DETAILED ACTION
1. Claims 1-20 are currently pending. The effective filing date of the present application is 4/4/2024.
Notice of Pre-AIA or AIA Status
2. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Interpretation
3. The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are:
Claim 1 – location signaling devices configured to capture wireless signals indicating locations of the objects throughout the physical space, the locations being provided as location data.” See MPEP 2181. Underlined is the generic placeholder used by the claim and bolded is the functional language. The generic placeholder is not modified by sufficient structure, material or acts for performing the claim. Therefore, 112(f) is invoked. See Spec. [0036].
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 101
4. 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.
5. Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed a judicial exception (i.e., an abstract idea) without significantly more.
Step 1 – Statutory Categories
As indicated in the preamble of the claim, the examiner finds the claim is directed to a process, machine, manufacture, or composition of matter. Claims 19-20 are processes (methods), and claims 1-18 are machines (systems or devices).
Step 2A – Prong 1: was there a Judicial Exception Recited
Claim 19 (similarly claim 1) recites the following bolded abstract concepts that are found to include “abstract idea”:
19. A method for determining a wait time of objects in a designated area of a physical space, the method comprising:
receiving, by a computer system, (i) image data from cameras positioned proximate the designated area that are configured to capture the image data of the designated area and (ii) location data from location signaling devices that are configured to capture wireless signals indicating locations of the objects in the physical space, the locations being provided as the location data;
translating, by the computer system, the received image data into a predetermined coordinate plane;
retrieving, by the computer system, one or more artificial intelligence (AI) models from a data store;
identifying, by the computer system, the objects within the designated area based on applying the AI models to at least the translated image data;
correlating, by the computer system, the identified objects with the received location data;
determining, by the computer system, wait time information of the identified objects in the designated area based on applying the AI models to at least the correlated data; and
returning, by the computer system, the wait time information.
Claim 19 (similarly claim 1) is directed to a series of steps for determining a wait time of objects in a designated area of a physical space, which is a managing personal behavior or relationships or interactions between people (social activities, teaching, and following rules or instructions) and thus grouped as a certain method of organizing human interactions and/or a mental process (see above notations). Thus, the claim recites an abstract idea. See MPEP §2106.4(a).
Step 2A – Prong 2: Can the Judicial Exception Recited be integrated into a practical application
Limitations that are indicative of integration into a practical application:
Improvements to the functioning of a computer, or to any other technology or technical field - see MPEP 2106.05(a)
Applying or using a judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition – see Vanda Memo
Applying the judicial exception with, or by use of, a particular machine - see MPEP 2106.05(b)
Effecting a transformation or reduction of a particular article to a different state or thing - see MPEP 2106.05(c)
Applying or using the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception - see MPEP 2106.05(e) and Vanda Memo
Limitations that are not indicative of integration into a practical application:
Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f)
Adding insignificant extra-solution activity to the judicial exception - see MPEP 2106.05(g)
Generally linking the use of the judicial exception to a particular technological environment or field of use – see MPEP 2106.05(h)
This judicial exception is not integrated into a practical application because computer system, artificial intelligence models, cameras, location signaling devices, and wireless communication network are merely generically recited computer elements that do not add a meaningful limitation to the abstract idea because they amount to simply the abstract idea on a generic computer. Accordingly, alone and in combination, these additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. See Specification [0036] discussing the multiple types of generic location signaling devices that could be used. The claim is directed to an abstract idea.
Step 2B – Significantly More Analysis
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because, when considered separately and in combination computer system, artificial intelligence models, cameras, location signaling devices, and wireless communication network amounts to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. Thus, claims 1 and 19 are not patent eligible.
Dependent claims 2-18 and 20 fail to provide additional elements that are sufficient to amount to significantly more than the judicial exception. The dependent claims introduce other additional elements that are amounts to no more than mere instructions to apply the exception using a generic computer component such as POS terminal, GUI display, and OLS model. Therefore, claims 2-18 and 20 are rejected for the same reasons as stated in the rejection from independent claim from which they depend.
Claim Rejections - 35 USC § 102
6. The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale or otherwise available to the public before the effective filing date of the claimed invention.
7. Claims 1-4, 8, 10, 12, 14-15, and 17-19 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by U.S. Pat. Pub. No. 2026/0050852to Zang et al. (“Zang”).
8. With regards to claim 1 (similarly claim 19), Zang disclosed the limitations of,
cameras positioned proximate the designated area and configured to capture image data of the designated area (See [0056] discussing camera placement.);
location signaling devices configured to capture wireless signals indicating locations of the objects throughout the physical space, the locations being provided as location data (See [0053]-[0054] discussing the location of multiple sensors to identified occupied locations, [0065]- [0067] discussing location calculations, and [0006] & [0011] discussing the variety of sensors that could be used) and ; and
a computer system in wireless network communication with the cameras and the location signaling devices, wherein the computer system is configured to perform operations (See generally [0085]-[0093] discussing computer implementation of the process.)comprising:
receiving the image data and the location data from the cameras and the location signaling devices, respectively (See [0045] discussing cameras relaying to the process entrance and exit data and [0049]-[0051] discussing the sensor data being sent to a processor.);
translating the received image data into a predetermined coordinate plane (See Fig. 5 depicting a plane of the store with occupied indicators and [0054] discussing the circle indication of the within the store.);
retrieving one or more artificial intelligence (AI) models from a data store (See [0053] discussing the machine learning aspects of the system being stored on a data server.);
identifying the objects within the designated area based on applying the AI models to at least the translated image data (See [0056] discussing the learning model and camera data being used accounting devices could then generate a series of tuples, with each tuple containing a time stamp and a number of individuals queuing at that time stamp.);
correlating the identified objects with the received location data (See [0065] discussing raining data teaches the sensor selection model the intrinsic correlations between sensor locations and their statistical significance in determining the queue volume prediction.);
determining wait time information of the identified objects in the designated area based on applying the AI models to at least the correlated data (See [0013] discussing the recommendation being based on the queue volume prediction and [0061] discussing the recommender being a machine learning model.); and
returning the wait time information (See [0057] discussing generating a recommendation that includes service time and available queues.).
9. With regards to claim 2, Zang disclosed the limitations of,
wherein the predetermined coordinate plane is a coordinate plane of the location data (See Figs. 4 and 5 depicting a floor plan and [0053] discussing the floor plan being part of the store information saved to the data server.).
10. With regards to claim 3, Zang disclosed the limitations of,
wherein correlating the identified objects with the received location data comprises verifying that the identified objects are located within the designated area before moving to a second designated area proximate the designated area (See [0047] discussing tracking of a person between designated sensor areas.).
11. With regards to claim 4, Zang disclosed the limitations of,
wherein determining wait time information in the designated area comprises generating a count of the identified objects that form a line in the designated space (See [0056] discussing counting a person in checkout area and [0045] discussing counting at ingress and egress of the area.).
12. With regards to claim 8, Zang disclosed the limitations of,
determining a wait time for each of the identified objects based on applying the AI models to at least the correlated data (See [0013] discussing the recommendation being based on the queue volume prediction and [0061] discussing the recommender being a machine learning model.); and
determining an average wait time for the identified objects based on combining the wait time for each of the identified objects (See [0061] discussing setting the service time to the average amount of time.).
13. With regards to claim 10, Zang is silent on the limitations of,
receiving transaction data from one or more point of sale (POS) terminals that are proximate the designated area (See [0053] discussing historical queueing data being received and stored in the data server including information used to make recommendations and [0008]discussing service time for the individual being based transaction time and the number of open queues; and then using the data for the recommendation.); and
correlating, based on applying the AI models, at least one of the image data or the location data with the transaction data to determine the wait time information (See [0008]discussing service time for the individual being based transaction time and the number of open queues; and then using the data for the recommendation. Examiner notes that the number of queues and which queue an individual is in is included as sensor location data, [0047].).
14. With regards to claim 12, Zang disclosed the limitations of,
correlating portions of the translated image data with the received location data that satisfy one or more proximity criteria (See [0053]-[0054] discussing comparing the historical sensor data with the historical queuing data.); and
identifying the objects within the designated area based on applying the AI models to the correlated data(See [0053]-[0056] discussing comparing the historical sensor data with the historical queuing data and training a machine learning aspect based on that data to count the number of people.).
15. With regards to claim 14, Zang disclosed the limitations of,
wherein returning the wait time information comprises presenting the wait time information in a graphical user interface (GUI) display of a user relevant to the physical space (See [0015] discussing the user interface displaying the recommendation.).
16. With regards to claim 15, Zang disclosed the limitations of,
wherein the wait time information is determined, by the computer system, for a predetermined future period of time (See for example [0012] discussing the queue volume prediction corresponds to a predetermined future time window.).
17. With regards to claim 17, Zang disclosed the limitations of,
wherein determining wait time information further comprises generating a graphical depiction of the wait time information that is synced with the translated image data (See Figs. 4 and 5 depicting a floor plan and [0053] discussing the floor plan being part of the store information saved to the data server, [0015] discussing the user interface displaying the recommendation, and [0013] discussing the recommendation being based on the queue volume prediction.).
18. With regards to claim 18, Zang disclosed the limitations of,
wherein the designated area is a wait area before a checkout area in a retail environment (See [0056] discussing cameras tracking in the checkout area.).
Claim Rejections - 35 USC § 103
19. 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.
20. Claims 5-7, 13, and 20 are rejected under 35 U.S.C. 103 as being unpatenable by Zang in view of U.S. Pat. Pub. No. 2021/0124947 to Datar et al. (“Datar”).
21. With regards to claim 5 (similarly claim 20), Zang disclosed the limitations of,
determining that an object amongst the identified objects enters the designated area (See [0056] discussing counting a person in checkout area and [0045] discussing counting at ingress and egress of the area.);
determining that the object enters a second designated area proximate the designated area (See [0047] discussing tracking of a person between designated sensor areas.);
Zang is silent on the limitations of,
detecting a decrease in movement of the object in the designated area;
starting a timer in response to detecting the decrease in movement;
stopping the timer in response to determining that the object enters the second designated area; and
determining a wait time of the object as a total time that the timer was activated.
However, Datar teaches that it would have been obvious to one of ordinary skill in the checkout art to include detecting a decrease in movement of the object in the designated area; starting a timer in response to detecting the decrease in movement; stopping the timer in response to determining that the object enters the second designated area; and determining a wait time of the object as a total time that the timer was activated (See [455] discussing the tracking system monitoring of when an item stops moving and [0590] discussing the tracking system timing the event to determining an amount of time elapsed of the event.).
Therefore, it would have been obvious for one of ordinary skill in the checkout art before the effective filing date of the claimed invention to have modified the teachings of Zang to include detecting a decrease in movement of the object in the designated area; starting a timer in response to detecting the decrease in movement; stopping the timer in response to determining that the object enters the second designated area; and determining a wait time of the object as a total time that the timer was activated, as disclosed by Datar. One of ordinary skill in the art would have been motivated to make this modification in order to identify and track an object within a space (Datar [0022]).
22. With regards to claim 6, Zang is silent on the limitations of,
wherein the AI models were trained to perform the determining, the detecting, the starting, the determining, the stopping, and the determination operations.
However, Datar teaches that it would have been obvious to one of ordinary skill in the checkout art to include wherein the AI models were trained to perform the determining, the detecting, the starting, the determining, the stopping, and the determination operations (See [0041] discussing the tracking system is configured to employ a machine learning model to detect differences between a series of images over time; further, the tracking system is configured to use the machine learning model to determine whether an item has been removed or replaced from a rack and after detecting that an item has been removed or replaces from a rack; and the tracking system may then identify the item and modify a digital cart of a person that is adjacent to the rack based on the identified item.).
Therefore, it would have been obvious for one of ordinary skill in the checkout art before the effective filing date of the claimed invention to have modified the teachings of Zang to include wherein the AI models were trained to perform the determining, the detecting, the starting, the determining, the stopping, and the determination operations, as disclosed by Datar. One of ordinary skill in the art would have been motivated to make this modification in order to identify and track an object within a space (Datar [0022]).
23. With regards to claim 7, Zang disclosed the limitations of,
wherein the AI models were trained to perform the determining the wait time of the object operation (See [0013] discussing the recommendation being based on the queue volume prediction and [0061] discussing the recommender being a machine learning model.).
24. With regards to claim 13, Zang is silent on the limitations of,
wherein the identified objects comprise assets, each of the assets comprising an asset signaling device, wherein the asset signaling device is configured to transmit and receive signals with at least the location signaling devices, wherein the location signaling devices are configured to generate the location data based on the transmitted and received signals with the asset signaling device.
However, Datar teaches that it would have been obvious to one of ordinary skill in the checkout art to include the identified objects comprise assets, each of the assets comprising an asset signaling device, wherein the asset signaling device is configured to transmit and receive signals with at least the location signaling devices, wherein the location signaling devices are configured to generate the location data based on the transmitted and received signals with the asset signaling device (See [0563] discussing using RFID tags for the tracking system to provide distance and location information, [0460] discussing the tag being visible on the item and can be detected by sensors.).
Therefore, it would have been obvious for one of ordinary skill in the checkout art before the effective filing date of the claimed invention to have modified the teachings of Zang to include the identified objects comprise assets, each of the assets comprising an asset signaling device, wherein the asset signaling device is configured to transmit and receive signals with at least the location signaling devices, wherein the location signaling devices are configured to generate the location data based on the transmitted and received signals with the asset signaling device, as disclosed by Datar. One of ordinary skill in the art would have been motivated to make this modification as a simple substitution of one tracking sensor for another.
25. Claim 9 is rejected under 35 U.S.C. 103 as being unpatenable by Zang in view of U.S. Pat. Pub. No. 2023/0079388 to Fisher et al. (“Fisher”).
26. With regards to claim 9, Zang disclosed the limitations of,
identifying one or more objects that are within a threshold proximity of each other in the designated area (See [0066] discussing the sensor location scoring above a predetermined threshold.); and
wherein determining wait time information in the designated area comprises determining a wait time (See [0057] discussing generating a recommendation that includes service time and available queues.)
Zang is silent on the limitations of,
grouping the identified one or more objects into a group, … for the group.
However, Fisher teaches that it would have been obvious to one of ordinary skill in the checkout art to include grouping the identified one or more objects into a group (See [0277] discussing identifying a group of shoppers that are shopping together.).
Therefore, it would have been obvious for one of ordinary skill in the checkout art before the effective filing date of the claimed invention to have modified the teachings of Zang to include grouping the identified one or more objects into a group, as disclosed by Fisher. One of ordinary skill in the art would have been motivated to make this modification in order to identify and track subjects through an event (Fisher [0273]).
27. Claim 11 is rejected under 35 U.S.C. 103 as being unpatenable by Zang in view of U.S. Pat.. No. 7,957,565 to Sharma et al. (“Sharma”).
28. With regards to claim 11, Zang is silent on the limitations of,
detecting one or more of the objects that satisfy one or more object behavior; and
removing the detected objects from the translated image data.
However, Sharma teaches that it would have been obvious to one of ordinary skill in the checkout art to include detecting one or more of the objects that satisfy one or more object behavior; and removing the detected objects from the translated image data group (See [Abstract] discussing recognizing employees among the people in a physical space based on automatic behavior analysis of the people and [Col. 8, l. 58-63] discussing removing employe data from the analysis.).
Therefore, it would have been obvious for one of ordinary skill in the checkout art before the effective filing date of the claimed invention to have modified the teachings of Zang to include detecting one or more of the objects that satisfy one or more object behavior; and removing the detected objects from the translated image data group, as disclosed by Sharma. One of ordinary skill in the art would have been motivated to make this modification in order to focus on customer analysis (Sharma [Col. 8, l. 53- Col. 9, l. 19]).
29. Claim 16 is rejected under 35 U.S.C. 103 as being unpatenable by Zang in view of U.S. Pat. Pub. No. 2011/0264492 to Anand et al. (“Anand”).
30. With regards to claim 16, Zang is silent on the limitations of,
wherein the AI models comprise an ordinary least squares (OLS) model.
However, Anand teaches that it would have been obvious to one of ordinary skill in the checkout art to include the AI models comprise an ordinary least squares (OLS) model (See [0033] discussing using OLS regression as known forecasting or event prediction model.).
Therefore, it would have been obvious for one of ordinary skill in the checkout art before the effective filing date of the claimed invention to have modified the teachings of Zang to include the AI models comprise an ordinary least squares (OLS) model, as disclosed by Anand. One of ordinary skill in the art would have been motivated to make this modification as a simple substitution of a known mathematical model (Anand [0033]).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. See Notice of References Cited, PTO form 892.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MICHAEL JARED WALKER whose telephone number is (303)297-4407. The examiner can normally be reached Monday-Thursday 9:00 AM -5:00 PM CT.
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/MICHAEL JARED WALKER/Primary Examiner, Art Unit 3627 Michael.walker@uspto.gov
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