DETAILED ACTION
This Final Office action is in response to Applicant’s Amendment on 10/23/2025. To be clear, the claims filed on 06/20/2025 were NOT ENTERED; and, the claims filed on 10/22/2025 are ENTERED and examined in this action. Accordingly, as filed on 10/22/2025, claims 1-10 and 17-26 are pending. The effective filing date of the claimed invention is 12/17/2019.
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 .
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 1-10 and 17-26 are rejected under 35 U.S.C. 101 because the claims are directed to abstract idea.
Step 1 – Claims 1-10 and 25 relate to process claims; claims 17-24 are system/machine claims; and, claim 261 is limited to non-transitory manufactures. Accordingly, claims 1-10 and 17-26 pass step 1.
Step 2A, Prong 1 – Claim 1 (and similarly claims 17 and 26) recites the abstract idea of
accessing, 2 image input associated with an item, the image input comprising at least one of a video or a photograph (see e.g. MPEP 2106.04(a)(2)(II)(B); MPEP 2106.04(a)(2)(III)(C)(2));
retrieving, (see e.g. MPEP 2106.04(a)(2)(II)(B) and 2106.04(a)(2)(III));
determining, (see MPEP 2106.04(a)(2)(III) performed in mind/pen and paper; MPEP 2106.04(a)(2)(II)(A-B)); and
displaying, (see e.g. MPEP 2106.04(a)(2)(II)(C), see IV case, communicating a notification to the user via a device).
When these abstract idea limitations are viewed alone, and in ordered combination, the examiner finds that claim 1 recites abstract idea.
Step 2A, Prong 2 – The examiner does not find that claim 1 (and similarly claims 17 and 26) to integrate the abstract idea with practical application. The claimed additional limitations are 1) one or more cameras associated with a plurality of first client devices within a geographic region; 2) one or more hardware processors of a second client device, second and first device are different; 3) a user interface of the second client device. In general, these additional limitations are recited at a high level of generality and act as tools to implement the underlying abstract idea. As for the camera(s) associated with a plurality of first devices that facilitates data access, first and second device different, the examiner refers to MPEP 2106.05(a)(I)(iv) Examples that the courts have indicated may not be sufficient to show an improvement in computer-functionality: iv. Recording, transmitting, and archiving digital images by use of conventional or generic technology in a nascent but well-known environment, without any assertion that the invention reflects an inventive solution to any problem presented by combining a camera and a cellular telephone, TLI Communications, 823 F.3d at 611-12, 118 USPQ2d at 1747. For the first and second device being different see apply it standard at MPEP 2106.05(f). As for the one or more processors of a second device, the examiner refers to MPEP 2106.05(b)(II) For example, as described in MPEP § 2106.05(f), additional elements that invoke computers or other machinery merely as a tool to perform an existing process will generally not amount to significantly more than a judicial exception. See, e.g., Versata Development Group v. SAP America, 793 F.3d 1306, 1335, 115 USPQ2d 1681, 1702 (Fed. Cir. 2015) (explaining that in order for a machine to add significantly more, it must “play a significant part in permitting the claimed method to be performed, rather than function solely as an obvious mechanism for permitting a solution to be achieved more quickly”). As for the user interface of the second device, see MPEP 2106.04(a)(2)(III)(C)(3) and MPEP 2106.05(a)(I)(x) Examples that the courts have indicated may not be sufficient to show an improvement in computer-functionality: vi. Instructions to display two sets of information on a computer display in a non-interfering manner, without any limitations specifying how to achieve the desired result, Interval Licensing LLC v. AOL, Inc., 896 F.3d 1335, 1344-45, 127 USPQ2d 1553, 1559-60 (Fed. Cir. 2018).
Accordingly, when these additional limitations are viewed alone and in ordered combination, the examiner finds that the claim is directed to abstract idea.
Step 2B - The examiner does not find that claim 1 (and similarly claims 17 and 26) to recite significantly more than the abstract idea. The above findings relating to the additional limitations from Step 2A, Prong 2 is equally applied to Step 2B. Another consideration when determining whether a claim recites significantly more than a judicial exception is whether the additional element(s) are well-understood, routine, conventional activities previously known to the industry. This consideration is only evaluated in Step 2B of the eligibility analysis. MPEP 2106.05(d)(II) indicates that “The courts have recognized the following computer functions as well‐understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity.” Then lists the following:
i. Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network); but see DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d 1245, 1258, 113 USPQ2d 1097, 1106 (Fed. Cir. 2014) (“Unlike the claims in Ultramercial, the claims at issue here specify how interactions with the Internet are manipulated to yield a desired result‐‐a result that overrides the routine and conventional sequence of events ordinarily triggered by the click of a hyperlink.” (emphasis added));
iv. Storing and retrieving information in memory, Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93;
Accordingly, the examiner finds that the retrieving and sending/transmitting over a network limitations are found to be WURC.
When these additional limitations are viewed alone and in ordered combination, the examiner finds that the claim is directed to abstract idea.
Dependent Claims – Claims 2 and 18 recites more abstract under MPEP 2106.04(a)(2)(III) and the receiving of data from a device, with no improvement, and in the “apply it” manner. Claims 3 and 19 recite more abstract idea under MPEP 2106.04(a)(2)(III) and MPEP 2106.04(a)(2)(II)(B). Claims 4 and 20 recite more abstract idea under MPEP 2106.04(a)(2)(I). Claims 5-7 and 21-23 recite more abstract idea relating to the data content of the message, under e.g. MPEP 2106.04(a)(2)(II)(A) and (B), determining and predicting data MPEP 2106.04(a)(2)(III). Claim 5 recites a dashboard that indicates data, and where different devices are associated with different users and the examiner refers to abstract idea of e.g. mental process without an improvement to the dashboard art, “apply it”. Claims 8 and 24 recite abstract idea under MPEP 2106.04(a)(2)(III), with “apply it” additional limitation. Claims 9 and 25 recites data associations, which is abstract idea under MPEP 2106.04(a)(2)(III). Claim 10 recites more abstract idea under e.g. MPEP 2106.04(a)(2)(I) and (III). Claims 1-10 and 17-26 are therefore found to be directed to abstract idea.
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
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Claims 1-3, 8-10, 17-20, and 24-26 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Pat. Pub. No. 2016/0132821 to Glasgow et al. (“Glasgow”) in view of U.S. Pat. Pub. No. 2015/0278912 to Melcher et al. (“Melcher”).
With regard to claims 1, 17, and 26, Glasgow discloses the claimed method comprising, performed by a second client device (see e.g. Fig. 1 (to the right) for the second client device see e.g. [0027] devices 150, The e-commerce machines 120 and 140, the inventory management machine 130, and the devices 150 may each be implemented in a computer system, in whole or in part, as described below with respect to FIG. 15.; for the first device see e.g. Fig. 1, inventory management machine 130, ecommerce machine 120, 140, etc.):
accessing (e.g. [0023] Data is provided to the database by one or more sensors . . . The identification of items in the inventory and the quantity owned may be input by a user or automatically determined through the use of the sensors; [0029] The inventory management machine 130 may provide data to other machines (e.g., the e-commerce machines 120 and 140 or the devices 150) via the network 170 or another network. The inventory management machine 130 may receive data from other machines (e.g., the e-commerce machines 120 and 140 or the devices 150) via the network 170 or another network.), from one or more camera associated with a plurality of first client devices within a geographic region, (see image sensor at e.g. [0030] and Fig. 4 as camera, associated with first device of refrigerator), respective image input associated with an item, the image input comprising at least one of a video or a photograph (see e.g. [0030] where the client device such as refrigerator has an associated camera that takes images of the consumable items in the refrigerator, and where the images are accessed in order to analyze the data; [0035] camera may take a picture), wherein the second client device is different from the plurality of first client devices (see Fig. 1, explained above);
retrieving, using one or more hardware processors of the second client device, purchase history data of previous purchases associated with the item (see e.g. Fig. 12 and [0085-86] FIG. 12 is a flowchart illustrating operations of the inventory management machine 130 using the database schema 1100 in performing a process 1200 of managing an inventory; [0094] For example, the sensor module 210 [of machine 130] may communicate with the sensor modules 320 of one or more devices 150; [0091] The item is identified by the identification module 250 using a database lookup (operation 1240). The database may be a user-specific database of items previously purchased by the user, or a global database of all known items. In some example embodiments, both databases are used. (emphasis added), where this information can be/is communicated back to the device 150);
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determining, using the one or more hardware processors of the second client device, a pattern corresponding to one or more of a level of consumption of the item based on an analysis of the respective image input using one or more image recognition techniques and based on an analysis of the purchase history data (see e.g. [0030] To illustrate, one roommate may consume one brand of soda (e.g., Brand X) while another roommate consumes a different brand of soda (e.g., Brand Y). An image sensor (e.g., a camera) in the refrigerator, coupled to a processor configured to analyze images and identify the number of cans of each type of soda, can determine when the quantity of Brand X or Brand Y soda falls below a predetermined threshold [(e.g. determining a pattern)]. Based on an association of the soda with the corresponding roommate, an order for the soda can be placed and the appropriate roommate billed. The examiner finds that Glasgow appears to refer to the determining being performed in the first device, not the second device as claimed. At [0034] Glasgow does disclose “Any one or more of the modules described herein may be implemented using hardware (e.g., a processor of a machine) or a combination of hardware and software. For example, any module described herein may configure a processor to perform the operations described herein for that module. Moreover, any two or more of these modules may be combined into a single module, and the functions described herein for a single module may be subdivided among multiple modules. Furthermore, according to various example embodiments, modules described herein as being implemented within a single machine, database, or device may be distributed across multiple machines, databases, or devices.” Based on this disclosure of Glasgow, it appears that rearranging the parts, such as by performing the determination on the second device as opposed to the first device, would be an obvious modification, as Glasgow explicitly states that this is fully possible given the description of Glasgow that the processing can be performed on any computing device, including separating the processing into separate parts and processing on one or more processors. See MPEP 2144.04(VI)(C) Rearrangement of parts obvious matter of design choice. Therefore, it would have been obvious to one of ordinary skill in the data management art before the effective filing date of the claimed invention to modify Glasgow to include such determining operation on any of the processors of the system including the devices that are connected to the first device, such as the second device processor and/or e-commerce machine 140, where this obvious design choice is advantageous as it allows the designer to engineer where the processing power is be allocated in the system, and Glasgow provides specific support where the processing actions can be performed any of the devices, or a combination of them); and
displaying, at a user interface of the second client device, the pattern (see e.g. Fig. 9 and [0067-69] where the pattern is shown as “Condition to place order for 12 Cans of soda has been met.” And this is on the second device as shown in e.g. Glasgow [0031 “For example, the device 150 may be a sensor, a desktop computer, a vehicle computer, a tablet computer, a navigational device, a portable media device, or a smart phone belonging to the user 160.”).
While Glasgow mentions at [0091] that “[t]he database may be a user-specific database of items previously purchased by the user, or a global database of all known items,” Glasgow does not explicitly disclose using purchase history data of previous purchases associated with the item to determine consumption pattern, and then displaying that pattern.
For “purchase history data of previous purchases associated with the item” – see Melcher e.g. [0058-61] [0124] “The order module 260 determines a quantity of milk to order based on the user characteristics (e.g., historical purchase data for milk during the current season of the year).” (emphasis added); [0125] In further example embodiments, the order module 260 determines the order parameters based on the user characteristics such as past orders for coffee included in a purchase history of the user; [0033] In various example embodiments, the attribute data is received or accessed from a broad gamut of attribute sources such as, for example, from mobile devices, smart devices, smart homes, social network services, user profiles, browsing histories, purchase histories, and so forth, Demand indications that are indicative of anticipatory demand by the user for a particular item are extracted from the attribute data. For example, purchase histories may indicate prior purchases for coffee products, location data (e.g., as determined by a Global Positioning System (GPS) component of a mobile device, beacon detections, or other location services) may indicate frequent trips to coffee shops, or social media data such as check-ins or user postings may indicate an affinity for coffee.
For “determining a pattern corresponding to level of consumption . . . based on purchase history” – see Melcher e.g. [0087], Fig. 4, 410-440. “For instance, the analysis module 255 calculates a usage rate corresponding to the commerce item based on the attribute data, the user characteristics, or other data and applies the usage rate to determine the inventory threshold for the commerce item to avoid depletion of a supply of the commerce item. For example, the analysis module 255 determines the usage rate for a particular item based on historical purchase history data and infers usage rate based on a frequency of purchase of the particular item. In a specific example, the commerce item may be coffee beans and the analysis module 255 determines that based on the user's current supply of coffee beans and the user's rate of consumption (e.g., the usage rate) corresponding to coffee beans, the user may run out in fourteen days. In this specific example, the analysis module 255 determines the inventory threshold to be a value, such as a quantity of the coffee beans, that may be the current inventory level several days prior to depletion of the supply of coffee beans.”
For plurality of first clients within a geographic region – see Melcher, abstract [0070], “attribute data associated with a user is received from a plurality of attribute sources”; [0130] In an example embodiment, the attribute data may include data corresponding to the user device sources 1920. The user device sources 1920 may include such non-limiting examples as a personal computer (PC), a tablet computer, a laptop computer, a netbook, a set-top box (STB), a personal digital assistant (PDA), an entertainment media system, a cellular telephone, a smart phone, a mobile device, a wearable device (e.g., a smart watch), a smart home device (e.g., a smart appliance), and other smart devices; [0122] Referring now to FIG. 16, a scene 1600 depicts a living room attached to an open kitchen. In the example of FIG. 16, the scene 1600 includes a media entertainment device 1610, a smart television (TV) 1620, a lamp 1630, a mobile computer 1640, a mobile device 1650, a user 1660, a smart refrigerator 1670, and a kitchen display 1680. Each of the devices 1610-1650, 1670, and 1680 may be attribute sources coupled to a network (e.g., the network 104) and operable to communicate with the data mesh system 150;
For displaying to a second client device (UI/notification) – see Melcher e.g. [0056] Referring to FIG. 2A, the presentation module 210 may provide various presentation and user interface functionality operable to interactively present and receive information from users. For example, the presentation module 210 may cause presentation of various notifications or user interfaces that provide the user an option to make a purchase associated with the identified items. In various implementations, the presentation module 210 presents or causes presentation of information (e.g., visually displaying information on a screen, acoustic output, haptic feedback); [0111] At operation 1110, the presentation module 210 generates the notification that includes an option to make the user purchase. The notification may include a user interface, a text message (Short Message Service (SMS), Multimedia Messaging Service (MMS), Enhanced Messaging Service (EMS), other messaging modalities), and so on. In some example embodiments, the presentation module 210 may generate the content of the notification based on the commerce item, the user characteristics, the user characteristics of the similar users, the attribute data, and so forth. In various example embodiments, the notification may include the order parameters for the user purchase.
The examiner finds that it would have been obvious to one of ordinary skill in the mobile device and UI art before the effective filing date of the claimed invention to modify Glasgow’s sensor-based system to manage invention with the ability to include such purchase history based patterning, as disclosed throughout Melcher. The motivation to combine these references in such a way comes from Melcher: [0087] “to avoid depletion of a supply of the commerce item”; [0089]; [0091] and also to support zero0effeort shopping which is what Melcher relates to as a whole. In other words, this allows for the obtaining of more accurate and anticipatory reordering, thereby reducing stock outs and user intervention, as expressly taught by Melcher.
With regard to claims 2 and 18, Glasgow further discloses where determining the pattern further comprises receiving, from the at least one first client device, a report that indicates the pattern (see e.g. [0030] where the images received from first device are “reports” regarding the information about the items, the rate of use, etc.).
With regard to claims 3 and 19, Glasgow further discloses determining, based on the pattern, a schedule for transmitting an additional message to the at least one first client device, wherein the additional message indicates for the at least one first client device to purchase the item; and transmitting, to the at least one first client device, the additional message according to the schedule (see e.g. Fig. 9, 930, Remind Me Later).
With regard to claims 8 and 24, Glasgow further discloses displaying, at the user interface of the second client device, the pattern (see e.g. Fig. 9).
With regard to claims 9 and 24-25, Glasgow further discloses where the purchase history data of the previous purchases associated with the item corresponds to at least one of a geographic location or a time period (see e.g. [0085-86] The database may be a user-specific database of items previously purchased by the user, or a global database of all known items. In some example embodiments, both databases are used. (emphasis added), where the time period is the time period before the present operating time).
With regard to claim 10, Glasgow further discloses where the analysis of the purchase history data is performed using at least one machine learning model (see abstract).
Claims 4 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Glasgow, Melcher, in view of International Pub. No. WO 01/71546 A2 to Resh (“Resh”).
With regard to claims 4 and 20, Glasgow is silent regarding predicting, based on the pattern, a frequency of ordering of the item corresponding to the at least one first client device, wherein the schedule for transmitting the message is based on the frequency of ordering of the item.
Resh teaches at e.g. pages 43-44 that it would have been obvious to predicting, based on the pattern (based on real-time inventory levels and actual usage rates), a frequency of ordering of the item corresponding to the at least one first client device (the predicting the frequency of ordering is performed when the system of Resh sends out the one or more reorder notices where this is based on the use and inventory level(s)), wherein the schedule for transmitting the message is based on the frequency of ordering of the item (in other words, the timing of when the reorder notice is sent out is based on the frequency of usage).
Therefore, it would have been obvious to one of ordinary skill in the inventory management art to include the ability to predict a frequency of ordering, and then send out notification of reordering based on that, as taught by Resh, where this is performed in order to maintain appropriate inventory levels of products and reduce inventory back orders, rush orders, and corresponding rush charges and obsolescence. Resh, page 44.
Claims 5 and 21 are rejected under 35 U.S.C. 103 as being unpatentable over Glasgow, Melcher, in view of U.S. Pat. Pub. No. 2014/0249999 to Johnson et al. (“Johnson”).
With regard to claims 5 and 21, Glasgow further discloses image-based inventory and consumption rate (sensor-driven). Melcher further teaches purchase history-based usage rate/demand, combined with smart device inventory. Glasgow and Melcher do not teach the rest of claim 5. Johnson teaches a merchant dashboard showing number of purchases/transactions over time (e.g. [0065]), segmented by geographic region (e.g. [0065]), presented to a second user (merchant) about the behavior of first users (customers) (e.g. [0065] [0085] Fig. 5 [0098-103] [0122] etc.). Therefore, one of ordinary skill in the dashboard analytics art before the effective filing date of the claimed invention would modify Glasgow/Melcher to include such dashboard analytics and the like in order to show the merchant (second user/device) the various data points that have been mathematically calculated to show the merchant what is going on with the products they are selling, in various geographic areas, and the like. This makes it easier for the user to view the data, and make educated decisions from the data presented in different ways.
Claims 6 and 22 are rejected under 35 U.S.C. 103 as being unpatentable over Glasgow, Melcher, in view of U.S. Pat. Pub. No. 2019/0089193 to Ranjin et al. (“Ranjin”).
With regard to claims 6 and 22, Glasgow does not disclose the limitations of claims 6 and 22. However, Ranjin teaches at e.g. Fig. 9F, 9G, [0264-266] that it would have been obvious to transmit a display message including a graph of cumulative user consumption of the item over a time period, and wherein the time period comprises a future time period or a historical time period (see Ranjin, Fig. 9F, 9G, [0264-266]). Therefore, it would have been obvious to one of ordinary skill in the graphing art before the effective filing date of the claimed invention to modify Glasgow to include such as graphical message, where this is beneficial in that the user will be allowed to make multiple comparisons of the months of data. See Ranjin at e.g. [0265].
Claims 7 and 23 are rejected under 35 U.S.C. 103 as being unpatentable over Glasgow, Melcher, in view of U.S. Pat. Pub. No. 2014/0039979 to Zhang et al. (“Zhang”).
With regard to claims 7 and 23, Glasgow does not disclose the limitations of claims 7 and 23. However, Zhang teaches at e.g. Fig. 7, [0019] etc. that it would have been obvious to include the transmitting of a graph of predicted purchases of the item (see e.g. Fig. 7, estimated sales of this year graph, where the “Now” is not at the end of the graph, and therefore this is predicted for the future time period) associated with a geographic location (see e.g. [0019] where this can be applied to a single business) over a future time period (see [0019] into the future). Therefore, it would have been obvious to one of ordinary skill in the forecasting art before the effective filing date of the claimed invention to modify Glasgow to include the transmitting of the forecasted demand of an item into the future, as this allows the business to plan ahead and be prepared for such downturn or upturn in forecasted sales. See Zhang.
Response to Arguments
Applicant's arguments filed 10/22/2025 have been fully considered but they are not persuasive.
Applicant argues that the claims recite eligible subject matter. The examiner respectfully disagrees. The examiner has updated the 101 rejection above to show that the claims not only recite abstract idea, but also are directed to abstract idea. This includes analyzing the claims under Step 2A, Prong 1 and 2; and, Step 2B. Step 2B focuses on whether the claim limitations are well-understood, routine, and conventional. Above, the examiner has succinctly indicated that there are limitations that are WURC.
As for the prior art rejections, the examiner refers to a new secondary reference of Melcher to fill in the argued/amended gaps of the primary reference Glasgow. Accordingly, this is a new ground of rejection and the arguments are moot.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Peter Ludwig whose telephone number is (571)270-5599. The examiner can normally be reached Mon-Fri 9-5.
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/PETER LUDWIG/ Primary Examiner, Art Unit 3627
1 See Applicant’s originally-filed Specification at [0099] “the machine-storage medium is non-transitory.”
2 The crossed-out language is not found to be abstract idea. See additional limitation analysis under Step 2A, Prong 2; and, Step 2B.
Prosecution Insights