DETAILED ACTION
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 .
Response to Amendment
Applicant’s “Response to Amendment and Reconsideration” filed on 02/12/2026 have been considered.
Applicant’s response by virtue of amendment to claim(s) 1-9, 11, 15-16 have overcome the Examiner’s rejection under 35 USC § 101.
Claim(s) 1-4, 6-9, 11 are amended.
Claim(s) 10, 12-14, 17 are cancelled.
Claim(s) 1-9, 11, 15-16 are pending in this application and an action on the merits follows.
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.
Claim(s) 1-9, 11, 15-16 are rejected under 35 U.S.C. § 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more and thus do not satisfy the criteria for subject matter eligibility.
Step 1
Claim(s) 1 fall(s) in one of the four statutory categories of invention.
Step 2A Prong One: Yes
An automatic inventory shelf monitoring system for monitoring products’ inventory on a shelf unit (300), comprising:
-
generate a single panoramic image of the entire shelf for analysis,
analyze said single panoramic image,
determine the number of units and/or the exact location of each product residing on each shelf of said shelf unit (300), and
provide an output indicating a required amount of units of each product that is required for refilling/restocking the shelf unit (300), and
The limitations of claim(s) 1 recite(s) concept(s) of inventorying management of shelves, which falls into the grouping of Certain Methods of Organizing Human Activity. The concepts of receiving data (A), generating data (B), analyzing data (C), and determining data (D), sending /outputting data (E), using data (F) related to shelf inventory quantities are considered commercial and fundamental economic practice and activities known in the retail industry.
Claims 1-9, 11, 15-16 recite an abstract idea.
Step 2A Prong Two: No
The additional elements are:
Claim(s) 1: “: a) a digital image capturing system designed to capture an image of all product on all shelfs within said shelf unit ((300)); b) a transportation system mounted on said shelf unit (300) and designed to move said image capturing system along said shelf unit (300); and c) a computerized system comprising a processor and a memory”, “said computerized system further includes machine learning algorithms”;
Claim 2: radar;
Claim 3: A barcode reader;
Claims: 5-6: rail(s)
Claims: 7 and 8: camera;
Claim 16: one people-detection unit;
Examiner does not believe the current claimed invention as it is written integrates the recited judicial exception identified under Step 2A Prong One into a practical application.
The additional elements that performs limitation A and the limitations of claims 2-3 and 16 are claimed at a high level of generality and are considered merely data received such as, and thus are considered nothing more than insignificant extra-solution activity; the additional elements that performs limitations B-D are claimed at a high level of generality and are considered nothing more than combine images together and analyze it and determine a quantity of inventory without the recitation of an improvement of technology, technical field, and/or a computer functionality or function; the additional elements that performs limitation E is claimed at a high level of generality and is considered nothing more than data being transmitted, and thus is mere instructions to implement an abstract idea on a computer; the additional elements that performs limitation E is claimed at a high level of generality and is considered nothing more than use historical data adaptively using a existent technology (machine learning) without the recitation of an improvement of technology, technical field, and/or a computer functionality or function. When view in combination, the additional elements generality links the use of the judicial exception to a particular technological environment or field of use, and thus do not integrate the abstract idea into a practical application, and claim(s) 1, 2, 3, 5-6, 7, 8, 16 are directed to the judicial exception.
Claims 1-9, 11, 15-16 recite an abstract idea.
Step 2B: No
Claims 1-9, 11, 15-16 are not including additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed with respect to Step 2A Prong Two, generally links the use of the judicial exception to a particular technological environment or field of use, do not recite significantly more than the judicial exception.
As discussed with respect to Step 2A Prong Two, the same analysis applies here in 2B the additional elements in the claims generally linking the use of the judicial exception to a particular technological environment or field of use (i.e., computer technology) such that they amount to no more than mere instructions to apply the judicial exception using generic computer components. The same analysis applies here in 2B, i.e., generality links the use of the judicial exception to a particular technological environment or field of use.
Examiner takes Official Notices that is old and well-known in the retail environment to have cameras, radar with transportation system, and RFID and barcode technology use to capture data of items on shelves.
Further, Considered as an ordered combination, the additional elements of Applicants' claims add nothing that is not already present when the steps are considered separately. The claimed invention does not focus on an improvement in computers as tools, but rather certain independently abstract ideas of infrastructure management to collect data, receive data, and generate reports that use computers as tools. {Elec. Power, 830 F.3d at 1354). (Step 2B: NO).
Further, the Office have found that receiving and transmitting data over the network is not enough to be patent-eligible, see MPEP 2106.05(d), that gathering data is not enough is not enough to be patent-eligible, see MPEP2106.05(g).
See MPEP 2106.05(d)(II) 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. 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. A VAuto. 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. Hoteis.com, L.P., 773 F.3d 1245, 1258, 113 USPQ2d 1097, 1106 (Fed. Cir. 2014) ("Unlike the claims in Ultramercial,Vne 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, VersataDev. 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.
Even when the steps are considered in combination, did not amount to an inventive concept.
As for dependent claims 2-9, 11, 15-16, the claims merely recite limitations that further narrow the abstract idea recited on claim 1, and thus fail to amount significantly more.
Therefore, claims 1-9, 11, 15-16 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 for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1, 3, 5-6, 8-9, 11, 15 are rejected under 35 U.S.C. 103 as being unpatentable over Kinno et al. (US 20200242541 A1, hereinafter Kinno) in view of Sawasaki (US 20020143672 A1), in view of Bogolea et al. (US 20170337508 A1, hereinafter Bogolea), and further in view of Nazarian et al. (US 20180285902 A1, hereinafter Nazarian).
Regarding claim 1, Kinno discloses:
An automatic inventory shelf monitoring system for monitoring products' inventory on a shelf unit (300), comprising: Figures 12A-12B on the celling or Figures 21A-21B;
a) a digital image capturing system designed to capture an image of all product on all shelfs within said shelf unit ((300)); ([0097] and Figures 12A-12B on the celling or Figures 21A-21B behind the shelf – a camera system with one camera 1201 or a plurality cameras 1201);
b) a transportation system [on celling or behind the] said shelf unit (300) and designed to move said image capturing system along said shelf unit (300); and ([0097] and Figures 12A-12B on the celling or Figures 21A-21B behind the shelf [0141][0142] - 1211 rails to move the camera or cameras);
c) a computerized system comprising a processor and a memory, wherein: ([0098] and Figures 12A the information processing apparatus 1203)
- said computerized system is designed to receive images taken by said image capturing system, analyze [images], determine the number of units and/or the exact location of each product residing on each shelf of said shelf unit (300), and provide an output indicating an amount of units of each product, and. ([0097] “an image of the store shelf 1221 captured by the camera 1201 is sent to the information processing apparatus 1203”; [0098] “detects stockout of a product based on the image of the store shelf 1221 sent from the camera 1201”; [0083] “The stock status 812 is information concerning the stock status of a product, for example, a remaining product quantity, the presence/absence of stock, and a scheduled arrival date/time.”);
Kinno does not disclose the rail as “mounted” on said shelf unit;
Sawasaki discloses: [0059] and Figure 4B and Figure 5A-5B – a motion rails with camera mounted on a shelf;
It would have been obvious to one with ordinary skill in the art before the effective filing date of the invention, to modify Kinno to include the above limitations as taught by Sawasaki, in order to lighten the burden imposed on operating retail business with the reduced number of clerks at the shop as making an inventory, see Sawasaki para. 9.
Kinno discloses an image of the store shelf 1221 captured by the camera 1201 is sent to the information processing apparatus 1203; however, does not disclose generate a single panoramic image of the entire shelf for analysis, analyze said single panoramic image;
Bogolea discloses: [0041][0042] “stiches multiple raw images recorded by the robotic system at one waypoint or along multiple adjacent waypoints into a larger (e.g., panoramic) image of one complete shelving segment or shelving structure…process this larger, composite image in subsequent Blocks of the method S100” see para. 31-32, 42, 50,60-61, 69, 78, 80-81, 100-102, 126-131 - processing the images and counting stock;
It would have been obvious to one with ordinary skill in the art before the effective filing date of the invention, to modify Kinno to include the above limitations as taught by Bogolea, in order to enable the associate to view both real visual data of the store and quantitative and qualitative stock data, see Bogolea para. 127.
Kinno discloses stock status 812 as remaining product quantity on shelf; however, does not disclose “that is required for refilling/restocking the shelf unit (300)” and “said computerized system further includes machine learning algorithms to adaptively improve inventory monitoring based on historical data.”.
Nazarian discloses: [0033][0035]-[0037] “The server 116 generates, based on the current shelf inventory of the product, and using a rate of sales model specific to the product, a schedule for restocking the product on the shelf (404). The server 116 receives a real-time notification that at least one unit of the product has been removed from the shelf (406) and modifies the current shelf inventory based on the notification, to yield an updated shelf inventory (408). The server 116 also modifies the rate of sales model based on the sale, to yield an updated rate of sales model specific to the product (410)”, “the modifying of the rate of sales model is performed using machine learning, wherein the machine learning uses a machine learning model which is updated on a periodic basis”;[0027]-[0028] “ thereby informing the an autonomous vehicle, robot, or a store associate 122 when the shelf 102 needs to be restocked.”, “The robot may receive the request for the item and the number of items to restock”
It would have been obvious to one with ordinary skill in the art before the effective filing date of the invention, to modify Kinno to include the above limitations as taught by Nazarian, in order to increase profit, see Nazarian para. 12.
Regarding claim 3, Kinno does not disclose: wherein said image capturing system further comprises a barcode reader or is configured to read such a barcode, thereby enabling identification of products directly from captured images.
Bogolea discloses: ([0074] “detect a product label on a shelf within the image; reads a barcode, QR code, SKU, product description, and/or other product identifier in Block S130; selects a set of template images tagged with the same barcode, QR code, SKU, product description, facing count, and/or other product identifier in Block S140; and assigns the set of template images to a slot region in the image proximal (e.g., above) the product label. In this variation, the system can then determine the status of a product arranged on the shelf in the corresponding slot in Block S152 based directly on product facing count and product identifier data appearing on a product label applied to a shelf”);
It would have been obvious to one with ordinary skill in the art before the effective filing date of the invention, to modify Kinno to include the above limitations as taught by Bogolea, in order to enable the associate to view both real visual data of the store and quantitative and qualitative stock data, see Bogolea para. 127.
Regarding claim 5, Kinno discloses:
wherein said transportation system comprises a single rail (101) along the shelf unit (300) onto which said image capturing system moves. ([0141] and Figure 21A – a rail 2111 is provided and no rail 2112 is provided);
Regarding claim 6, Kinno discloses:
wherein said transportation system comprises two rails (101),(102) along the shelf unit (300) designed to provide enhanced stability and support for said image capturing system as it moves along. ([0141][0142] and Figure 21A-21B – a rail 2111 is provided and rail 2112 is also provided);
Regarding claim 8, Kinno discloses:
wherein said image capturing system comprises a single image capturing unit (104), including a camera, and said transportation system is further designed to move said image capturing unit (104) up and down thereby enabling scanning all the shelves within the shelf unit (300). ([0097] and Figures 12A-12B on the celling or Figures 21A-21B behind the shelf – a camera system with one camera 1201 or a plurality cameras 1201; [0141][0142] “it is possible to move the camera 2101 in the longitudinal direction (vertical direction) and the lateral direction (horizontal direction)” and Figure 21A-21B – a rail 2111 is provided and rail 2112 is also provided;);
Regarding claim 9, Kinno discloses:
wherein said computerized system is designed to activated automatically generate periodic reports on inventory status and provide alerts for restocking. ([0109] “The display unit 1342 displays the information concerning the stockout product 1223 notified from the notifier 1333 of the information processing apparatus 1203. The display unit 1342 is, for example, a monitor or a display. Note that a sound or light may be generated while displaying the information concerning the stockout product 1223 on the display unit 1342. This can notify the clerk 1232 that the detection of the stockout product 1223 is made.”; [0098] “detects stockout of a product based on the image of the store shelf 1221 sent from the camera 1201”; [0083] “The stock status 812 is information concerning the stock status of a product, for example, a remaining product quantity, the presence/absence of stock, and a scheduled arrival date/time.” ; [0106] “The controller 1332 controls image capturing by the image capturer 1301 and movement of the image capturer 1301 by the moving unit 1302 at a predetermined timing”; [0065] “The controller 332 shortens the interval of control of image capturing by the image capturer 301 and movement by the moving unit 302 in a predetermined time period before the start of an event around the store. It is expected that store visitors concentrate a predetermined time period, for example, an hour to 10 min before the event is held around the store, and the possibility of occurrence of stockout is high.”; [0065] “It is expected that store visitors concentrate a predetermined time period, for example, an hour to 10 min before the event is held around the store, and the possibility of occurrence of stockout is high. Therefore, to cope with this situation, during this time period, the controller 332 shortens the interval of control of the image capturer 301 to control the image capturer 301 to perform image capturing and movement frequently. If the image capturer 301 is moved frequently to capture the store shelf 221 by shortening the interval of control in this way, detection of a stockout product is easy”)
Kinno does not disclose the alert based on predefined thresholds.
Nazarian discloses: [0029]-[0032] “The sales rate for the product is determined based on the factors described herein. The on-shelf inventory level “P” that results in the highest rate of sales is identified. A minimum threshold for the on-0shelf inventory may also be identified. This may be the level below which the rate of sales should robot drop. This level “Min” may be set by a user, such as a store manager or associate”; [0033]-[0036] “the updated schedule can be generated to maintain shelf inventory of the product within a threshold range of the amount of inventory corresponding to the apex rate of sales”;
It would have been obvious to one with ordinary skill in the art before the effective filing date of the invention, to modify Kinno to include the above limitations as taught by Nazarian, in order to maintain a desired sales rate, see Nazarian para. 29.
Regarding claim 11, Kinno does not disclose: wherein said computerized system is further designed to identify the product type, via its barcode or by comparing the image to an existing database.
Bogolea discloses: ([0074]– detect a product label on a shelf within the image; reads a barcode, QR code, SKU, product description, and/or other product identifier in Block S130; selects a set of template images tagged with the same barcode, QR code, SKU, product description, facing count, and/or other product identifier in Block S140; and assigns the set of template images to a slot region in the image proximal (e.g., above) the product label. In this variation, the system can then determine the status of a product arranged on the shelf in the corresponding slot in Block S152 based directly on product facing count and product identifier data appearing on a product label applied to a shelf;
It would have been obvious to one with ordinary skill in the art before the effective filing date of the invention, to modify Kinno to include the above limitations as taught by Bogolea, in order to enable the associate to view both real visual data of the store and quantitative and qualitative stock data, see Bogolea para. 127.
Regarding claim 15, Kinno does not disclose: wherein the system can be activated manually according to need.
Sawasaki discloses: ([0085] When an inventory employee wishes to display a desired object commodity on the management display 53A or 53B, the inventory employee transmits the name of the desired object commodity to the control computer 10A. Upon receipt of the name of the desired object commodity by the control computer 10A, the camera controller 13A causes the TV camera 20A to take an image of a selling area in which the desired object commodity is disposed, and the taken image of the selling area is transmitted to the inventory computer 50A or 50B and displayed on the management display 53A or 53B.);
It would have been obvious to one with ordinary skill in the art before the effective filing date of the invention, to modify Kinno to include the above limitations as taught by Sawasaki, in order to lighten the burden imposed on operating retail business with the reduced number of clerks at the shop as making an inventory, see Sawasaki para. 9.
Claim(s) 2 is rejected under 35 U.S.C. 103 as being unpatentable over Kinno, Sawasaki, Bogolea, and Nazarian combination as applied to claim 1, and further in view of Tiwari et al. (US 20210342772 A1, hereinafter Tiwari).
Regarding claim 2, the combination does not disclose: wherein said image capturing system further comprises at least one radar sender and receiver designed to capture reflected radar signals to identify rear-located units of products, thereby enhancing detection capabilities.
Tiwari discloses: Figure 8 radar scanning modulo; [0020][0023]-[0024] “The radar scanning module (or the remote computer system) can also implement tomographic to compile several radar scans—captured over multiple radar scan cycles at the robotic system moves along one inventory structure—into a 3D radar scan of this inventory structure based on known movements of the robotic system.”
It would have been obvious to one with ordinary skill in the art before the effective filing date of the invention, to modify the combination to include the above limitations as taught by Tiwari, in order to have a new and useful method for maintaining perpetual inventory within a store, see Tiwari para. 2.
Claim(s) 4 is rejected under 35 U.S.C. 103 as being unpatentable over Kinno, Sawasaki, Bogolea, and Nazarian combination as applied to claim 1, and further in view of Trivelpiece et al. (US 20180107969 A1, hereinafter Trivelpiece).
Regarding claim 4, the combination does not disclose: wherein said image capturing system comprises an RF reader, thereby enhancing detection capabilities.
Trivelpiece discloses: [0060] and figure 1 RFID tag reader 160; [0034] “combining data from RFID tag reads and the camera images”
It would have been obvious to one with ordinary skill in the art before the effective filing date of the invention, to modify the combination to include the above limitations as taught by Trivelpiece, in order to have the total accuracy of the inventorying process to be increased by a significant percentage, see Trivelpiece para. 34.
Claim(s) 7 and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Kinno, Sawasaki, Bogolea, and Nazarian combination as applied to claim 1, and further in view of Adato et al. (US 20190215424 A1, hereinafter Adato).
Regarding claim 7, the combination, specifically Kinno discloses:
wherein said image capturing system comprises a plurality of image capturing units (104), including cameras, and ([0097] “a plurality of cameras 1201 may be provided”);
The combination does not disclose: each unit (104) is assigned to a different shelf within said shelf unit (300).
Adato discloses: multiple camera on designated area covering part of the shelf, see para. 149-170; Figure 6A and Figure 6C;
It would have been obvious to one with ordinary skill in the art before the effective filing date of the invention, to modify the combination to include the above limitations as taught by Adato, in order to avoid sending images with customer/employee/people/person to the server, see Adato para. 161.
Regarding claim 16, the combination does not disclose: further comprising at least one people-detection unit, wherein the computerized system is further designed to receive data from said people-detection unit and determine whether one or more persons are standing in-front or in vicinity to the shelf, and activate the system only when it identifies that no person is standing in-front or in vicinity to the shelf.
Adato discloses: [0161]“The selected area may be associated with distance d1 between first retail shelving unit 602 and second retail shelving unit 604. The selected area may be within the field of view of image capture device 506 or an area where the object causes an occlusion of a region of interest (such as a shelf, a portion of a shelf being monitored, and more). Upon detecting object 608, system 500 may cause image capture device 506 to forgo image acquisition while object 608 is within the selected area. In one example, object 608 may be an individual, such as a customer or a store employee... In the example illustrated in FIG. 6A, system 500A may detect that object 608 has entered into its associated field of view (e.g., using a proximity sensor) and may instruct image capturing device 506 to forgo image acquisition”
It would have been obvious to one with ordinary skill in the art before the effective filing date of the invention, to modify the combination to include the above limitations as taught by Adato, in order to avoid sending images with customer/employee/people/person to the server, see Adato para. 161.
Response to Arguments
Applicant's arguments filed 02/12/2026 have been fully considered but are moot because the new ground of rejection necessitated by Applicant's amendments.
Applicant argues the claimed invention as amended cannot be considered receiving data and transferring it, see Remarks page 1. The claimed invention as amended merely recites receiving/generate panoramic image (stitching images)/analyze it without reciting the improvement or technical mechanisms used with an improvement, and cannot be considered an improvement of a technology or technical field or computer function/functionality without an improvement. Further, merely recite a machine learning without using it and without the recitation of the improvement cannot be considered an improvement of technology or technical field. When view in combination, the additional elements generality links the use of the judicial exception to a particular technological environment or field of use, and thus do not integrate the abstract idea into a practical application.
For at least those reasons, the rejection is maintained.
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to VANESSA DELIGI whose telephone number is (571)272-0503. The examiner can normally be reached on Monday-Friday 07:30AM-5PM.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Florian (Ryan) Zeender can be reached on (571) 272-6790. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/VANESSA DELIGI/Patent Examiner, Art Unit 3627
/FLORIAN M ZEENDER/Supervisory Patent Examiner, Art Unit 3627
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