DETAILED ACTION
Status of Claims
Claims 1, 4-11, and 14-20 submitted on 12/10/2025 are pending and have been examined. Claims 1, 4, 11, 14, 19, and 20 have been amended. Claims 2, 3, 12, and 13 have been cancelled.
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. 18/507,785, filed on 11/13/2023 and Application No. 18/299,854, filed on 04/13/2023.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 02/09/2026 has been considered by the examiner.
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, 4-11, and 14-20 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, 4-10, and 20 are directed to a machine and claims 11 and 14-19 are directed to a process (see MPEP 2106.03).
Step 2A, Prong 1
Claim 1, taken as representative, recites at least the following limitations that recite an abstract idea:
optimizing availability of products for display comprising:
receiving a plurality of scan events associated with a plurality of products, wherein each scan event of the plurality of scan events comprises a timestamp and a current location;
determining a plurality of ranges of time by predicting, one or more lead times associated with the plurality of products based at least on historic data, wherein each range of time of the plurality of ranges of time is associated with a destination fulfillment center, and wherein the historic data includes at least one or more past lead times for delivering products to and stowing products at least one destination fulfillment center;
for each scan event of the plurality of scan events:
determining whether the scan event is received within a first range of time of the plurality of ranges of time;
determining whether the current location of the scan event corresponds to a first location, wherein the first location is not the destination fulfillment center;
when the scan event is received within the first range of time and the current location corresponds to the first location,
updating to indicate that a first subset of products of the plurality of products associated with the scan event is available for sale at a first time; and
when the scan event is received after the first range of time and the current location does not correspond to the first location, determining, at a second time after the first time, whether to update to indicate that the first subset of products is available for sale;
generating, at the first time, a graphical user interface, comprising a product availability for each product of the 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. Claims 11 and 20 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 a plurality of scan events associated with a plurality of products, wherein each scan event of the plurality of scan events comprises a timestamp and a current location;
determining a plurality of ranges of time by predicting, using one or more trained machine learning models, one or more lead times associated with the plurality of products based at least on historic data stored in a database, wherein each range of time of the plurality of ranges of time is associated with a destination fulfillment center, and wherein the historic data includes at least one or more past lead times for delivering products to and stowing products at at least one destination fulfillment center;
for each scan event of the plurality of scan events:
determining whether the scan event is received within a first range of time of the plurality of ranges of time;
determining whether the current location of the scan event corresponds to a first location, wherein the first location is not the destination fulfillment center;
when the scan event is received within the first range of time and the current location corresponds to the first location,
updating the database to indicate that a first subset of products of the plurality of products associated with the scan event is available for sale at a first time; and
when the scan event is received after the first range of time and the current location does not correspond to the first location, determining, at a second time after the first time, whether to update the database to indicate that the first subset of products is available for sale;
generating, at the first time, a graphical user interface, the graphical user interface comprising a product availability for each product of the plurality of products; and
transmitting the graphical user interface to at least one customer device.
Claims 11 and 20 include the same additional elements as claim 1.
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 graphical user interfaces and databases (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 ¶0098 and ¶¶0146-0147).
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 4-9 and 14-18 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 4-9 and 14-18 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 4-9 and 14-18 do not introduce any further additional elements.
Thus, dependent claims 4-9 and 14-18 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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
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, 4-6, 10, 14, 15, 19, and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Sayan et al. (US 2012/0191817 A1 [previously cited]) in view of Fernandes et al. (US 2021/0192435 A1) in view of Schoening et al. (US 2020/0250610 A1 [previously cited]).
Regarding Claim 1, Sayan et al., hereinafter, Sayan, discloses a computer-implemented system for optimizing availability of products for display on a graphical user interface, the system comprising (Fig. 2; Abstract):
a memory storing instructions (Fig. 3; ¶0029); and
at least one processor configured to execute the instructions to perform steps comprising: receiving a plurality of scan events associated with a plurality of products, wherein each scan event of the plurality of scan events comprises a timestamp and a current location (Fig. 3; ¶¶0066-0067[When the product tag is scanned (e.g., by a mobile device), the time of scan can be sent along with the indicia information (e.g., code, product identifier), and/or the location of the device to the server 301.] in view of ¶0029 which discloses a processor; Examiner notes that the location of the device is comparable to the current location associated with the scan event and product);
determining a plurality of ranges of time associated with the plurality of products based at least on historic data stored in a database, wherein each range of time of the plurality of ranges of time is associated with a destination fulfillment center (¶0066[When the product tag is scanned (e.g., by a mobile device), the time of scan can be sent along with the indicia information (e.g., code, product identifier), and/or the location of the device to the server 301. The server 301 can then calculate a time difference between the time of scan and the destination time. The time difference calculation may be limited to only being performed when the destination location matches or is similar to (e.g., a pre-defined distance away from) the scanned location. If the time difference is within a pre-defined threshold period (e.g., a number of seconds, minutes, hours, days, etc.), the product has been routed in adherence to the guidelines. A different freshness period and/or threshold period may be stored by the server 301 for each product or code] in view of ¶0081[The product tracking services 405 records data of the messages it receives from the manufacturer. For example, the services 405 can store a record for each unit of goods shipped by the manufacturer in a database on the memory 304. Each record may include product identifying information (e.g., the product identifier, the tracking code, etc.) and origin information (e.g., location of the manufacturer, the manufacturer identifier, time/date of manufacture, time/date of shipment, origin of raw materials used in product, etc.)]; Examiner notes that the time difference calculation is comparable to a range of time and that origin information is comparable to historic data stored);
for each scan event of the plurality of scan events: determining whether the scan event is received within a first range of time of the plurality of ranges of time (¶0066[When the product tag is scanned (e.g., by a mobile device), the time of scan can be sent along with the indicia information (e.g., code, product identifier), and/or the location of the device to the server 301. The server 301 can then calculate a time difference between the time of scan and the destination time. The time difference calculation may be limited to only being performed when the destination location matches or is similar to (e.g., a pre-defined distance away from) the scanned location. If the time difference is within a pre-defined threshold period (e.g., a number of seconds, minutes, hours, days, etc.), the product has been routed in adherence to the guidelines. A different freshness period and/or threshold period may be stored by the server 301 for each product or code.]);
determining whether the current location of the scan event corresponds to a first location, wherein the first location is not the destination fulfillment center (¶0066[The server 301 can then calculate a time difference between the time of scan and the destination time. The time difference calculation may be limited to only being performed when the destination location matches or is similar to (e.g., a pre-defined distance away from) the scanned location.]; Examiner notes that determining whether destination matches or is similar to the scanned location is comparable to determining whether the current location of the scan corresponds to a destination fulfillment center);
when the scan event is received within the first range of time and the current location corresponds to the first location, updating the database to indicate that a first subset of products of the plurality of products associated with the scan event is adherent to guidelines at a first time (¶0066[The server 301 may store a freshness period for each product or for each unique code. The above-described destination time/date can be calculated based on the shipping time/date and the freshness period. For example, the destination time/date can be calculated by adding the freshness period to the shipping time/date. When the product tag is scanned (e.g., by a mobile device), the time of scan can be sent along with the indicia information (e.g., code, product identifier), and/or the location of the device to the server 301. The server 301 can then calculate a time difference between the time of scan and the destination time. The time difference calculation may be limited to only being performed when the destination location matches or is similar to (e.g., a pre-defined distance away from) the scanned location. If the time difference is within a pre-defined threshold period (e.g., a number of seconds, minutes, hours, days, etc.), the product has been routed in adherence to the guidelines. A different freshness period and/or threshold period may be stored by the server 301 for each product or code.] in view of ¶0082[The computer server 301 can also maintain an inventory for the manufacturer. For example, the inventory services 413 of the back-end application 404 can be used to maintain the inventory. The inventory services 413 can update the inventory based on the received manufacturer messages and knowledge of the current inventory (e.g., from access to an inventory server of the manufacturer).]); and
when the scan event is received after the first range of time, determining, at a second time after the first time, whether to update the database to indicate that the first subset of products is adherent to guidelines (¶¶0066-0067[For example, the destination time/date can be calculated by adding the freshness period to the shipping time/date. When the product tag is scanned (e.g., by a mobile device), the time of scan can be sent along with the indicia information (e.g., code, product identifier), and/or the location of the device to the server 301. The server 301 can then calculate a time difference between the time of scan and the destination time. The time difference calculation may be limited to only being performed when the destination location matches or is similar to (e.g., a pre-defined distance away from) the scanned location. If the time difference is within a pre-defined threshold period (e.g., a number of seconds, minutes, hours, days, etc.), the product has been routed in adherence to the guidelines]);
generating, at the first time, a graphical user interface, the graphical user interface comprising a product for each product of the plurality of products (Fig. 2; ¶0026[FIG. 2 illustrates a commerce system according to an exemplary embodiment of the invention. The devices of FIG. 1 are divided into supplier devices 110 and consumer devices 120 and the cloud 100 includes a supplier cloud 101 that interfaces with the supplier devices 110 and a consumer cloud 102 that interfaces with the consumer devices. The supplier devices 110 or the consumer devices 110 include software and hardware to scan product tags 140]); and
transmitting the graphical user interface to at least one customer device (Fig. 2[showing the transmission of the GUI to a customer device via arrows]; ¶0026[FIG. 2 illustrates a commerce system according to an exemplary embodiment of the invention. The devices of FIG. 1 are divided into supplier devices 110 and consumer devices 120 and the cloud 100 includes a supplier cloud 101 that interfaces with the supplier devices 110 and a consumer cloud 102 that interfaces with the consumer devices. The supplier devices 110 or the consumer devices 110 include software and hardware to scan product tags 140]).
Although Sayan discloses determining a plurality of ranges of time based on historic data, Sayan does not explicitly disclose determining a time by predicting, using one or more trained machine learning models, one or more lead times associated with products, and wherein the historic data includes at least one or more past lead times for delivering products to and stowing products at at least one destination fulfillment center.
However, Fernandes et al., hereinafter, Fernandes teaches predicting lead times using a machine learning model and a database storing historic lead times for products at a destination center (¶0076[the machine learning approach is used (step 555), the lead time variability generator 324 outputs data including: predicted lead time, product number, store number, and error based on products arriving early/on time or late, RMSE & MAPE using train and test split based on historical data evidence. Based on the above two models now, using a voting technique on the errors, the lead time variability generator 324 chooses the best model (step 560), and generates the predicted lead time for the product number at the level of the retail facility 110 (step 565).] in view of ¶¶0021-0022[ the electronic database 140 stores electronic data that comprises historical lead time data associated with products stocked at the retail facility 110, historical demand forecast data associated with the products stocked at the retail facility 110, historical sales data associated with the products stocked at the retail facility 110, and order-related data associated with the product stocked at the retail facility 110.]; according to ¶0088 of the instant specification, “A lead time may be associated with the duration of time a product must be stowed… within, or the duration of time it takes a product to be stowed”).
The system of Fernandes is applicable to the system of Sayan as they share characteristics and capabilities, namely, they are both targeted to product inventory management. 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 products stored in a database and ranges of time as disclosed by Sayan to include predicting lead times using machine learning and historic data of past lead times as taught by Fernandes. One of ordinary skill in the art would have been motivated to expand the system of Sayan in order to determine an estimated safety stock value with respect to the product at the retail facility (Abstract).
Although Sayan discloses updating a database to indicate products associated with a scan event are adherent to guidelines, Sayan in view of Fernandes does not explicitly teach products associated with a scan event that are available for sale.
Although Sayan discloses receiving scan events and determining whether to update a database, Sayan in view of Fernandes does not explicitly teach when a scan is after a time range and the current location does not correspond to the first location, determining that the product is available for sale and product availability.
However, Schoening et al., hereinafter, Schoening teaches listing products as being available for sale and determining that a current location does not correspond to the correct location (Fig. 10; ¶¶0106-0113[In some examples of the system, the tracking application 36 may periodically update the information displayed on the display screen 50B by querying the product and order database 27 and sending the results of that query to the user interface device 23, which is then displayed on the display screen 50B... While dropping off the product 13 at such a location, it is possible that the RFID reader 20 and the antennas 21A-C read the location designation RFID tag 30 of an adjacent shelf 12 or bay 14 and send incorrect location information to the asset tracking and management device 26 and stored on the product and order database 27. If such an error occurs, the forklift operator may alert a shipping clerk to the mistake or the forklift operator may manually correct the incorrect information stored in the product database 27 directly from the user interface device 23] in view of ¶0006).
The system of Schoening is applicable to the system of Sayan in view of Fernandes as they share characteristics and capabilities, namely, they are all targeted to product inventory management. 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 and databases as taught by Sayan in view of Fernandes to include item availability and location determination as taught by Schoening. One of ordinary skill in the art would have been motivated to expand the system of Sayan in view of Fernandes in order to manage the tracking of and shipping of products in a storage or warehouse environment (¶0002).
Regarding Claim 4, Sayan in view of Fernandes in view of Schoening teaches the computer-implemented system of claim 1, Sayan further discloses wherein the historic data further includes and is organized based on at least one of an order volume, a product type, a shipping method, traffic data, transit time, lead time, buffer time, location data, or a day of the week (¶0066[When the product tag is scanned (e.g., by a mobile device), the time of scan can be sent along with the indicia information (e.g., code, product identifier), and/or the location of the device to the server 301. The server 301 can then calculate a time difference between the time of scan and the destination time. The time difference calculation may be limited to only being performed when the destination location matches or is similar to (e.g., a pre-defined distance away from) the scanned location. If the time difference is within a pre-defined threshold period (e.g., a number of seconds, minutes, hours, days, etc.), the product has been routed in adherence to the guidelines. A different freshness period and/or threshold period may be stored by the server 301 for each product or code]; Examiner notes that freshness period for each product is comparable to historic data being based on a product type).
Regarding Claim 5, Sayan in view of Fernandes in view of Schoening teaches the computer-implemented system of claim 1, Sayan further discloses wherein the first location comprises a transfer facility (¶0066[When a product with the product tag is routed (e.g., shipped) from one party to another (e.g., from a manufacturer to a wholesaler), it is expected that the routing will occur within a certain pre-determined period of time (e.g., within a number of days, weeks, etc.)]; Examiner notes that manufacturer and wholesaler are comparable to transfer facilities).
Regarding Claim 6, Sayan in view of Fernandes in view of Schoening teaches the computer-implemented system of claim 1, Sayan further discloses wherein the second time is associated with a second scan event corresponding to a second location (¶0058[The accounts management service 410 of the back-end application 404 can manage/store accounts for users (e.g., manufacturers, vendors) to remotely enter the product information and their locations.] in view of ¶0066).
Regarding Claim 10, Sayan in view of Fernandes in view of Schoening teaches the computer-implemented system of claim 1, Sayan further discloses wherein the product availability comprises a stock amount of each product of the plurality of products (¶0089[The wholesaler device can scan the invoice barcode to initialize a bill of lading with the quantities and identities of products that were ordered, and then the quantities received can be automatically updated as each unit of goods is scanned by the device. The wholesaler application can enable a user to send the resulting bill of lading back to the originating manufacturer.]; Examiner notes that quantities are comparable to a stock amount), and
wherein the graphical user interface comprises a webpage (Fig. 2; ¶0026[FIG. 2 illustrates a commerce system according to an exemplary embodiment of the invention. The devices of FIG. 1 are divided into supplier devices 110 and consumer devices 120 and the cloud 100 includes a supplier cloud 101 that interfaces with the supplier devices 110 and a consumer cloud 102 that interfaces with the consumer devices. The supplier devices 110 or the consumer devices 110 include software and hardware to scan product tags 140] in view of ¶0062[Each micro-site can correspond to a manufacturer, a wholesaler, or vendor/supplier. The account management service 410 can maintain accounts that enable a user to remotely log-on to the computer server 301 to make changes to their corresponding micro-site. The micro-site can provide product information on a product associated with the scanned product identifier, information of the manufacturer that makes the product, or information about a vendor that supplies the product.]; Examiner notes that a micro-site is comparable to a webpage).
Regarding Claim 11, Sayan discloses a computer-implemented method for optimizing availability of products for display on a graphical user interface, the method comprising (Fig. 2; Abstract):
receiving a plurality of scan events associated with a plurality of products, wherein each scan event of the plurality of scan events comprises a timestamp and a current location (Fig. 3; ¶¶0066-0067[When the product tag is scanned (e.g., by a mobile device), the time of scan can be sent along with the indicia information (e.g., code, product identifier), and/or the location of the device to the server 301.] in view of ¶0029 which discloses a processor; Examiner notes that the location of the device is comparable to the current location associated with the scan event and product);
determining a plurality of ranges of time associated with the plurality of products based at least on historic data stored in a database, wherein each range of time of the plurality of ranges of time is associated with a destination fulfillment center (¶0066[When the product tag is scanned (e.g., by a mobile device), the time of scan can be sent along with the indicia information (e.g., code, product identifier), and/or the location of the device to the server 301. The server 301 can then calculate a time difference between the time of scan and the destination time. The time difference calculation may be limited to only being performed when the destination location matches or is similar to (e.g., a pre-defined distance away from) the scanned location. If the time difference is within a pre-defined threshold period (e.g., a number of seconds, minutes, hours, days, etc.), the product has been routed in adherence to the guidelines. A different freshness period and/or threshold period may be stored by the server 301 for each product or code] in view of ¶0081[The product tracking services 405 records data of the messages it receives from the manufacturer. For example, the services 405 can store a record for each unit of goods shipped by the manufacturer in a database on the memory 304. Each record may include product identifying information (e.g., the product identifier, the tracking code, etc.) and origin information (e.g., location of the manufacturer, the manufacturer identifier, time/date of manufacture, time/date of shipment, origin of raw materials used in product, etc.)]; Examiner notes that the time difference calculation is comparable to a range of time and that origin information is comparable to historic data stored);
for each scan event of the plurality of scan events: determining whether the scan event is received within a first range of time of the plurality of ranges of time (¶0066[When the product tag is scanned (e.g., by a mobile device), the time of scan can be sent along with the indicia information (e.g., code, product identifier), and/or the location of the device to the server 301. The server 301 can then calculate a time difference between the time of scan and the destination time. The time difference calculation may be limited to only being performed when the destination location matches or is similar to (e.g., a pre-defined distance away from) the scanned location. If the time difference is within a pre-defined threshold period (e.g., a number of seconds, minutes, hours, days, etc.), the product has been routed in adherence to the guidelines. A different freshness period and/or threshold period may be stored by the server 301 for each product or code.]);
determining whether the current location of the scan event corresponds to a first location, wherein the first location is not the destination fulfillment center (¶0066[The server 301 can then calculate a time difference between the time of scan and the destination time. The time difference calculation may be limited to only being performed when the destination location matches or is similar to (e.g., a pre-defined distance away from) the scanned location.]; Examiner notes that determining whether destination matches or is similar to the scanned location is comparable to determining whether the current location of the scan corresponds to a destination fulfillment center);
when the scan event is received within the first range of time and the current location corresponds to the first location, updating the database to indicate that a first subset of products of the plurality of products associated with the scan event is adherent to guidelines at a first time (¶0066[The server 301 may store a freshness period for each product or for each unique code. The above-described destination time/date can be calculated based on the shipping time/date and the freshness period. For example, the destination time/date can be calculated by adding the freshness period to the shipping time/date. When the product tag is scanned (e.g., by a mobile device), the time of scan can be sent along with the indicia information (e.g., code, product identifier), and/or the location of the device to the server 301. The server 301 can then calculate a time difference between the time of scan and the destination time. The time difference calculation may be limited to only being performed when the destination location matches or is similar to (e.g., a pre-defined distance away from) the scanned location. If the time difference is within a pre-defined threshold period (e.g., a number of seconds, minutes, hours, days, etc.), the product has been routed in adherence to the guidelines. A different freshness period and/or threshold period may be stored by the server 301 for each product or code.] in view of ¶0082[The computer server 301 can also maintain an inventory for the manufacturer. For example, the inventory services 413 of the back-end application 404 can be used to maintain the inventory. The inventory services 413 can update the inventory based on the received manufacturer messages and knowledge of the current inventory (e.g., from access to an inventory server of the manufacturer).]); and
when the scan event is received after the first range of time, determining, at a second time after the first time, whether to update the database to indicate that the first subset of products is (¶¶0066-0067[For example, the destination time/date can be calculated by adding the freshness period to the shipping time/date. When the product tag is scanned (e.g., by a mobile device), the time of scan can be sent along with the indicia information (e.g., code, product identifier), and/or the location of the device to the server 301. The server 301 can then calculate a time difference between the time of scan and the destination time. The time difference calculation may be limited to only being performed when the destination location matches or is similar to (e.g., a pre-defined distance away from) the scanned location. If the time difference is within a pre-defined threshold period (e.g., a number of seconds, minutes, hours, days, etc.), the product has been routed in adherence to the guidelines]);
generating, at the first time, a graphical user interface, the graphical user interface comprising a product for each product of the plurality of products (Fig. 2; ¶0026[FIG. 2 illustrates a commerce system according to an exemplary embodiment of the invention. The devices of FIG. 1 are divided into supplier devices 110 and consumer devices 120 and the cloud 100 includes a supplier cloud 101 that interfaces with the supplier devices 110 and a consumer cloud 102 that interfaces with the consumer devices. The supplier devices 110 or the consumer devices 110 include software and hardware to scan product tags 140]); and
transmitting the graphical user interface to at least one customer device (Fig. 2[showing the transmission of the GUI to a customer device via arrows]; ¶0026[FIG. 2 illustrates a commerce system according to an exemplary embodiment of the invention. The devices of FIG. 1 are divided into supplier devices 110 and consumer devices 120 and the cloud 100 includes a supplier cloud 101 that interfaces with the supplier devices 110 and a consumer cloud 102 that interfaces with the consumer devices. The supplier devices 110 or the consumer devices 110 include software and hardware to scan product tags 140]).
Although Sayan discloses determining a plurality of ranges of time based on historic data, Sayan does not explicitly disclose determining a time by predicting, using one or more trained machine learning models, one or more lead times associated with products, and wherein the historic data includes at least one or more past lead times for delivering products to and stowing products at at least one destination fulfillment center.
However, Fernandes teaches predicting lead times using a machine learning model and a database storing historic lead times for products at a destination center (¶0076[the machine learning approach is used (step 555), the lead time variability generator 324 outputs data including: predicted lead time, product number, store number, and error based on products arriving early/on time or late, RMSE & MAPE using train and test split based on historical data evidence. Based on the above two models now, using a voting technique on the errors, the lead time variability generator 324 chooses the best model (step 560), and generates the predicted lead time for the product number at the level of the retail facility 110 (step 565).] in view of ¶¶0021-0022[ the electronic database 140 stores electronic data that comprises historical lead time data associated with products stocked at the retail facility 110, historical demand forecast data associated with the products stocked at the retail facility 110, historical sales data associated with the products stocked at the retail facility 110, and order-related data associated with the product stocked at the retail facility 110.]; according to ¶0088 of the instant specification, “A lead time may be associated with the duration of time a product must be stowed… within, or the duration of time it takes a product to be stowed”).
The method of Fernandes is applicable to the method of Sayan as they share characteristics and capabilities, namely, they are both targeted to product inventory management. 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 products stored in a database and ranges of time as disclosed by Sayan to include predicting lead times using machine learning and historic data of past lead times as taught by Fernandes. One of ordinary skill in the art would have been motivated to expand the method of Sayan in order to determine an estimated safety stock value with respect to the product at the retail facility (Abstract).
Although Sayan discloses updating a database to indicate products associated with a scan event are adherent to guidelines, Sayan in view of Fernandes does not explicitly teach products associated with a scan event that are available for sale.
Although Sayan discloses receiving scan events and determining whether to update a database, Sayan in view of Fernandes does not explicitly teach when a scan is after a time range and the current location does not correspond to the first location, determining that the product is available for sale and product availability.
However, Schoening teaches listing products as being available for sale and determining that a current location does not correspond to the correct location (in view of Fig. 10; ¶¶0106-0113[In some examples of the system, the tracking application 36 may periodically update the information displayed on the display screen 50B by querying the product and order database 27 and sending the results of that query to the user interface device 23, which is then displayed on the display screen 50B... While dropping off the product 13 at such a location, it is possible that the RFID reader 20 and the antennas 21A-C read the location designation RFID tag 30 of an adjacent shelf 12 or bay 14 and send incorrect location information to the asset tracking and management device 26 and stored on the product and order database 27. If such an error occurs, the forklift operator may alert a shipping clerk to the mistake or the forklift operator may manually correct the incorrect information stored in the product database 27 directly from the user interface device 23] in view of ¶0006).
The method of Schoening is applicable to the method of Sayan in view of Fernandes as they share characteristics and capabilities, namely, they are all targeted to product inventory management. 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 and databases as taught by Sayan in view of Fernandes to include item availability and location determination as taught by Schoening. One of ordinary skill in the art would have been motivated to expand the method of Sayan in view of Fernandes in order to manage the tracking of and shipping of products in a storage or warehouse environment (¶0002).
Regarding Claim 14, Sayan in view of Fernandes in view of Schoening teaches the computer-implemented method of claim 11, Sayan further discloses wherein the historic data further includes and is organized based on at least one of an order volume, a product type, a shipping method, traffic data, transit time, lead time, buffer time, location data, or a day of the week (¶0066[When the product tag is scanned (e.g., by a mobile device), the time of scan can be sent along with the indicia information (e.g., code, product identifier), and/or the location of the device to the server 301. The server 301 can then calculate a time difference between the time of scan and the destination time. The time difference calculation may be limited to only being performed when the destination location matches or is similar to (e.g., a pre-defined distance away from) the scanned location. If the time difference is within a pre-defined threshold period (e.g., a number of seconds, minutes, hours, days, etc.), the product has been routed in adherence to the guidelines. A different freshness period and/or threshold period may be stored by the server 301 for each product or code]; Examiner notes that freshness period for each product is comparable to historic data being based on a product type).
Regarding Claim 15, Sayan in view of Fernandes in view of Schoening teaches the computer-implemented method of claim 11, Sayan further discloses wherein the first location comprises a transfer facility (¶0066[When a product with the product tag is routed (e.g., shipped) from one party to another (e.g., from a manufacturer to a wholesaler), it is expected that the routing will occur within a certain pre-determined period of time (e.g., within a number of days, weeks, etc.)]; Examiner notes that manufacturer and wholesaler are comparable to transfer facilities).
Regarding Claim 19, Sayan in view of Fernandes in view of Schoening teaches the computer-implemented method of claim 11, Sayan further discloses wherein the product availability comprises a stock amount of each product of the plurality of products (¶0089[The wholesaler device can scan the invoice barcode to initialize a bill of lading with the quantities and identities of products that were ordered, and then the quantities received can be automatically updated as each unit of goods is scanned by the device. The wholesaler application can enable a user to send the resulting bill of lading back to the originating manufacturer.]; Examiner notes that quantities are comparable to a stock amount), and
wherein the graphical user interface comprises a webpage (Fig. 2; ¶0026[FIG. 2 illustrates a commerce system according to an exemplary embodiment of the invention. The devices of FIG. 1 are divided into supplier devices 110 and consumer devices 120 and the cloud 100 includes a supplier cloud 101 that interfaces with the supplier devices 110 and a consumer cloud 102 that interfaces with the consumer devices. The supplier devices 110 or the consumer devices 110 include software and hardware to scan product tags 140] in view of ¶0062[Each micro-site can correspond to a manufacturer, a wholesaler, or vendor/supplier. The account management service 410 can maintain accounts that enable a user to remotely log-on to the computer server 301 to make changes to their corresponding micro-site. The micro-site can provide product information on a product associated with the scanned product identifier, information of the manufacturer that makes the product, or information about a vendor that supplies the product.]; Examiner notes that a micro-site is comparable to a webpage).
Regarding Claim 20, Sayan discloses a computer-implemented system for optimizing availability of products for display on a graphical user interface, the system comprising (Fig. 2; Abstract):
a memory storing instructions (Fig. 3; ¶0029); and
at least one processor configured to execute the instructions to perform steps comprising: receiving a plurality of scan events associated with a plurality of products, wherein each scan event of the plurality of scan events comprises a timestamp and a current location (Fig. 3; ¶¶0066-0067[When the product tag is scanned (e.g., by a mobile device), the time of scan can be sent along with the indicia information (e.g., code, product identifier), and/or the location of the device to the server 301.] in view of ¶0029 which discloses a processor; Examiner notes that the location of the device is comparable to the current location associated with the scan event and product);
determining a plurality of ranges of time based at least on historic data stored in a database, wherein determining the plurality of ranges of time includes associated with the plurality of products based at least on historic data stored in a database (¶0066[When the product tag is scanned (e.g., by a mobile device), the time of scan can be sent along with the indicia information (e.g., code, product identifier), and/or the location of the device to the server 301. The server 301 can then calculate a time difference between the time of scan and the destination time. The time difference calculation may be limited to only being performed when the destination location matches or is similar to (e.g., a pre-defined distance away from) the scanned location. If the time difference is within a pre-defined threshold period (e.g., a number of seconds, minutes, hours, days, etc.), the product has been routed in adherence to the guidelines. A different freshness period and/or threshold period may be stored by the server 301 for each product or code] in view of ¶0081[The product tracking services 405 records data of the messages it receives from the manufacturer. For example, the services 405 can store a record for each unit of goods shipped by the manufacturer in a database on the memory 304. Each record may include product identifying information (e.g., the product identifier, the tracking code, etc.) and origin information (e.g., location of the manufacturer, the manufacturer identifier, time/date of manufacture, time/date of shipment, origin of raw materials used in product, etc.)]; Examiner notes that the time difference calculation is comparable to a range of time and that origin information is comparable to historic data stored);
for each scan event of the plurality of scan events: determining whether the scan event is received within a first range of time of the plurality of ranges of time (¶0066[When the product tag is scanned (e.g., by a mobile device), the time of scan can be sent along with the indicia information (e.g., code, product identifier), and/or the location of the device to the server 301. The server 301 can then calculate a time difference between the time of scan and the destination time. The time difference calculation may be limited to only being performed when the destination location matches or is similar to (e.g., a pre-defined distance away from) the scanned location. If the time difference is within a pre-defined threshold period (e.g., a number of seconds, minutes, hours, days, etc.), the product has been routed in adherence to the guidelines. A different freshness period and/or threshold period may be stored by the server 301 for each product or code.]);
determining whether the current location of the scan event corresponds to a first location (¶0066[The server 301 can then calculate a time difference between the time of scan and the destination time. The time difference calculation may be limited to only being performed when the destination location matches or is similar to (e.g., a pre-defined distance away from) the scanned location.]; Examiner notes that determining whether destination matches or is similar to the scanned location is comparable to determining whether the current location of the scan corresponds to a destination fulfillment center);
based on determining that the scan event is received within the first range of time and the current location corresponds to the first location, updating the database to indicate that a first subset of products of the plurality of products associated with the scan event is adherent to guidelines at a first time (¶0066[The server 301 may store a freshness period for each product or for each unique code. The above-described destination time/date can be calculated based on the shipping time/date and the freshness period. For example, the destination time/date can be calculated by adding the freshness period to the shipping time/date. When the product tag is scanned (e.g., by a mobile device), the time of scan can be sent along with the indicia information (e.g., code, product identifier), and/or the location of the device to the server 301. The server 301 can then calculate a time difference between the time of scan and the destination time. The time difference calculation may be limited to only being performed when the destination location matches or is similar to (e.g., a pre-defined distance away from) the scanned location. If the time difference is within a pre-defined threshold period (e.g., a number of seconds, minutes, hours, days, etc.), the product has been routed in adherence to the guidelines. A different freshness period and/or threshold period may be stored by the server 301 for each product or code.] in view of ¶0082[The computer server 301 can also maintain an inventory for the manufacturer. For example, the inventory services 413 of the back-end application 404 can be used to maintain the inventory. The inventory services 413 can update the inventory based on the received manufacturer messages and knowledge of the current inventory (e.g., from access to an inventory server of the manufacturer).]); and
based on determining that the scan event is received after the first range of time, determining, at a second time after the first time, whether to update the database to indicate that the first subset of products is adherent to guidelines (¶¶0066-0067[For example, the destination time/date can be calculated by adding the freshness period to the shipping time/date. When the product tag is scanned (e.g., by a mobile device), the time of scan can be sent along with the indicia information (e.g., code, product identifier), and/or the location of the device to the server 301. The server 301 can then calculate a time difference between the time of scan and the destination time. The time difference calculation may be limited to only being performed when the destination location matches or is similar to (e.g., a pre-defined distance away from) the scanned location. If the time difference is within a pre-defined threshold period (e.g., a number of seconds, minutes, hours, days, etc.), the product has been routed in adherence to the guidelines]);
generating a graphical user interface, the graphical user interface comprising a product for each product of the plurality of products (Fig. 2; ¶0026[FIG. 2 illustrates a commerce system according to an exemplary embodiment of the invention. The devices of FIG. 1 are divided into supplier devices 110 and consumer devices 120 and the cloud 100 includes a supplier cloud 101 that interfaces with the supplier devices 110 and a consumer cloud 102 that interfaces with the consumer devices. The supplier devices 110 or the consumer devices 110 include software and hardware to scan product tags 140]); and
transmitting the graphical user interface to at least one customer device (Fig. 2[showing the transmission of the GUI to a customer device via arrows]; ¶0026[FIG. 2 illustrates a commerce system according to an exemplary embodiment of the invention. The devices of FIG. 1 are divided into supplier devices 110 and consumer devices 120 and the cloud 100 includes a supplier cloud 101 that interfaces with the supplier devices 110 and a consumer cloud 102 that interfaces with the consumer devices. The supplier devices 110 or the consumer devices 110 include software and hardware to scan product tags 140]).
Although Sayan discloses determining a plurality of ranges of time based on historic data, Sayan does not explicitly disclose determining a time predicting, using one or more trained machine learning models, one or more lead times associated with products, and wherein the historic data includes at least one or more past lead times for delivering products to and stowing products at at least one destination fulfillment center.
However, Fernandes teaches predicting lead times using a machine learning model and a database storing historic lead times for products at a destination center (¶0076[the machine learning approach is used (step 555), the lead time variability generator 324 outputs data including: predicted lead time, product number, store number, and error based on products arriving early/on time or late, RMSE & MAPE using train and test split based on historical data evidence. Based on the above two models now, using a voting technique on the errors, the lead time variability generator 324 chooses the best model (step 560), and generates the predicted lead time for the product number at the level of the retail facility 110 (step 565).] in view of ¶¶0021-0022[ the electronic database 140 stores electronic data that comprises historical lead time data associated with products stocked at the retail facility 110, historical demand forecast data associated with the products stocked at the retail facility 110, historical sales data associated with the products stocked at the retail facility 110, and order-related data associated with the product stocked at the retail facility 110.]; according to ¶0088 of the instant specification, “A lead time may be associated with the duration of time a product must be stowed… within, or the duration of time it takes a product to be stowed”).
The system of Fernandes is applicable to the system of Sayan as they share characteristics and capabilities, namely, they are both targeted to product inventory management. 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 products stored in a database and ranges of time as disclosed by Sayan to include predicting lead times using machine learning and historic data of past lead times as taught by Fernandes. One of ordinary skill in the art would have been motivated to expand the system of Sayan in order to determine an estimated safety stock value with respect to the product at the retail facility (Abstract).
Although Sayan discloses updating a database to indicate products associated with a scan event are adherent to guidelines, Sayan in view of Fernandes does not explicitly teach products associated with a scan event that are available for sale.
Although Sayan discloses receiving scan events and determining whether to update a database, Sayan in view of Fernandes does not explicitly teach when a scan is after a time range and the current location does not correspond to the first location, determining that the product is available for sale and product availability.
However, Schoening teaches listing products as being available for sale and determining that a current location does not correspond to the correct location (in view of Fig. 10; ¶¶0106-0113[In some examples of the system, the tracking application 36 may periodically update the information displayed on the display screen 50B by querying the product and order database 27 and sending the results of that query to the user interface device 23, which is then displayed on the display screen 50B... While dropping off the product 13 at such a location, it is possible that the RFID reader 20 and the antennas 21A-C read the location designation RFID tag 30 of an adjacent shelf 12 or bay 14 and send incorrect location information to the asset tracking and management device 26 and stored on the product and order database 27. If such an error occurs, the forklift operator may alert a shipping clerk to the mistake or the forklift operator may manually correct the incorrect information stored in the product database 27 directly from the user interface device 23] in view of ¶0006).
The system of Schoening is applicable to the system of Sayan in view of Fernandes as they share characteristics and capabilities, namely, they are all targeted to product inventory management. 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 and databases as taught by Sayan in view of Fernandes to include item availability and location determination as taught by Schoening. One of ordinary skill in the art would have been motivated to expand the system of Sayan in view of Fernandes in order to manage the tracking of and shipping of products in a storage or warehouse environment (¶0002).
Claim(s) 7 and 16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Sayan in view of Fernandes in view of Schoening in further view of Zhao et al. (US 2021/0089975 A1 [previously cited]).
Regarding Claim 7, Sayan in view of Fernandes in view of Schoening teaches the computer-implemented system of claim 6, Sayan further discloses wherein the second location comprises a destination fulfillment center (¶0058[The accounts management service 410 of the back-end application 404 can manage/store accounts for users (e.g., manufacturers, vendors) to remotely enter the product information and their locations.] in view of ¶0066; Examiner notes that manufacturers are comparable to a destination fulfillment center).
Although Sayan discloses a second location comprising a destination fulfillment center, Sayan in view of Fernandes in view of Schoening does not explicitly teach an inbound zone of a destination.
However, Zhao et al., hereinafter, Zhao teaches an inbound zone of a fulfillment center (Fig. 2; ¶0084[In Step 520, the warehouse management system 119 verifies if a package purchase order was confirmed. Confirmation of the order includes receipt of a notification from a third-party system. In some embodiments, the confirmation may depend on the receipt of the first set of packages. The ordered packages may be received by a fulfillment center 200 similar to products received in inbound zone 203 and described in FIG. 2 above]).
The system of Zhao is applicable to the system of Sayan in view of Fernandes in view of Schoening as they share characteristics and capabilities, namely, they are all targeted to product inventory management. 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 and databases as taught by Sayan in view of Fernandes in view of Schoening to include an inbound zone of a fulfillment center as taught by Zhao. One of ordinary skill in the art would have been motivated to expand the system of Sayan in view of Fernandes in view of Schoening in order to ship an expected number of orders handled by a first fulfillment center (¶0005).
Regarding Claim 16, Sayan in view of Fernandes in view of Schoening teaches the computer-implemented method of claim 11, Sayan further discloses wherein the second time is associated with a second scan event corresponding to a second location (¶0058[The accounts management service 410 of the back-end application 404 can manage/store accounts for users (e.g., manufacturers, vendors) to remotely enter the product information and their locations.] in view of ¶0066), and
wherein the second location comprises a destination fulfillment center (¶0058[The accounts management service 410 of the back-end application 404 can manage/store accounts for users (e.g., manufacturers, vendors) to remotely enter the product information and their locations.] in view of ¶0066; Examiner notes that manufacturers are comparable to a destination fulfillment center).
Although Sayan discloses a second location comprising a destination fulfillment center, Sayan in view of Fernandes in view of Schoening does not explicitly teach an inbound zone of a destination.
However, Zhao teaches an inbound zone of a fulfillment center (Fig. 2; ¶0084[In Step 520, the warehouse management system 119 verifies if a package purchase order was confirmed. Confirmation of the order includes receipt of a notification from a third-party system. In some embodiments, the confirmation may depend on the receipt of the first set of packages. The ordered packages may be received by a fulfillment center 200 similar to products received in inbound zone 203 and described in FIG. 2 above]).
The method of Zhao is applicable to the method of Sayan in view of Fernandes in view of Schoening as they share characteristics and capabilities, namely, they are all targeted to product inventory management. 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 and databases as taught by Sayan in view of Fernandes in view of Schoening to include an inbound zone of a fulfillment center as taught by Zhao. One of ordinary skill in the art would have been motivated to expand the method of Sayan in view of Fernandes in view of Schoening in order to ship an expected number of orders handled by a first fulfillment center (¶0005).
Claim(s) 8 and 17 is/are rejected under 35 U.S.C. 103 as being unpatentable over Sayan in view of Fernandes in view of Schoening in further view of Gabbai et al. (US 2018/0025310 A1 [previously cited]).
Regarding Claim 8, Sayan in view of Fernandes in view of Schoening teaches the computer-implemented system of claim 1, Sayan further discloses wherein updating the database comprises adding the product identifier to a first table of the database (¶0088[The server 301 can generate an inventory for the wholesaler based on the received wholesaler messages. For example, each time a unit of goods is scanned by the wholesale device, the server 301 can add that unit to the inventory of the corresponding wholesaler.] in view of ¶0082), and
wherein the first table of the database includes one or more product identifiers associated with products that are available for sale (¶0087[The wholesale message may additionally include at least one of a product identifier of the unit (e.g., UPC), a device identifier of the wholesaler device, a wholesale identifier identifying the wholesaler (e.g., name, address, a wholesaler code, etc.), a scheduled destination identifier (e.g., a code, address, location, of the site the unit is to be delivered), a scheduled delivery time/date, etc. The product tracking service 405 can update/append the record it maintains for the tracking code with the additional information that is present in the received message.]).
Although Sayan discloses a database including a table with identifiers for products, Sayan in view of Fernandes in view of Schoening 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 Sayan in view of Fernandes in view of Schoening 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 Sayan in view of Fernandes in view of Schoening 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 Sayan in view of Fernandes in view of Schoening so that inventory management efficiency may be improved by making the pick-pack-deliver process more dynamic (¶0018).
Regarding Claim 17, Sayan in view of Fernandes in view of Schoening teaches the computer-implemented method of claim 11, Sayan further discloses wherein updating the database comprises adding the product identifier to a first table of the database (¶0088[The server 301 can generate an inventory for the wholesaler based on the received wholesaler messages. For example, each time a unit of goods is scanned by the wholesale device, the server 301 can add that unit to the inventory of the corresponding wholesaler.] in view of ¶0082), and
wherein the first table of the database includes one or more product identifiers associated with products that are available for sale (¶0087[The wholesale message may additionally include at least one of a product identifier of the unit (e.g., UPC), a device identifier of the wholesaler device, a wholesale identifier identifying the wholesaler (e.g., name, address, a wholesaler code, etc.), a scheduled destination identifier (e.g., a code, address, location, of the site the unit is to be delivered), a scheduled delivery time/date, etc. The product tracking service 405 can update/append the record it maintains for the tracking code with the additional information that is present in the received message.]).
Although Sayan discloses a database including a table with identifiers for products, Sayan in view of Fernandes in view of Schoening 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 Sayan in view of Fernandes in view of Schoening 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 Sayan in view of Fernandes in view of Schoening 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 Sayan in view of Fernandes in view of Schoening so that inventory management efficiency may be improved by making the pick-pack-deliver process more dynamic (¶0018).
Claim(s) 9 and 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Sayan in view of Fernandes in view of Schoening in further view of Gabbai in view of Francis et al. (US 2024/0303594 A1 [previously cited]).
Regarding Claim 9, Sayan in view of Fernandes in view of Schoening in view of Gabbai teaches the computer-implemented system of claim 8, Sayan further discloses wherein the database includes a table including one or more identifiers associated with products (¶0087[[The wholesale message may additionally include at least one of a product identifier of the unit (e.g., UPC), a device identifier of the wholesaler device, a wholesale identifier identifying the wholesaler (e.g., name, address, a wholesaler code, etc.), a scheduled destination identifier (e.g., a code, address, location, of the site the unit is to be delivered), a scheduled delivery time/date, etc. The product tracking service 405 can update/append the record it maintains for the tracking code with the additional information that is present in the received message.]).
Although Sayan discloses a database including a table with identifiers for products, Sayan in view of Fernandes in view of Schoening in view of Gabbai 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 et al., hereinafter, 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 Sayan in view of Fernandes in view of Schoening in view of Gabbai 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 database as taught by Sayan in view of Fernandes in view of Schoening in view of Gabbai 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 Sayan in view of Fernandes in view of Schoening in view of Gabbai in order to efficiently pick items from customer orders (¶0090).
Regarding Claim 18, Sayan in view of Fernandes in view of Schoening in view of Gabbai teaches the computer-implemented method of claim 17, Sayan further discloses wherein the database includes a table including one or more identifiers associated with products (¶0087[[The wholesale message may additionally include at least one of a product identifier of the unit (e.g., UPC), a device identifier of the wholesaler device, a wholesale identifier identifying the wholesaler (e.g., name, address, a wholesaler code, etc.), a scheduled destination identifier (e.g., a code, address, location, of the site the unit is to be delivered), a scheduled delivery time/date, etc. The product tracking service 405 can update/append the record it maintains for the tracking code with the additional information that is present in the received message.]).
Although Sayan discloses a database including a table with identifiers for products, Sayan in view of Fernandes in view of Schoening in view of Gabbai 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 Sayan in view of Fernandes in view of Schoening in view of Gabbai 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 database as taught by Sayan in view of Fernandes in view of Schoening in view of Gabbai 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 Sayan in view of Fernandes in view of Schoening in view of Gabbai in order to efficiently pick items from customer orders (¶0090).
Response to Arguments
Applicant’s arguments on pages 10 of the remarks filed 12/10/2025, with respect to the previous Claim Objects have been fully considered and are persuasive in view of the currently amended claims.
Accordingly, the previous Claim Objections are withdrawn.
Applicant’s arguments on pages 10-19 of the remarks filed 12/10/2025, with respect to the previous 35
USC § 101 rejections have been fully considered but are not persuasive.
Applicant argues on pages 11-14 of the remarks that the amended claims do not recite an abstract idea. Examiner respectfully disagrees. 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. As noted above and in the previous office action, the claims recite improving product sales and availability. This is an abstract idea because it is a concept of business relations which makes it a method of organizing human activity (i.e., one of the groupings of abstract ideas enumerated in MPEP 2106.04(a)(2)).
Applicant cites Enfish, L.L.C. v. Microsoft Corp. for support. 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, applicant argues on pages 13-14 of the remarks that the amended claims recite technical systems and methods for optimizing display of items and are not Certain Methods of Organizing Human Activity. Examiner respectfully disagrees. As noted previously, the claims recite improving product availability which is an abstract idea because it is a concept of business relations which makes it a method of organizing human activity (i.e., one of the groupings of abstract ideas enumerated in MPEP 2106.04(a)(2)).
Applicant further argues on pages 14-16 of the remarks that the amended claims integrate the abstract idea into a practical application and provide a technical improvement. Examiner respectfully disagrees. Optimizing availability of products for display comprising: receiving a plurality of scan events associated with a plurality of products, wherein each scan event of the plurality of scan events comprises a timestamp and a current location; determining a plurality of ranges of time by predicting, one or more lead times associated with the plurality of products based at least on historic data, wherein each range of time of the plurality of ranges of time is associated with a destination fulfillment center, and wherein the historic data includes at least one or more past lead times for delivering products to and stowing products at at least one destination fulfillment center; for each scan event of the plurality of scan events:
determining whether the scan event is received within a first range of time of the plurality of ranges of time; determining whether the current location of the scan event corresponds to a first location, wherein the first location is not the destination fulfillment center; when the scan event is received within the first range of time and the current location corresponds to the first location, updating to indicate that a first subset of products of the plurality of products associated with the scan event is available for sale at a first time; and when the scan event is received after the first range of time and the current location does not correspond to the first location, determining, at a second time after the first time, whether to update to indicate that the first subset of products is available for sale; generating, at the first time, a graphical user interface, comprising a product availability for each product of the 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 components which are recited at a high-level does not integrate the abstract idea into a practical application or provide a technical improvement. The additional elements of a computer, a graphical user interface, processor, trained machine learning models, databases, and memory are described as generic in Fig. 5, ¶0078, ¶0098 and ¶¶0146-0147 of the instant specification.
Applicant cites ¶¶0004-0005 of the instant specification for support, however, accounting for unstowed items in an inventory and optimizing the availability of products in marking, indicating or otherwise considering not yet stowed products as available and providing locations for expedited stowing is all part of the abstract idea. The mere execution of the abstract idea on components such as a webpage and graphical user interface which are recited at a high-level and as generic does not overcome the rejection.
Applicant further argues on pages 16-17 that the claims amount to “significantly more” than the abstract idea. Examiner respectfully disagrees. Determining a plurality of ranges of time by predicting, one or more lead times associated with the plurality of products based at least on historic data stored, wherein each range of time of the plurality of ranges of time is associated with a destination fulfillment center, and wherein the historic data includes at least one or more past lead times for delivering products to and stowing products at at least one destination fulfillment center; for each scan event of the plurality of scan events ... when the scan event is received within the first range of time and the current location corresponds to the first location, updating to indicate that a first subset of products of the plurality of products associated with the scan event is available for sale at a first time; generating, at the first time, a graphical user interface, comprising a product availability for each product of the plurality of products are all part of the abstract idea and the additional elements of a trained machine learning model, a database, and a graphical user interface 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.
Applicant cites Berkheimer v. HP, Inc. and argues well-understood, routine or conventional. Applicant argues that the amended claims are not well-understood, routine or conventional. Examiner respectfully disagrees. Furthermore, 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 offers
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 19-21 of the remarks filed 12/10/2025, with respect to the previous 35 USC § 103 rejections have been fully considered but are mostly moot in view of the new 103 rejection of the amended claims.
Applicant argues on page 20 of the remarks that Sayan does not disclose “wherein determining the plurality of ranges of time includes predicting one or more lead times associated with the plurality of products” in claim 2. Examiner respectfully disagrees. The instant specification states that a “lead time may be associated with the duration of time a product must be stowed… within, or the duration of time it takes a product to be stowed.” Sayan discloses a destination time and date that can be calculated based on shipping date and freshness period of a product (see ¶0066) which is comparable to the applicant’s description of the limitation, “wherein determining the plurality of ranges of time includes predicting one or more lead times associated with the plurality of products.” Sayan discloses in ¶0066 that a destination time/date is calculated (or predicted) for a product by “adding the freshness period to the shipping time/date” similar to the description of a lead time as set forth by the instant specification. Therefore, Sayan discloses “wherein determining the plurality of ranges of time includes predicting one or more lead times associated with the plurality of products” in previously presented claim 2.
Accordingly, references Sayan, Schoening, Zhao, Gabbai, and Francis 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