have stored upon it a plurality of item identifiers (product name, product type, barcode, RFID tag, etc.) and an estimated quantity of each item in the store inventory. The recorded quantity in the inventory database may be based on monitoring, receiving, and sales of each item. In some embodiments, if the item request in step 1110 identifies an item type or category that includes multiple unique items, the system may check the in-stock status of each item matching the type or category.]);
based on validation of the second subset of products, updating the database to indicate that the second subset of products is available for sale (Fig. 10; ¶0155[FIG. 10 illustrates a block diagram of a system 1000 for determining item availability as configured in accordance with various embodiments of these teachings. The system 1000 includes a central computer system 1010, an inventory database 1020, and an MTU 1030. The system is configured to determine whether an item is out of stock according to the inventory database 1020 and determine whether an item is available for purchase on the shopping floor based on information gathered by the MTU 1030] in view of ¶0239[The central computer system typically accesses and evaluates sensor data and/or determined characteristics relative to multiple database sources of various characteristics, images, data, and the like]);
generating a graphical user interface based on the updated database, the graphical user interface comprising a product availability for each product of a plurality of products (¶0166[In yet another example, the system may determine whether the item is available for purchase online and present the user with an option to purchase the item online (e.g. send a link to the product, add the product to the user's online shopping cart). In some embodiments, the system may select from one or more of the out of stock responses based on one or more of the customer's shopping history, item type, item availability in another store, distance to the alternate store, item availability for online purchase, etc.] in view of ¶0042[In some embodiments, the user interface units 114 may be general purpose computer devices that include computer programming code to allow it to interact with the system 106… user interface units 114 may be operated by customers of the shopping facility or may be operated by workers at the shopping facility, such as facility employees (associates or colleagues), vendors, suppliers, contractors, etc.]; Examiner notes that responses indicating stock levels of an item is comparable to indicating product availability of items); and
transmitting the graphical user interface to at least one customer device (Fig. 1; ¶¶0040-0042[In this illustrative example, the central computer system 106 also wirelessly communicates with a plurality of user interface units 114… These user interface units 114 generally provide a user interface for interaction with the system…. In some embodiments, the user interface units 114 may be general purpose computer devices that include computer programming code to allow it to interact with the system 106… user interface units 114 may be operated by customers of the shopping facility or may be operated by workers at the shopping facility, such as facility employees (associates or colleagues), vendors, suppliers, contractors, etc.]).
Although High discloses updating a database to indicate that the first subset of products is available for sale, High does not explicitly disclose updating a database based on at least the inspection.
However, Zimet teaches indicating that products are available for sale following inspection of the products (¶¶0052-0053[Once received, inventory may be audited, for example. Auditing may include sorting and/or inspecting received physical inventory, such as equipment… Units that pass, and are to be made available for storage or processed for resale, may proceed either to diagnostics, or to storage. Diagnostics may include testing to insure proper functionality of a device, and or to ensure proper security, such as the removal of all identifying information from a computer hard drive. Items that fail the diagnostic stage may proceed to demanufacturing or disposal. Items that pass the diagnostic stage may proceed to staging, where the diagnosed items may be cleared for sale or redeployment. Alternatively, units that pass may proceed to client storage, where equipment or inventory is prepared for storage, and/or stored for reuse, redeployment, or resale.]).
The system of Zimet is applicable to the system of High as they share characteristics and capabilities, namely, they are both targeted to online selling of goods and services. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the inspection process as disclosed by High to include messages confirming that products have been received and are available for sale as taught by Zimet. One of ordinary skill in the art would have been motivated to expand the system of High in order to provide an inventory tracking system that tracks the status of all items within the inventory tracking system, and tracks separately, but in communication with, the inventory tracking system auction items, items for sale, items destroyed, and/or reconditioned items (¶0010).
Although High discloses determining a scan being present and determining product ID being in a list, High in view of Zimet does not explicitly teach determining whether an event time is within a preset time range, wherein the preset time range is determined by one or more machine learning models trained to predict one or more lead times for the second subset of products.
However, Fernandes teaches determining whether a time of an event associated with products is within a range and predicting lead times for products using machine learning models (¶0038[In the embodiment of FIG. 3, the computing device 120 also includes or is coupled to a lead time variability generator 324. The lead time variability generator 324 is configured to analyze the electronic data obtained from the at least one electronic database to determine an estimated actual lead time value with respect to the product. In some aspects, the lead time variability generator 324 is programmed to perform one or more of the following functions: calculate a historical lead time for a given interval of time (e.g., 1 year, 2 year, 3 years, etc.) of orders using various dates recorded in the order cycle; predict the lead time for future orders using a probabilistic approach; predict lead time for future orders using a machine learning model incorporating item-, store-, and vendor-based features; and based on the validation methodology, choose the optimal lead time prediction. In some implementations, the lead time variability generator 324 is configured to analyze the historical lead time data to determine the estimated actual lead time value with respect to the product based on: a probabilistic model comprising weighted kernel density, log curve, polynomial curve, univariate spline, cubic spline, and gaussian curve, and/or a machine learning random forest model. In addition, the lead time variability generator 324 may be configured to select the estimated actual lead time value derived via the probabilistic model or the estimated actual lead time value derived via the machine learning random forest model (i.e., best model selection) based on estimated accuracy of the selected model.]).
The system of Fernandes is applicable to the system of High in view of Zimet as they share characteristics and capabilities, namely, they are all targeted to managing product inventory online. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the validation of items as taught by High in view of Zimet to include a machine learning model that predicts time ranges in relation to products as taught by Fernandes. One of ordinary skill in the art would have been motivated to expand the system of High in view of Zimet in order to reduce out-of-stock events and build-up of excess inventory for the products at the retail facility (¶0002).
Claim(s) 4, 5, 8, 9, 14, 15, and 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over High in view of Zimet in view of Fernandes in further view of Francis et al. (US 2024/0303594 A1 [previously cited]).
Regarding Claim 4, High in view of Zimet in view of Fernandes teaches the computer-implemented system of claim 1, High further discloses wherein validating the second subset of products comprises:
determining whether a scan time stored in a received scan event associated with the second subset of products (¶0247[Further, in some instances, one or more… scans, and/or video of the item may be maintained in the database and/or references in the database (e.g., link to access a separate memory storage and/or database)] in view of ¶0220[the central computer system accesses and/or maintains one or more databases, indexes, arrays, spreadsheets or the like]);
determining, using the retrieved information from the database, whether a product identifier associated with the second subset of products is included in a predetermined list of identifiers (Figs. 7 and 11; ¶¶0162-0166[In step 1113, the system queries an inventory database to determine whether the item requested in step 710 is in stock. The inventory database may have stored upon it a plurality of item identifiers (product name, product type, barcode, RFID tag, etc.) and an estimated quantity of each item in the store inventory. The recorded quantity in the inventory database may be based on monitoring, receiving, and sales of each item. In some embodiments, if the item request in step 1110 identifies an item type or category that includes multiple unique items, the system may check the in-stock status of each item matching the type or category.]);
determining that the scan is within the preset and determining that the product identifier is included in the predetermined list of identifiers, updating the database to indicate that the second subset of products is available for sale (¶0247[Further, in some instances, one or more… scans, and/or video of the item may be maintained in the database and/or references in the database (e.g., link to access a separate memory storage and/or database)] in view of ¶0220[the central computer system accesses and/or maintains one or more databases, indexes, arrays, spreadsheets or the like] In further view of ¶¶0155-00166[The system 1000 includes a central computer system 1010, an inventory database 1020, and an MTU 1030. The system is configured to determine whether an item is out of stock according to the inventory database 1020 and determine whether an item is available for purchase on the shopping floor based on information gathered by the MTU 1030]); and
in response to determining that the scan time is not within the present time range or determining that the product identifier is included in the predetermined list of identifiers, forgoing updating the database to indicate that the second subset of products is available for sale (¶¶0162-0166[In step 1113, the system queries an inventory database to determine whether the item requested in step 710 is in stock. The inventory database may have stored upon it a plurality of item identifiers (product name, product type, barcode, RFID tag, etc.) and an estimated quantity of each item in the store inventory. The recorded quantity in the inventory database may be based on monitoring, receiving, and sales of each item. In some embodiments, if the item request in step 1110 identifies an item type or category that includes multiple unique items, the system may check the in-stock status of each item matching the type or category.]] in view of ¶0220[the central computer system accesses and/or maintains one or more databases, indexes, arrays, spreadsheets or the like]).
Although High discloses determining a scan being present and determining product ID being in a list, High in view of Zimet in view of Fernandes does not explicitly teach determining whether a scan time is within a preset time range.
Although High discloses determining a scan being present and determining product ID being in a list, High in view of Zimet in view of Fernandes does not explicitly teach in response to determining that the scan time is within the preset time range and determining that the product identifier is not included in the predetermined list of identifiers.
However, Francis et al., hereinafter, Francis, teaches determining the scan time being within a time range and the product not being included in a list of identifiers (¶0297[Similarly, if a new item is scanned that has not been previously included in the most recent item association table, the system may update the item association table to include the new item the first time the new item ID is scanned.] in view of ¶0347[In some implementations, one or more of the MSDs and/or the CCS may be configured to determine that two items are located adjacent to one another upon an MSD scanning the items and determining that the corresponding scan times are within a predetermined threshold amount of time. In some implementations, one or more of the MSDs and/or the CCS may be configured to determine that two items are located adjacent to one another upon an MSD scanning the items and determining that the corresponding scan times are within a predetermined threshold amount of time N number of times (e.g., a threshold number of times).]).
The system of Francis is applicable to the system of High in view of Zimet in view of Fernandes as they share characteristics and capabilities, namely, they are all targeted to online selling of goods and services. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the scan events as taught by High in view of Zimet in view of Fernandes to include time of scan and time ranges as taught by Francis. One of ordinary skill in the art would have been motivated to expand the system of High in view of Zimet in view of Fernandes in order to efficiently pick items from customer orders (¶0090).
Regarding Claim 5, High in view of Zimet in view of Fernandes in view of Francis teaches the computer-implemented system of claim 4, High further discloses wherein updating the database comprises adding the product identifier to a first table of the database (Fig. 1; ¶0152[An MTU may include count-it capabilities which may include visually counting merchandise, looking up the inventory expected to be on hand, and providing alerts and corrections when discrepancies exist.] and ¶0162[The inventory database 1020 may be a non-transitory memory storage that stores one or more inventory information of a plurality of items… The inventory database may have stored upon it a plurality of item identifiers (product name, product type, barcode, RFID tag, etc.) and an estimated quantity of each item in the store inventory]; Examiner notes making inventory corrections is comparable to adding products to an inventory database).
Regarding Claim 8, High in view of Zimet in view of Fernandes in view of Francis teaches the computer-implemented system of claim 4, High further discloses wherein the retrieved information from the database includes a category associated with the at least one identifier (Figs. 7 and 11; ¶¶0162-0166[In step 1113, the system queries an inventory database to determine whether the item requested in step 710 is in stock. The inventory database may have stored upon it a plurality of item identifiers (product name, product type, barcode, RFID tag, etc.) and an estimated quantity of each item in the store inventory]; Examiner notes that product type is comparable to a category).
Regarding Claim 9, High in view of Zimet in view of Fernandes in view of Francis teaches the computer-implemented system of claim 8, High further discloses wherein the category is a transfer category (¶0263[In some embodiments, predefined categories may comprise one or more: recyclable items, compostable items, likely customer items, merchandise, merchandise-like items, valuable items, metal items, glass items, paper items, plastic items, and trash]; Examiner notes that categories such as recyclable and trash are comparable to transfer categories that get transferred to other facilities).
Regarding Claim 14, High in view of Zimet in view of Fernandes teaches the computer-implemented method of claim 11, High further discloses wherein validating the second subset of products comprises:
determining whether a scan time stored in a received scan event associated with the second subset of products (¶0247[Further, in some instances, one or more… scans, and/or video of the item may be maintained in the database and/or references in the database (e.g., link to access a separate memory storage and/or database)] in view of ¶0220[the central computer system accesses and/or maintains one or more databases, indexes, arrays, spreadsheets or the like]);
determining, using the retrieved information from the database, whether a product identifier associated with the second subset of products is included in a predetermined list of identifiers (Figs. 7 and 11; ¶¶0162-0166[In step 1113, the system queries an inventory database to determine whether the item requested in step 710 is in stock. The inventory database may have stored upon it a plurality of item identifiers (product name, product type, barcode, RFID tag, etc.) and an estimated quantity of each item in the store inventory. The recorded quantity in the inventory database may be based on monitoring, receiving, and sales of each item. In some embodiments, if the item request in step 1110 identifies an item type or category that includes multiple unique items, the system may check the in-stock status of each item matching the type or category.]);
determining that the scan is within the preset and determining that the product identifier is included in the predetermined list of identifiers, updating the database to indicate that the second subset of products is available for sale (¶0247[Further, in some instances, one or more… scans, and/or video of the item may be maintained in the database and/or references in the database (e.g., link to access a separate memory storage and/or database)] in view of ¶0220[the central computer system accesses and/or maintains one or more databases, indexes, arrays, spreadsheets or the like] In further view of ¶¶0155-00166[The system 1000 includes a central computer system 1010, an inventory database 1020, and an MTU 1030. The system is configured to determine whether an item is out of stock according to the inventory database 1020 and determine whether an item is available for purchase on the shopping floor based on information gathered by the MTU 1030]); and
in response to determining that the scan time is not within the present time range or determining that the product identifier is included in the predetermined list of identifiers, forgoing updating the database to indicate that the second subset of products is available for sale (¶¶0162-0166[In step 1113, the system queries an inventory database to determine whether the item requested in step 710 is in stock. The inventory database may have stored upon it a plurality of item identifiers (product name, product type, barcode, RFID tag, etc.) and an estimated quantity of each item in the store inventory. The recorded quantity in the inventory database may be based on monitoring, receiving, and sales of each item. In some embodiments, if the item request in step 1110 identifies an item type or category that includes multiple unique items, the system may check the in-stock status of each item matching the type or category.]] in view of ¶0220[the central computer system accesses and/or maintains one or more databases, indexes, arrays, spreadsheets or the like]).
Although High discloses determining a scan being present and determining product ID being in a list, High in view of Zimet in view of Fernandes does not explicitly teach determining whether a scan time is within a preset time range.
Although High discloses determining a scan being present and determining product ID being in a list, High in view of Zimet in view of Fernandes does not explicitly teach in response to determining that the scan time is within the preset time range and determining that the product identifier is not included in the predetermined list of identifiers.
However, Francis teaches determining the scan time being within a time range and the product not being included in a list of identifiers (¶0297[Similarly, if a new item is scanned that has not been previously included in the most recent item association table, the system may update the item association table to include the new item the first time the new item ID is scanned.] in view of ¶0347[In some implementations, one or more of the MSDs and/or the CCS may be configured to determine that two items are located adjacent to one another upon an MSD scanning the items and determining that the corresponding scan times are within a predetermined threshold amount of time. In some implementations, one or more of the MSDs and/or the CCS may be configured to determine that two items are located adjacent to one another upon an MSD scanning the items and determining that the corresponding scan times are within a predetermined threshold amount of time N number of times (e.g., a threshold number of times).]).
The method of Francis is applicable to the method of High in view of Zimet in view of Fernandes as they share characteristics and capabilities, namely, they are all targeted to online selling of goods and services. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the scan events as taught by High in view of Zimet in view of Fernandes to include time of scan and time ranges as taught by Francis. One of ordinary skill in the art would have been motivated to expand the method of High in view of Zimet in view of Fernandes in order to efficiently pick items from customer orders (¶0090).
Regarding Claim 15, High in view of Zimet in view of Fernandes in view of Francis teaches the computer-implemented method of claim 14, High further discloses wherein updating the database comprises adding the product identifier to a first table of the database (Fig. 1; ¶0152[An MTU may include count-it capabilities which may include visually counting merchandise, looking up the inventory expected to be on hand, and providing alerts and corrections when discrepancies exist.] and ¶0162[The inventory database 1020 may be a non-transitory memory storage that stores one or more inventory information of a plurality of items… The inventory database may have stored upon it a plurality of item identifiers (product name, product type, barcode, RFID tag, etc.) and an estimated quantity of each item in the store inventory]; Examiner notes making inventory corrections is comparable to adding products to an inventory database).
Regarding Claim 18, High in view of Zimet in view of Fernandes in view of Francis teaches the computer-implemented method of claim 14, High further discloses wherein the retrieved information from the database includes a category associated with the at least one identifier (Figs. 7 and 11; ¶¶0162-0166[In step 1113, the system queries an inventory database to determine whether the item requested in step 710 is in stock. The inventory database may have stored upon it a plurality of item identifiers (product name, product type, barcode, RFID tag, etc.) and an estimated quantity of each item in the store inventory]; Examiner notes that product type is comparable to a category), and
wherein the category is a transfer category (¶0263[In some embodiments, predefined categories may comprise one or more: recyclable items, compostable items, likely customer items, merchandise, merchandise-like items, valuable items, metal items, glass items, paper items, plastic items, and trash]; Examiner notes that categories such as recyclable and trash are comparable to transfer categories that get transferred to other facilities).
Claim(s) 6, 7, 16, and 17 is/are rejected under 35 U.S.C. 103 as being unpatentable over High in view of Zimet in view of Fernandes in view of Francis in further view of Gabbai et al. (US 2018/0025310 A1 [previously cited]).
Regarding Claim 6, High in view of Zimet in view of Fernandes in view of Francis teaches the computer-implemented system of claim 5, High further discloses wherein the first table of the database includes one or more product identifiers associated with products that are available for sale (¶0162[The inventory database 1020 may be a non-transitory memory storage that stores one or more inventory information of a plurality of items… The inventory database may have stored upon it a plurality of item identifiers (product name, product type, barcode, RFID tag, etc.) and an estimated quantity of each item in the store inventory]).
Although High discloses a database including a table with identifiers for products, High in view of Zimet in view of Fernandes in further view of Francis does not explicitly teach storing products that have not been stowed and are available.
However, Gabbai et al., hereinafter, Gabbai, teaches a database storing products that have not been stowed (Fig. 2; ¶0022[The server 206 may store the image data in a database 208, which may also store a database model for the inventory distribution based on incoming inventory items, the positions where each incoming inventory item should be stored, and which inventory items should be picked for order fulfillment.]).
The system of Gabbai is applicable to the system of High in view of Zimet in view of Fernandes in further view of Francis as they share characteristics and capabilities, namely, they are all targeted to online selling of goods and services. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the database as taught by High in view of Zimet in view of Fernandes in further view of Francis to include a dataset for not yet stowed products as taught by Gabbai. One of ordinary skill in the art would have been motivated to expand the system of High in view of Zimet in view of Fernandes in further view of Francis so that inventory management efficiency may be improved by making the pick-pack-deliver process more dynamic (¶0018).
Regarding Claim 7, High in view of Zimet in view of Fernandes in view of Francis in view of Gabbai teaches the computer-implemented system of claim 6, High further discloses wherein the database includes a table including one or more identifiers associated with products (¶0162[The inventory database 1020 may be a non-transitory memory storage that stores one or more inventory information of a plurality of items… The inventory database may have stored upon it a plurality of item identifiers (product name, product type, barcode, RFID tag, etc.) and an estimated quantity of each item in the store inventory]).
Although High discloses a database including a table with identifiers for products, High in view of Zimet in view of Fernandes does not explicitly teach a second table including products that have been stowed, and wherein the first table is different from the second table.
However, Francis teaches a second table of products that have been stowed (¶0503[The inventory system may generate inventory data based on the acquired images. Example store inventory data may include, but is not limited to, a list of items (e.g., item IDs) and associated inventory status. Inventory status may indicate whether the item is in-stock (e.g., currently stocked in the store) or out-of-stock (e.g., not currently stocked in the store). In some implementations, the inventory status may indicate a number of items in stock.]).
The system of Francis is applicable to the system of High in view of Zimet in view of Fernandes as they share characteristics and capabilities, namely, they are all targeted to online selling of goods and services. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the database as taught by High in view of Zimet in view of Fernandes to include a dataset for products that have been stowed as taught by Francis. One of ordinary skill in the art would have been motivated to expand the system of High in view of Zimet in view of Fernandes in order to efficiently pick items from customer orders (¶0090).
Regarding Claim 16, High in view of Zimet in view of Fernandes in view of Francis teaches the computer-implemented method of claim 15, High further discloses wherein the first table of the database includes one or more product identifiers associated with products that are available for sale (¶0162[The inventory database 1020 may be a non-transitory memory storage that stores one or more inventory information of a plurality of items… The inventory database may have stored upon it a plurality of item identifiers (product name, product type, barcode, RFID tag, etc.) and an estimated quantity of each item in the store inventory]).
Although High discloses a database including a table with identifiers for products, High in view of Zimet in view of Fernandes in further view of Francis does not explicitly teach storing products that have not been stowed and are available.
However, Gabbai teaches a database storing products that have not been stowed (Fig. 2; ¶0022[The server 206 may store the image data in a database 208, which may also store a database model for the inventory distribution based on incoming inventory items, the positions where each incoming inventory item should be stored, and which inventory items should be picked for order fulfillment.]).
The method of Gabbai is applicable to the method of High in view of Zimet in view of Fernandes in further view of Francis as they share characteristics and capabilities, namely, they are all targeted to online selling of goods and services. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the database as taught by High in view of Zimet in view of Fernandes in further view of Francis to include a dataset for not yet stowed products as taught by Gabbai. One of ordinary skill in the art would have been motivated to expand the method of High in view of Zimet in view of Fernandes in further view of Francis so that inventory management efficiency may be improved by making the pick-pack-deliver process more dynamic (¶0018).
Regarding Claim 17, High in view of Zimet in view of Fernandes in view of Francis in view of Gabbai teaches the computer-implemented method of claim 16, High further discloses wherein the database includes a table including one or more identifiers associated with products (¶0162[The inventory database 1020 may be a non-transitory memory storage that stores one or more inventory information of a plurality of items… The inventory database may have stored upon it a plurality of item identifiers (product name, product type, barcode, RFID tag, etc.) and an estimated quantity of each item in the store inventory]).
Although High discloses a database including a table with identifiers for products, High in view of Zimet in view of Fernandes does not explicitly teach a second table including products that have been stowed, and wherein the first table is different from the second table.
However, Francis teaches a second table of products that have been stowed (¶0503[The inventory system may generate inventory data based on the acquired images. Example store inventory data may include, but is not limited to, a list of items (e.g., item IDs) and associated inventory status. Inventory status may indicate whether the item is in-stock (e.g., currently stocked in the store) or out-of-stock (e.g., not currently stocked in the store). In some implementations, the inventory status may indicate a number of items in stock.]).
The method of Francis is applicable to the method of High in view of Zimet in view of Fernandes as they share characteristics and capabilities, namely, they are all targeted to online selling of goods and services. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the database as taught by High in view of Zimet in view of Fernandes to include a dataset for products that have been stowed as taught by Francis. One of ordinary skill in the art would have been motivated to expand the method of High in view of Zimet in view of Fernandes in order to efficiently pick items from customer orders (¶0090).
Response to Arguments
Applicant’s arguments on pages 12-22 of the remarks filed 10/27/2025, with respect to the previous 35
USC § 101 rejections have been fully considered but are not persuasive.
Applicant argues on pages 12-16 of the remarks that the amended claims do not recite Methods of Organizing Human Activity and cites Enfish for support. Examiner respectfully disagrees. Enfish reflected an improvement to computer functionality and its specification described the prior art and how the invention improved the way the computer stores and retrieves data in memory in combination with the specific data structure recited in the claims that demonstrated eligibility (see MPEP 2106.05(a)(I)). Unlike the claims in Enfish, the additional elements of Applicant’s claims do not pertain to an “improvement” to the functioning of a computer or to another technology (see MPEP 2106.04(a) and 2106.05(a)).
Furthermore, according to the MPEP 2106.04, the question of whether a claim is “directed to” a judicial exception in Step 2A is now evaluated using a two-prong inquiry. Prong One asks if the claim “recites” an abstract idea, law of nature, or natural phenomenon. Under that prong, the mere inclusion of a judicial exception such as a method of organizing human activity in a claim means that the claim “recites” a judicial exception (see MPEP 2106.04 [“The mere inclusion of a judicial exception such as a mathematical formula (which is one of the mathematical concepts identified as an abstract idea in MPEP § 2106.04(a)) in a claim means that the claim "recites" a judicial exception under Step 2A Prong One.”]). Additionally, MPEP 2106.04 instructs examiners to refer to the groupings of abstract ideas enumerated in MPEP 2106.04(a)(2) (i.e., mathematical concepts, certain methods of organizing human activities, and mental processes) in order to identify abstract ideas. Receiving one or more scan events associated with a plurality of products; in response to determining that a first subset of products of the plurality of products is associated with a second category different from the first category: transmitting a first message to at least one user to cause the first subset of products to be moved to a first location for inspection, wherein transmitting the first message to the at least one user causes to move the first subset of products to the first location, and in response to receiving a second message confirming that the first subset of products has been inspected and received, updating to indicate that the first subset of products is available for sale; in response to determining that a second subset of products of the plurality of products is associated with the first category, validating the second subset of products by determining whether a time of at least one scan event associated with the second subset of products is within a preset time range, wherein the preset time range is determined by one or more lead times for the second subset of products; based on validation of the second subset of products, updating to indicate that the second subset of products is available for sale; generating a graphical user interface based on the updated, comprising a product availability for each product of a plurality of products; and transmitting the graphical user interface to at least one customer are commercial or legal interactions because they are directed to advertising, marketing or sales activities or behaviors, and business relations, see MPEP 2106.04(a)(2)(II).
Applicant argues on pages 16-18 of the remarks that the amended claims integrate the abstract idea into a practical application. Examiner respectfully disagrees. Receiving one or more scan events associated with a plurality of products; in response to determining that a first subset of products of the plurality of products is associated with a second category different from the first category: transmitting a first message to at least one user to cause the first subset of products to be moved to a first location for inspection, wherein transmitting the first message to the at least one user causes to move the first subset of products to the first location, and in response to receiving a second message confirming that the first subset of products has been inspected and received, updating to indicate that the first subset of products is available for sale; in response to determining that a second subset of products of the plurality of products is associated with the first category, validating the second subset of products by determining whether a time of at least one scan event associated with the second subset of products is within a preset time range, wherein the preset time range is determined by one or more lead times for the second subset of products; based on validation of the second subset of products, updating to indicate that the second subset of products is available for sale; generating a graphical user interface based on the updated, comprising a product availability for each product of a plurality of products; and transmitting the graphical user interface to at least one customer are all part of the abstract idea. The mere execution of the abstract idea on generic and high-level components such as a graphical user interface, memory, processor, database, device, automated transport machines, or machine learning models does not overcome the 101 rejection or provide technical improvements. These components are described at a high level and as generic in ¶0096, ¶0102, ¶0110, ¶0113 and Fig. 1A of the instant specification.
Applicant cites to ¶¶0004-0005 of the instant specification to show technical improvement on page 17 of the remarks. Examiner respectfully disagrees that the cited paragraphs show technical improvement. Accounting for unstowed items in inventory, optimizing the availability of products, where the availability may indicate that the products are available to sell to a customer and/or available for a customer to purchase, marking indicating, or otherwise considering not yet stowed products as available and providing locations of not yet stowed products to fulfillment center personnel for expedited stowing are all part of the abstract idea and executing the abstract idea on generic and high-level components such as a webpage and graphical user interfaces does not overcome the 101 rejection.
Applicant argues on pages 18-19 that the amended claims provide an inventive concept of optimizing product availability. Examiner respectfully disagrees. Transmitting a first message… wherein transmitting the first message to the at least one user causes to move the first subset of products to the first location, in response to receiving a second message confirming that the first subset of products has been inspected and received, updating to indicate that the first subset of products is available for sale, in response to determining that a second subset of products of the plurality of products is associated with the first category, validating the second subset of products by determining whether a time of at least one scan event associated with the second subset of products is within a preset time range, wherein the preset time range is determined by one or more lead times for the second subset of products, based on validation of the second subset of products, updating to indicate that the second subset of products is available for sale, generating a graphical user interface based on the updated database, comprising a product availability for each product of a plurality of products, and transmitting the graphical user interface to at least one customer are all part of the abstract idea. As noted previously, the additional elements such as a device, one or more automated transport machines, the database, one or more machine learning models trained to predict, the graphical user interface are described in the specification as well-known and generic computer components. Furthermore, the noted components add nothing that is not already present when the steps are considered separately and simply recite steps as performed by a generic computer. Therefore, the amended claims fail to provide significantly more than the judicial exception and does not overcome the rejection.
Applicant argues further that the amended claims overcome limitations in conventional systems. Examiner respectfully disagrees. According to the MPEP 2106.05(a), if it is asserted that the invention improves upon conventional functioning of a computer, or upon conventional technology or technological processes, a technical explanation as to how to implement the invention should be present in the specification. The instant specification does not provide sufficient details such that one of ordinary skill in the art would recognize the claimed invention as providing an improvement. The cited paragraph 0004 simply states an improvement in a conclusory manner. If the specification explicitly sets forth an improvement but in a conclusory manner (i.e., a bare assertion of an improvement without the detail necessary to be apparent to a person of ordinary skill in the art), the examiner should not determine the claim improves technology, see MPEP 2106.05(a).
Applicant argues on pages 20-22 that the previous office action failed to provide evidence for the additional elements being well-understood, routine or conventional. Examiner did not previously state that the additional elements are well-understood, routine, or conventional activity. However, the additional elements fail to provide significantly more also because the claim simply appends well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception. For example, the additional elements of claims 1, 11, and 20 utilize operations the courts have held to be well-understood, routine, and conventional (see: MPEP 2106.05(d)(II)), including at least:
receiving or transmitting data over a network,
storing or retrieving information from memory,
presenting information
Accordingly, Examiner maintains that the invention is directed to a judicial exception without
significantly more. The claims recite an abstract idea. This judicial exception is not integrated into a practical application. The claim(s) do not include additional elements that are sufficient to amount to significantly more than the judicial exception. Thus the 35 USC §101 rejections are maintained.
Applicant’s arguments on pages 22-24 of the remarks filed 10/27/2025, with respect to the previous 35 USC § 103 rejections have been fully considered but are moot in view of the new 103 rejection of the amended claims. Reference Fernandes was added as necessitated by the claim amendments.
As no remarks directed to the specific nature of how the previous art failed to teach the previously presented claims, references High, Zimet, Francis, and Gabbai have been maintained and reference Fernandes has been added in view of the claim amendments.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any extension fee pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the date of this final action.
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/AHOORA LADONI/Examiner, Art Unit 3689
/MARISSA THEIN/Supervisory Patent Examiner, Art Unit 3689