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 .
Status of Claims
Applicant filed an amendment on October 28, 2025. Claims 1-20 were pending in the Application. Claims 1, 11, and 20, are amended. No new claims have been added. No new claims have been canceled, with claims 9 and 18 remaining canceled. Claims 1, 11, and 20 are the independent claims, the remaining claims depend on claims 1 and 11. Thus claims 1-8, 10-17, and 19-20 are currently pending. After careful and full consideration of Applicant arguments and amendments, the Examiner finds them to be moot and/or not persuasive.
Response to Arguments
In the context of Claim Interpretation, Optional Language, paragraph 13 of the Non-Final Rejection Office Action dated July 29, 2025, Applicant has not adequately amended to render the Claim Interpretation, Optional Language, moot. The limitation of claim 6, “determining, …, the confidence score” does not necessarily occur in the case “the load measurement does not fall within the weight range”. Examiner hereby maintains the Claim Interpretation, Optional Language, paragraph 13 of the Non-Final Rejection Office Action dated February 24, 2025.
In the context of 35 U.S.C. §101, Applicant respectfully disagrees with the rejection. Applicant is of the opinion that the claims are statutory and respectfully asserts that “the present claim integrates any recited abstract idea into a practical application because it addresses a problem that arises specifically in the technical environment of automated checkout shopping carts: the high rate of misidentification of items compared to human-operated carts; in this technical field, a known deficiency is the inability to reliably correlate different sensory signals, such as visual data, with other information about the item, something that a human clerk can do intuitively; the claim applies an integrated hardware arrangement and specific processing steps to detect mismatches between identifiers and actual items placed in the cart, improving the cart's operation itself; the problem of item misidentification arises because the automated cart must operate without human intervention and relies on sensors and models to identify items; the claim solves this problem through a technical arrangement: it uses a plurality of load measurements taken over time from a load sensor physically coupled to the cart's storage area, each with an associated timestamp, rather than a single static measurement, which enables detection of subtle handling differences between items with similar appearances or identifiers; the method combines image data, identifier data, and time-series load measurement data into a feature vector, which is then processed by a machine-learning model trained to compute a confidence score indicating the likelihood that the identifier matches the actual item; a notification is automatically generated to an operator when the confidence score is below a threshold incorporating the computation into the workflow of the cart, minimizing errors in checkout; collectively, these operations improve the functioning and accuracy of the automated cart itself, rather than simply using the cart as a tool to carry out a generic business process; and the claimed invention recites an improvement to a technical field, and thus patent-eligible subject matter under Step 2A, Prong Two of the Alice test.”
Initially, the Examiner would like to point out that the basis of the rejection is Alice, by applying the subject matter eligibility analysis and flowchart according to MPEP § 2106, which applies a two-step framework, earlier set out in Mayo Collaborative Services v. Prometheus Laboratories, Inc., 566 U.S. 66 (2012), "for distinguishing patents that claim laws of nature, natural phenomena, and abstract ideas from those that claim patent-eligible applications of those concepts." Alice, 573 U.S. at 217.
Under the two-step framework, it must first be determined if "the claims at issue are directed to a patent-ineligible concept." If the claims are determined to be directed to a patent-ineligible concept, e.g., an abstract idea, then the second step of the framework is applied to determine if "the elements of the claim ... contain an "inventive concept" sufficient to 'transform' the claimed abstract idea into a patent-eligible application." (citing Mayo, 566 U.S. at 72-73, 79).
With regard to step one of the Alice framework, we apply a "directed to" two-prong test: 1) evaluate whether the claim recites a judicial exception, and 2) if the claim recites a judicial exception, evaluate whether the claim "applies, relies on, or uses the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that the claim is more than a drafting effort designed to monopolize the judicial exception," i.e., whether the claim integrates the judicial exception into a practical application. (MPEP §2106.04 II.A.1. and II.B.2.).
The Specification, (PG Pub US 20240281817 A1, para 1), provides evidence as to what the claimed invention is directed. In this case, the specification, (‘817 A1, para 1), discloses verifying identities predicted for items within a shopping cart, and is grouped under “Certain Methods of Organizing Human Activity, commercial or legal interactions (including agreements in the form of contracts, legal obligations; advertising, marketing or sales activities or behaviors; business relations)” in prong one of step 2A. (MPEP §2106.04 II.A.1.).
Claim 1 provides additional evidence, and recites the method limitations “accessing, by a processor of a shopping cart, an image of an item placed inside the shopping cart, wherein the image is captured by a camera coupled to the cart; receiving, by the processor of the shopping cart, an identifier for the item placed inside the shopping cart; capturing, by the processor of the shopping cart, a plurality of load measurements for the item inside the shopping cart, wherein each load measurement is recorded by a load sensor coupled to a storage area of the shopping cart and is stored with a timestamp describing when the load measurement was recorded, wherein capturing the plurality of load measurements for the item inside the shopping cart comprises: receiving, by the processor of the shopping cart, a load signal from the load sensor coupled to the storage area of the shopping cart, wherein the load signal comprises the plurality of load measurements measured by the load sensor over a period of time; encoding, by the processor of the shopping cart, a feature vector of the item based at least on the captured plurality of load measurements, the accessed image, and the received identifier; inputting, by the processor of the shopping cart, the encoded feature vector to a machine-learning model that is trained to compute a confidence score, the confidence score describing a likelihood that the received identifier matches the item placed inside the shopping cart based on the captured load measurement and the accessed image; determining, by the processor of the shopping cart, that the confidence score is less than a threshold confidence; and generating, by the processor of the shopping cart, a notification alerting an operator of an anomaly in the identifier based on the determination that the confidence score is less than the threshold confidence score”, where the italicized claim language represents the abstract idea of “identification of anomalies in shopping cart items preventing fraud and/or fraudulent activities.” (MPEP §2106.04 II.A.1.).
Additionally, the claim recites “encoding, …, a feature vector of the item based at least on the captured plurality of load measurements, the accessed image, and the received identifier”, “inputting, …, the encoded feature vector … that is trained to compute a confidence score, the confidence score describing a likelihood that the received identifier matches the item placed inside the shopping cart based on the captured load measurement and the accessed image”, and “determining, …, that the confidence score is less than a threshold confidence”, which are mathematical concepts/operations. And, therefore, the claim continues to recite an abstract idea as it has been held that a combination of abstract ideas is still abstract, “Adding one abstract idea (mathematical operations) to another abstract idea (identification of anomalies in shopping cart items preventing fraud and/or fraudulent activities) … does not render the claim non-abstract.” (RecogniCorp, LLC v. Nintendo Co., 855 F.3d 1322, 1327, 122 USPQ2d 1377 (Fed. Cir. 2017)).
This judicial exception is not integrated into a practical application because, when analyzed under prong two of step 2A (MPEP §2106.04 II.A.2.), the additional elements of the claim (the bolded claim language), such as “a processor of a shopping cart”, “a camera coupled to the cart”, “a load sensor coupled to a storage area of the shopping cart”, “encoding, by the processor of the shopping cart, a feature vector of the item based at least on the captured plurality of load measurements, the accessed image, and the received identifier”, “inputting, by the processor of the shopping cart, the encoded feature vector to a machine-learning model that is trained to compute a confidence score”, and “determining, by the processor of the shopping cart, that the confidence score is less than a threshold confidence”, represent the use of a computer as a tool to perform an abstract idea. Therefore, the additional elements do not integrate the abstract idea into a practical application as they do no more than represent a computer performing functions that correspond implementing the acts of “identification of anomalies in shopping cart items preventing fraud and/or fraudulent activities”.
With respect to the limitation, “accessing … wherein the image is captured by a camera coupled to the cart …” is not performed by the “processor”, and therefore, does not further describe accessing data, which represents the use of a computer to perform an economic or other task (MPEP § 2106.05(f)(2)). Same holds for the limitation “ capturing, …, a plurality of load measurements for the item inside the shopping cart, wherein each load measurement is recorded by a load sensor coupled to a storage area of the shopping cart and is stored …” as it describes functionality that is not performed by the “processor”, and therefore does not further describe capturing a plurality of load measurements, which represents the use of a computer to perform an economic or other task (MPEP § 2106.05(f)(2)). Additionally, the limitation “receiving, …, a load signal from the load sensor coupled to the storage area of the shopping cart, wherein the load signal comprises a plurality of load measurements measured by the load sensor over a period of time” is no more than receiving data, and according to MPEP § 2106.05(f)(2), using a computer to retrieve data (e.g., send, receive, store data) neither provides a practical application or significantly more.
Examiner notes the basis of the rejection was, and is not as any mental process covering performance in the mind, but classified as an abstract idea, “identification of anomalies in shopping cart items preventing fraud and/or fraudulent activities”, grouped under “Certain Methods of Organizing Human Activity, commercial or legal interactions (including agreements in the form of contracts, legal obligations; advertising, marketing or sales activities or behaviors; business relations)”.
With respect to the additional elements operating in a non-conventional and non-generic way and reflecting an improvement to a particular technological environment, the cited additional elements represent the use of a computer as a tool to perform an abstract idea. Therefore, the additional elements do not integrate the abstract idea into a practical application as they do no more than represent a computer performing functions that correspond to implementing the acts of “identification of anomalies in shopping cart items preventing fraud and/or fraudulent activities”. The claims are not directed to improving computers or related technologies, but improving the method for “identification of anomalies in shopping cart items preventing fraud and/or fraudulent activities”. For potential improvement in an abstract idea “identification of anomalies in shopping cart items preventing fraud and/or fraudulent activities”, it is important to keep in mind that an improvement in the abstract idea itself (e.g. an identification of anomalies in shopping cart items preventing fraud and/or fraudulent activities concept) is not an improvement in technology. (MPEP § 2106.04(d)(1)). Therefore, claim 1 is non-statutory.
Claim 11 also recites the abstract idea of “identification of anomalies in shopping cart items preventing fraud and/or fraudulent activities”, as well as the additional elements of “a non-transitory computer-readable storage medium”, “a processor of a shopping cart”, “a camera coupled to the cart”, “a load sensor coupled to a storage area of the shopping cart”, “encoding, by the processor of the shopping cart, a feature vector of the item based at least on the captured plurality of load measurements, the accessed image, and the received identifier”, “inputting, by the processor of the shopping cart, the encoded feature vector to a machine-learning model that is trained to compute a confidence score”, and “determining, by the processor of the shopping cart, that the confidence score is less than a threshold confidence”, which represent the use of a computer as a tool to perform an abstract idea. Therefore, the additional elements do not integrate the abstract idea into a practical application as they do no more than represent a computer performing functions that correspond to implementing the acts of “identification of anomalies in shopping cart items preventing fraud and/or fraudulent activities”.
With respect to the limitation, “accessing … wherein the image is captured by a camera coupled to the cart …” is not performed by the “processor”, and therefore, does not further describe accessing data, which represents the use of a computer to perform an economic or other task (MPEP § 2106.05(f)(2)). Same holds for the limitation “ capturing a plurality of load measurements for each item inside the shopping cart, wherein each load measurement is recorded by a load sensor coupled to a storage area of the shopping cart and is stored …” as it describes functionality that is not performed by the “processor”, and therefore does not further describe capturing a plurality of load measurements, which represents the use of a computer to perform an economic or other task (MPEP § 2106.05(f)(2)). Additionally, the limitation “receiving a load signal the load sensor coupled to the storage area of the shopping cart, wherein the load signal comprises the plurality of load measurements measured by the load sensor over a period of time” is no more than receiving data, and according to MPEP § 2106.05(f)(2), using a computer to retrieve data (e.g., send, receive, store data) neither provides a practical application or significantly more.
When analyzed under step 2B (MPEP 2106.05 I.A.), the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception itself. Viewed as a whole, the combination of elements recited in the claim merely describes the concept of “identification of anomalies in shopping cart items preventing fraud and/or fraudulent activities” using computer technology (e.g., “a processor of a shopping cart” and “a non-transitory computer-readable storage medium”). Therefore, the use of these additional elements do no more than employ a computer as a tool to implement the abstract idea. And as the computer does no more than serve as a tool to implement the abstract idea, they do not improve computer functionality or improve another technology or technical field. (MPEP 2106.05 I A (f) & (h)). Therefore, claim 11 is non-statutory.
Claim 20 also recites the abstract idea of “identification of anomalies in shopping cart items preventing fraud and/or fraudulent activities”, as well as the additional elements of “a shopping cart system”, “a shopping cart”, “a load sensor coupled to a storage area of the shopping cart”, “a camera coupled to the shopping cart”, “a processor”, “a non-transitory computer-readable medium”, “encoding, by the processor of the shopping cart, a feature vector of the item based at least on the captured plurality of load measurements, the accessed image, and the received identifier”, “inputting, by the processor of the shopping cart, the encoded feature vector to a machine-learning model that is trained to compute a confidence score”, and “determining, by the processor of the shopping cart, that the confidence score is less than a threshold confidence”, represent the use of a computer as a tool to perform an abstract idea. Therefore, the additional elements do not integrate the abstract idea into a practical application as they do no more than represent a computer performing functions that correspond to implementing the acts of “identification of anomalies in shopping cart items preventing fraud and/or fraudulent activities”.
With respect to the limitation, “accessing … wherein the image is captured by a camera coupled to the cart …” is not performed by the “processor”, and therefore, does not further describe accessing data, which represents the use of a computer to perform an economic or other task (MPEP § 2106.05(f)(2)). Same holds for the limitation “ capturing a plurality of load measurements for the item inside the shopping cart, wherein each load measurement is recorded by the load sensor and is stored …” as it describes functionality that is not performed by the “processor”, and therefore does not further describe capturing a plurality of load measurements, which represents the use of a computer to perform an economic or other task (MPEP § 2106.05(f)(2)).
When analyzed under step 2B (MPEP 2106.05 I.A.), the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception itself. Viewed as a whole, the combination of elements recited in the claim merely describes the concept of “identification of anomalies in shopping cart items preventing fraud and/or fraudulent activities” using computer technology (e.g., “a load sensor coupled to a storage of the shopping cart” and “a machine-learning model”). Therefore, the use of these additional elements do no more than employ a computer as a tool to implement the abstract idea. And as the computer does no more than serve as a tool to implement the abstract idea, they do not improve computer functionality or improve another technology or technical field. (MPEP 2106.05 I A (f) & (h)). Therefore, claim 20 is non-statutory.
Finally, Examiner notes the basis of the rejection is Alice, by applying the subject matter eligibility analysis and flowchart according to MPEP § 2106. And, based on this standard, the claims are non-statutory, and correctly rejected under 35 U.S.C. § 101.
Claim Interpretation - Optional Language
Claim 6, recites the limitation: “The method of claim 1, wherein inputting the encoded feature vector … the confidence score further comprises: … determining, by the processor of the shopping cart, the confidence score based on whether the load measurement falls within the weight range.” Therefore, “determining, …, the confidence score” does not necessarily occur in the case “the load measurement is determined not to fall within the weight range”. (MPEP § 2103 I C and MPEP § 2111.04 II).
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 1-8, 10-17, and 19-20 are rejected under 35 U.S.C. § 101 because the claimed invention is directed to an abstract idea without significantly more.
In the instant case, claims 1-8 and 10 are directed to “a method”; claims 11-17 and 19 are directed to “a non-transitory computer-readable storage medium”; and claim 20 is directed to “a system.” Therefore, these claims are directed to one of the four statutory categories of invention.
Claim 1 recites “identification of anomalies in shopping cart items preventing fraud and/or fraudulent activities”, which is a form of commercial or legal interactions (i.e., organizing human activity), and therefore, an abstract idea. Specifically, the claim recites “accessing, by a processor of a shopping cart, an image of an item placed inside the shopping cart, wherein the image is captured by a camera coupled to the cart; receiving, by the processor of the shopping cart, an identifier for the item placed inside the shopping cart; capturing, by the processor of the shopping cart, a plurality of load measurements for the item inside the shopping cart, wherein each load measurement is recorded by a load sensor coupled to a storage area of the shopping cart and is stored with a timestamp describing when the load measurement was recorded, wherein capturing the plurality of load measurements for the item inside the shopping cart comprises: receiving, by the processor of the shopping cart, a load signal from the load sensor coupled to the storage area of the shopping cart, wherein the load signal comprises the plurality of load measurements measured by the load sensor over a period of time; encoding, by the processor of the shopping cart, a feature vector of the item based at least on the captured plurality of load measurements, the accessed image, and the received identifier; inputting, by the processor of the shopping cart, the encoded feature vector to a machine-learning model that is trained to compute a confidence score, the confidence score describing a likelihood that the received identifier matches the item placed inside the shopping cart based on the captured load measurement and the accessed image; determining, by the processor of the shopping cart, that the confidence score is less than a threshold confidence; and generating, by the processor of the shopping cart, a notification alerting an operator of an anomaly in the identifier based on the determination that the confidence score is less than the threshold confidence score”. The abstract idea is in italics, and the additional elements are in bold. (MPEP §2106.04 II.A.1.).
Additionally, the claim recites “encoding, …, a feature vector of the item based at least on the captured plurality of load measurements, the accessed image, and the received identifier”, “inputting, …, the encoded feature vector … that is trained to compute a confidence score, the confidence score describing a likelihood that the received identifier matches the item placed inside the shopping cart based on the captured load measurement and the accessed image”, and “determining, …, that the confidence score is less than a threshold confidence”, which are mathematical concepts/operations. And, therefore, the claim continues to recite an abstract idea as it has been held that a combination of abstract ideas is still abstract, “Adding one abstract idea (mathematical operations) to another abstract idea (identification of anomalies in shopping cart items preventing fraud and/or fraudulent activities) … does not render the claim non-abstract.” (RecogniCorp, LLC v. Nintendo Co., 855 F.3d 1322, 1327, 122 USPQ2d 1377 (Fed. Cir. 2017)).
This judicial exception is not integrated into a practical application because, when analyzed under prong two of step 2A (MPEP §2106.04 II.A.2.), the additional elements of the claim, such as “a processor of a shopping cart”, “a camera coupled to the cart”, “a load sensor coupled to a storage area of the shopping cart”, “encoding, by the processor of the shopping cart, a feature vector of the item based at least on the captured plurality of load measurements, the accessed image, and the received identifier”, “inputting, by the processor of the shopping cart, the encoded feature vector to a machine-learning model that is trained to compute a confidence score”, and “determining, by the processor of the shopping cart, that the confidence score is less than a threshold confidence”, represent the use of a computer as a tool to perform an abstract idea. Therefore, the additional elements do not integrate the abstract idea into a practical application as they do no more than represent a computer performing functions that correspond to implementing the acts of “identification of anomalies in shopping cart items preventing fraud and/or fraudulent activities”.
With respect to the limitation, “accessing … wherein the image is captured by a camera coupled to the cart …” is not performed by the “processor”, and therefore, does not further describe accessing data, which represents the use of a computer to perform an economic or other task (MPEP § 2106.05(f)(2)). Same holds for the limitation “ capturing, …, a plurality of load measurements for the item inside the shopping cart, wherein each load measurement is recorded by a load sensor coupled to a storage area of the shopping cart and is stored …” as it describes functionality that is not performed by the “processor”, and therefore does not further describe capturing a plurality of load measurements, which represents the use of a computer to perform an economic or other task (MPEP § 2106.05(f)(2)). Additionally, the limitation “receiving, …, a load signal from the load sensor coupled to the storage area of the shopping cart, wherein the load signal comprises a plurality of load measurements measured by the load sensor over a period of time” is no more than receiving data, and according to MPEP § 2106.05(f)(2), using a computer to retrieve data (e.g., send, receive, store data) neither provides a practical application or significantly more.
Therefore, the additional elements do not integrate the abstract idea into a practical application as they do no more than represent a computer performing functions that correspond to implementing the acts of “identification of anomalies in shopping cart items preventing fraud and/or fraudulent activities.”
When analyzed under step 2B (MPEP 2106.05 I.A.), the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception itself. Viewed as a whole, the combination of elements recited in the claim merely describes the concept of “identification of anomalies in shopping cart items preventing fraud and/or fraudulent activities” using computer technology (e.g., “a processor of a shopping cart” and “a machine-learning model”). Therefore, the use of these additional elements do no more than employ a computer as a tool to implement the abstract. And as the computer does no more than serve as a tool to implement the abstract idea, they do not improve computer functionality or improve another technology or technical field. (MPEP 2106.05 I A (f) & (h)). Therefore, claim 1 is non-statutory.
Claim 11 also recites the abstract idea of “identification of anomalies in shopping cart items preventing fraud and/or fraudulent activities”, as well as the additional elements of “a non-transitory computer-readable storage medium”, “a processor of a shopping cart”, “a camera coupled to the cart”, “a load sensor coupled to a storage area of the shopping cart”, “encoding, by the processor of the shopping cart, a feature vector of the item based at least on the captured plurality of load measurements, the accessed image, and the received identifier”, “inputting, by the processor of the shopping cart, the encoded feature vector to a machine-learning model that is trained to compute a confidence score”, and “determining, by the processor of the shopping cart, that the confidence score is less than a threshold confidence”, represent the use of a computer as a tool to perform an abstract idea. Therefore, the additional elements do not integrate the abstract idea into a practical application as they do no more than represent a computer performing functions that correspond to implementing the acts of “identification of anomalies in shopping cart items preventing fraud and/or fraudulent activities”.
With respect to the limitation, “accessing … wherein the image is captured by a camera coupled to the cart …” is not performed by the “processor”, and therefore, does not further describe accessing data, which represents the use of a computer to perform an economic or other task (MPEP § 2106.05(f)(2)). Same holds for the limitation “ capturing a plurality of load measurements for the item inside the shopping cart, wherein each load measurement is recorded by a load sensor coupled to a storage area of the shopping cart and is stored …” as it describes functionality that is not performed by the “processor”, and therefore does not further describe capturing a plurality of load measurements, which represents the use of a computer to perform an economic or other task (MPEP § 2106.05(f)(2)). Additionally, the limitation “receiving a load signal from the load sensor coupled to the storage area of the shopping cart, wherein the load signal comprises the plurality of load measurements measured by the load sensor over a period of time” is no more than receiving data, and according to MPEP § 2106.05(f)(2), using a computer to retrieve data (e.g., send, receive, store data) neither provides a practical application or significantly more.
When analyzed under step 2B (MPEP 2106.05 I.A.), the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception itself. Viewed as a whole, the combination of elements recited in the claim merely describes the concept of “identification of anomalies in shopping cart items preventing fraud and/or fraudulent activities” using computer technology (e.g., “a processor of a shopping cart” and “a non-transitory computer-readable storage medium”). Therefore, the use of these additional elements do no more than employ a computer as a tool to implement the abstract idea. And as the computer does no more than server as a tool to implement the abstract idea, they do not improve computer functionality or improve another technology or technical field. (MPEP 2106.05 I A (f) & (h)). Therefore, claim 11 is non-statutory.
Claim 20 also recites the abstract idea of “identification of anomalies in shopping cart items preventing fraud and/or fraudulent activities”, as well as the additional elements of “a shopping cart system”, “a shopping cart”, “a load sensor coupled to a storage area of the shopping cart”, “a camera coupled to the shopping cart”, “a processor”, “a processor”, “a non-transitory computer-readable medium”, “encoding, by the processor of the shopping cart, a feature vector of the item based at least on the captured plurality of load measurements, the accessed image, and the received identifier”, “inputting, by the processor of the shopping cart, the encoded feature vector to a machine-learning model that is trained to compute a confidence score”, and “determining, by the processor of the shopping cart, that the confidence score is less than a threshold confidence”, represent the use of a computer as a tool to perform an abstract idea. Therefore, the additional elements do not integrate the abstract idea into a practical application as they do no more than represent a computer performing functions that correspond to implementing the acts of “identification of anomalies in shopping cart items preventing fraud and/or fraudulent activities”.
With respect to the limitation, “accessing … wherein the image is captured by a camera coupled to the cart …” is not performed by the “processor”, and therefore, does not further describe accessing data, which represents the use of a computer to perform an economic or other task (MPEP § 2106.05(f)(2)). Same holds for the limitation “ capturing a plurality load measurements for the item inside the shopping cart, wherein each load measurement is recorded by the load sensor and is stored …” as it describes functionality that is not performed by the “processor”, and therefore does not further describe capturing a plurality of load measurements, which represents the use of a computer to perform an economic or other task (MPEP § 2106.05(f)(2)).
When analyzed under step 2B (MPEP 2106.05 I.A.), the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception itself. Viewed as a whole, the combination of elements recited in the claim merely describes the concept of “identification of anomalies in shopping cart items preventing fraud and/or fraudulent activities” using computer technology (e.g., “a load sensor coupled to a storage of the shopping cart” and “a machine-learning model”). Therefore, the use of these additional elements do no more than employ a computer as a tool to implement the abstract idea. And as the computer does no more than serve as a tool to implement the abstract idea, they do not improve computer functionality or improve another technology or technical field. (MPEP 2106.05 I A (f) & (h)). Therefore, claim 20 is non-statutory.
Dependent claims 2-8, 10, 12-17, and 19 further describe the abstract idea of “identification of anomalies in shopping cart items preventing fraud and/or fraudulent activities”, which is insufficient to overcome the rejections of claims 1 and 11.
Dependent claims 3-8, 10, 13-17, and 19 do not recite any new additional elements that integrate the abstract idea into a practical application, and that do no more than represent a computer performing functions that correspond to implementing the acts of “identification of anomalies in shopping cart items preventing fraud and/or fraudulent activities”, when analyzed under Step 2A, Prong Two.
Dependent claims 2 and 12 recite a new additional element of “a graphical user interface on the shopping cart”, which does no more than employ a computer as a tool to implement the abstract idea. And, as it does no more than employ a computer as a tool to implement the abstract idea, it does not improve computer functionality or improve another technology or technical field.
Hence, claims 1-8, 10-17, and 19-20 are not patent eligible.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Cohn et al (U. S. Patent No. 11064821 B2) – Resolving Events In Item-Identifying Carts
Cohn discloses item-identifying carts that may be utilized by users to automatically identify items that the users place in their carts. In addition, these carts may automatically determine the outcome of respective events that occur with respect to these identified items. For example, the carts may be configured to identify one or more items that are placed into or removed from the cart, and thereafter determine one or more actions taken with respect to the identified items and a quantity of the items involved. For example, after identifying a first item and a second item either placed into or removed from the cart, the cart may determine that the user added two instances of the first item and removed one instance of the second item. In response to making this determination, the cart may update a virtual cart of a user operating the physical cart.
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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/STEVEN R CHISM/Examiner, Art Unit 3692
/RYAN D DONLON/Supervisory Patent Examiner, Art Unit 3692