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 May 20, 2026. Claims 1-20 were pending in the Application. Claims 1, 4, 7-8, 11, 14-15, and 18 are amended. Claims 21-23 have been added. Claims 6, 13, and 20 have been canceled, with claims 5, 12 and 19 remaining canceled. Claims 1, 8, and 15 are the independent claims, the remaining claims depend on claims 1, 8, and 15. Thus claims 1-4, 7-11, 14-18, and 21-23 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 35 U.S.C. §101, Applicant respectfully traverses the rejection. Applicant is of the opinion that the claims are statutory and respectfully asserts that “it is unclear to Applicant how the recited limitations constitute "fundamental economic principles or practices (including hedging, insurance, mitigating risk)"; the claims do not identify concepts related to fundamental economic practices and respectfully requests withdrawal of the rejection; Applicant respectfully requests an explanation as to how these specific technical limitations are fairly characterized as "insurance payout based on implemented risk mitigation”; even assuming, arguendo, that the claims recite an abstract idea at Step 2A Prong One, the claims integrate any alleged abstract idea into a practical application at Step 2A Prong Two; the claims recite a particular solution to a particular technical problem; amended claim 1 reflects an improvement upon conventional techniques by reciting a specific technical pipeline that solves the technical problem posed by conventional techniques for confirming whether mitigation techniques have been implemented at remote locations; new dependent claims 21-23 recite improvements to machine learning performance by reciting two purpose-specific machine learning models, each actively trained on distinct training datasets associated with different tasks; the first machine learning model, as recited by amended claim 1, is actively trained "using training data corresponding to historical sensor data from historical vehicles within a threshold proximity of various locations at various times and historical mitigation systems confirmed to have been installed at the same locations at the various times”; the second machine learning model, as recited by new claim 21, is actively trained "using a second set of training data corresponding to historical environmental sensor data from historical vehicles within a threshold proximity of various locations at various times and historical weather events confirmed to have occurred at the same locations at the various times"; both models are further applied to the retrieved "environmental sensor data captured by vehicle-mounted sensors associated with the identified one or more vehicles" as recited by amended claim 1; and claims 21-23 recite improvements to the machine learning system by training purpose-specific models on distinct training datasets associated with different workstreams, and respectfully requests withdrawal of the rejection under 35 U.S.C. § 101”.
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 20240062307 A1, para 6), provides evidence as to what the claimed invention is directed. In this case, the specification, (‘307 A1, para 6), discloses that the invention generally relates to avoiding or decreasing payouts that happen due to a lack of mitigation techniques being used by the agribusiness, the agribusiness may be offered a discount on the parametric insurance policy based upon whether or not they have implemented various mitigation techniques”, which recites an abstract idea of “insurance payout based on implemented risk mitigation”, as implementing mitigation techniques is a means by which to reduce or mitigate risk of destruction to property and/or animals. Therefore, this is an abstract idea, and is grouped under “Certain Methods of Organizing Human Activity, fundamental economic principles or practices (including hedging, insurance, mitigating risk), in prong one of step 2A. (MPEP §2106.04 II.A.1.).
Claim 1 provides additional evidence, and recites the limitations of “determining, by one or more processors, an indication of an occurrence of a weather event associated with a location of interest; determining, by the one or more processors, an indication of one or more possible mitigation techniques for mitigating damage caused by the weather event associated with the location of interest; receiving, by the one or more processors, indications of location data captured by location sensors associated with each of a plurality of vehicles over a period of time prior to the occurrence of the weather event, each vehicle of the plurality of vehicles having at least one driver or passenger; comparing, by the one or more processors, the location data captured by the location sensors associated with each of the plurality of vehicles to the location of interest; identifying, by the one or more processors, based upon the comparing, one or more vehicles, of the plurality of vehicles, within a threshold proximity of the location of interest over the period of time; retrieving, by the one or more processors, environmental sensor data captured by vehicle-mounted sensors associated with the identified one or more vehicles within the threshold proximity of the location of interest over the period of time; training, by the one or more processors, a machine learning model using training data corresponding to historical sensor data from historical vehicles within a threshold proximity of various locations at various times and historical mitigation techniques confirmed to have been implemented at the various locations at the various times; determining, by the one or more processors, based upon applying the trained machine learning model to the environmental sensor data captured by the vehicle-mounted sensors associated with the identified one or more vehicles over the period of time, an indication of whether any of the one or more possible mitigation techniques have been performed at the location of interest over the period of time; and automatically initiating, by the one or more processors, a monetary transfer to an individual associated with the location of interest based upon the indication of the occurrence of the weather event associated with the location of interest, and based upon determining whether any of the one or more possible mitigation techniques have been performed at the location of interest over the period of time”. The abstract idea is in italics, and the additional elements are in bold. (MPEP §2106.04 II.A.1.).
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 “using autonomous and connected vehicles”, “a plurality of vehicles configured”, “one or more processors and a memory storing computer-executable instructions that, when executed by the one or more processors, cause the one or more processors to perform operations comprising: …”, “location sensors associated with each of the plurality of vehicles”, “one or more vehicles, of the plurality of vehicles”, “each vehicle of the plurality of vehicles having at least one driver or passenger”, “vehicle-mounted sensors associated with the identified one or more vehicles”, “training a machine learning model using training data corresponding to historical sensor data from historical vehicles within a threshold proximity of various locations at various times and historical mitigation techniques confirmed to have been implemented at the various locations at the various times”, and “based upon applying the trained machine learning model to the environmental sensor data captured by the vehicle-mounted sensors associated with the identified one or more vehicles”, amount to merely “apply it”, as they 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 “insurance payout based on implemented risk mitigation”.
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, “insurance payout based on implemented risk mitigation,” grouped under “Certain Methods of Organizing Human Activity, fundamental economic principles or practices (including hedging, insurance, mitigating risk).”
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 “insurance payout based on implemented risk mitigation.” The claims are not directed to improving computers or related technologies, but improving the method for “insurance payout based on implemented risk mitigation.” For potential improvement in an abstract idea of “insurance payout based on implemented risk mitigation,” it is important to keep in mind that an improvement in the abstract idea itself (e.g. an insurance payout based on implemented risk mitigation concept) is not an improvement in technology. (MPEP § 2106.04(d)(1)). Therefore, claim 1 is non-statutory.
Claim 8 also recites the abstract idea of “insurance payout based on implemented risk mitigation”, as well as the additional elements of “a computer system for using autonomous and connected vehicles”, “a plurality of vehicles configured”, “one or more processors and a memory storing computer-executable instructions that, when executed by the one or more processors, cause the one or more processors to perform operations comprising: …”, “location sensors associated with each of the plurality of vehicles”, “one or more vehicles, of the plurality of vehicles”, “each vehicle of the plurality of vehicles having at least one driver or passenger”, “vehicle-mounted sensors associated with the identified one or more vehicles”, “training, by the one or more processors, a machine learning model using training data corresponding to historical sensor data from historical vehicles within a threshold proximity of various locations at various times and historical mitigation techniques confirmed to have been implemented at the various locations at the various times”, and “based upon applying the trained machine learning model to the environmental sensor data captured by the vehicle-mounted sensors associated with the identified one or more vehicles”, which amount to merely “apply it”, as they 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 “insurance payout based on implemented risk mitigation”.
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 describe the concept of “insurance payout based on implemented risk mitigation” using computer technology (e.g., “one or more processors” and “a memory”). 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 nor improve another technology nor a technical field. Therefore, claim 8 is non-statutory.
Claim 15 also recites the abstract idea of “insurance payout based on implemented risk mitigation”, as well as the additional elements “a non-transitory computer-readable storage medium storing computer-readable instructions for using autonomous and connected vehicles …, wherein the computer-readable instructions, when executed by one or more processors, cause the one or more processors to perform operations comprising: …”, “location sensors associated with each of a plurality of vehicles”, “one or more vehicles, of the plurality of vehicles”, “each vehicle of the plurality of vehicles having at least one driver or passenger”, “vehicle-mounted sensors associated with the identified one or more vehicles”, “training a machine learning model using training data corresponding to historical sensor data from historical vehicles within a threshold proximity of various locations at various times and historical mitigation techniques confirmed to have been implemented at the various locations at the various times”, and “based upon applying the trained machine learning model to the environmental sensor data captured by the sensors associated with the identified one or more vehicles”, which amount to merely “apply it”, as they 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 “insurance payout based on implemented risk mitigation”.
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 describe the concept of “insurance payout based on implemented risk mitigation” using computer technology (e.g., “training a machine learning model using training data corresponding to historical sensor data from historical vehicles within a threshold proximity of various locations at various times and historical mitigation techniques confirmed to have been implemented at the various locations at the various times” 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 nor improve another technology nor a technical field. Therefore, claim 15 is non-statutory.
Finally, Examiner reiterates 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.
In the context of 35 U.S.C. § 103, after further consideration and search, no prior art was found to render at least these limitations obvious:
“receiving, by the one or more processors, indications of location data captured by location sensors associated with each of a plurality of vehicles over a period of time prior to the occurrence of the weather event, each vehicle of the plurality of vehicles having at least one driver or passenger”, “comparing, by the one or more processors, the location data captured by the location sensors associated with each of the plurality of vehicles to the location of interest”, “identifying, by the one or more processors, based upon the comparing, one or more vehicles, of the plurality of vehicles, within a threshold proximity of the location of interest over the period of time”, “retrieving, by the one or more processors, environmental sensor data captured by vehicle-mounted sensors associated with the identified one or more vehicles within the threshold proximity of the location of interest over the period of time”, and “automatically initiating, by the one or more processors, a monetary transfer to an individual associated with the location of interest based upon the indication of the occurrence of the weather event associated with the location of interest, and based upon determining whether any of the one or more possible mitigation techniques have been performed at the location of interest over the period of time”.
Therefore, the rejection under 35 U.S.C. § 103 being rescinded is maintained.
Claim Rejections - 35 USC § 101
35 U.S.C. § 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-4, 7-11, 14-18, and 21-23 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 1-4, 7, and 21 are directed to a “method”; claims 8-11, 14, and 22 are directed to a “system”; and claims 15-18 and 23 are directed to “a non-transitory computer-readable storage medium”. Therefore, these claims are directed to one of the four statutory categories of invention.
Claim 1 recites “insurance payout based on implemented risk mitigation,” which is a form of fundamental economic principles or practices (i.e., organizing human activity), and therefore, an abstract idea. Specifically, the claim recites “determining, by one or more processors, an indication of an occurrence of a weather event associated with a location of interest; determining, by the one or more processors, an indication of one or more possible mitigation techniques for mitigating damage caused by the weather event associated with the location of interest; receiving, by the one or more processors, indications of location data captured by location sensors associated with each of a plurality of vehicles over a period of time prior to the occurrence of the weather event, each vehicle of the plurality of vehicles having at least one driver or passenger; comparing, by the one or more processors, the location data captured by the location sensors associated with each of the plurality of vehicles to the location of interest; identifying, by the one or more processors, based upon the comparing, one or more vehicles, of the plurality of vehicles, within a threshold proximity of the location of interest over the period of time; retrieving, by the one or more processors, environmental sensor data captured by vehicle-mounted sensors associated with the identified one or more vehicles within the threshold proximity of the location of interest over the period of time; training, by the one or more processors, a machine learning model using training data corresponding to historical sensor data from historical vehicles within a threshold proximity of various locations at various times and historical mitigation techniques confirmed to have been implemented at the various locations at the various times; determining, by the one or more processors, based upon applying the trained machine learning model to the environmental sensor data captured by the vehicle-mounted sensors associated with the identified one or more vehicles over the period of time, an indication of whether any of the one or more possible mitigation techniques have been performed at the location of interest over the period of time; and automatically initiating, by the one or more processors, a monetary transfer to an individual associated with the location of interest based upon the indication of the occurrence of the weather event associated with the location of interest, and based upon determining whether any of the one or more possible mitigation techniques have been performed at the location of interest over the period of time”. The abstract idea is in italics, and the additional elements are in bold. (MPEP §2106.04 II.A.1.).
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 “using autonomous and connected vehicles”, “a plurality of vehicles configured”, “one or more processors and a memory storing computer-executable instructions that, when executed by the one or more processors, cause the one or more processors to perform operations comprising: …”, “location sensors associated with each of the plurality of vehicles”, “one or more vehicles, of the plurality of vehicles”, “each vehicle of the plurality of vehicles having at least one driver or passenger”, “vehicle-mounted sensors associated with the identified one or more vehicles”, “training a machine learning model using training data corresponding to historical sensor data from historical vehicles within a threshold proximity of various locations at various times and historical mitigation techniques confirmed to have been implemented at the various locations at the various times”, and “based upon applying the trained machine learning model to the environmental sensor data captured by the vehicle-mounted sensors associated with the identified one or more vehicles”, amount to merely “apply it”, as they 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 “insurance payout based on implemented risk mitigation”.
The limitation of “receiving, by one or more processors, indications of location data captured by location sensors associated with each of a plurality of vehicles over a period of time prior to the occurrence of the weather event, each vehicle of the plurality of vehicles having at least one driver or passenger” as an additional element, is recited at a high level of generality (i.e., as a general means of gathering data from sensors on the vehicles), and amounts to mere data gathering, which is a form of insignificant extra-solution activity.
Accordingly, these additional elements, even in combination, do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
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 “insurance payout based on implemented risk mitigation” using computer technology (e.g., “one or more processors” and “location sensors associated with each of the plurality of vehicles”). 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.
The limitation of “receiving, by one or more processors, indications of location data captured by location sensors associated with each of a plurality of vehicles over a period of time prior to the occurrence of the weather event, each vehicle of the plurality of vehicles having at least one driver or passenger” as an additional , is recited at a high level of generality (i.e., as a general means of gathering data from sensors on the vehicles), and amounts to mere data gathering, which is a form of insignificant extra-solution activity, and does not amount to significantly more than the judicial exception. Therefore, claim 1 is non-statutory.
Claim 8 also recites the abstract idea of “insurance payout based on implemented risk mitigation”, as well as the additional elements of “a computer system for using autonomous and connected vehicles”, “a plurality of vehicles configured”, “one or more processors and a memory storing computer-executable instructions that, when executed by the one or more processors, cause the one or more processors to perform operations comprising: …”, “location sensors associated with each of the plurality of vehicles”, “one or more vehicles, of the plurality of vehicles”, “each vehicle of the plurality of vehicles having at least one driver or passenger”, “vehicle-mounted sensors associated with the identified one or more vehicles”, “training, by the one or more processors, a machine learning model using training data corresponding to historical sensor data from historical vehicles within a threshold proximity of various locations at various times and historical mitigation techniques confirmed to have been implemented at the various locations at the various times”, and “based upon applying the trained machine learning model to the environmental sensor data captured by the vehicle-mounted sensors associated with the identified one or more vehicles”, which amount to merely “apply it”, as they 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 “insurance payout based on implemented risk mitigation”.
The limitation of “receiving indications of location data captured by location sensors associated with each of a plurality of vehicles over a period of time prior to the occurrence of the weather event” as an additional element, is recited at a high level of generality (i.e., as a general means of gathering data from sensors on the vehicles), and amounts to mere data gathering, which is a form of insignificant extra-solution activity.
Accordingly, these additional elements, even in combination, do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
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 describe the concept of “insurance payout based on implemented risk mitigation” using computer technology (e.g., “vehicle-mounted sensors associated with the identified one or more vehicles” and “a memory”). 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 nor improve another technology nor a technical field.
The limitation of “receiving indications of location data captured by location sensors associated with each of a plurality of vehicles over a period of time prior to the occurrence of the weather event” as an additional element, is recited at a high level of generality (i.e., as a general means of gathering data from sensors on the vehicles), and amounts to mere data gathering, which is a form of insignificant extra-solution activity, and does not amount to significantly more than the judicial exception. Therefore, claim 8 is non-statutory.
Claim 15 also recites the abstract idea of “insurance payout based on implemented risk mitigation”, as well as the additional elements “a non-transitory computer-readable storage medium storing computer-readable instructions for using autonomous and connected vehicles …, wherein the computer-readable instructions, when executed by one or more processors, cause the one or more processors to perform operations comprising: …”, “location sensors associated with each of a plurality of vehicles”, “one or more vehicles, of the plurality of vehicles”, “each vehicle of the plurality of vehicles having at least one driver or passenger”, “vehicle-mounted sensors associated with the identified one or more vehicles”, “training a machine learning model using training data corresponding to historical sensor data from historical vehicles within a threshold proximity of various locations at various times and historical mitigation techniques confirmed to have been implemented at the various locations at the various times”, and “based upon applying the trained machine learning model to the environmental sensor data captured by the sensors associated with the identified one or more vehicles”, which amount to merely “apply it”, as they 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 “insurance payout based on implemented risk mitigation”.
The limitation of “receiving indications of location data captured by location sensors associated with each of a plurality of vehicles over a period of time prior to the occurrence of the weather event” as an additional element, is recited at a high level of generality (i.e., as a general means of gathering data from sensors on the vehicles), and amounts to mere data gathering, which is a form of insignificant extra-solution activity.
Accordingly, these additional elements, even in combination, do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
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 describe the concept of “insurance payout based on implemented risk mitigation” using computer technology (e.g., “training a machine learning model using training data corresponding to historical sensor data from historical vehicles within a threshold proximity of various locations at various times and historical mitigation techniques confirmed to have been implemented at the various locations at the various times” 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 nor improve another technology nor a technical field.
The limitation of “receiving indications of location data captured by location sensors associated with each of a plurality of vehicles over a period of time prior to the occurrence of the weather event” as an additional element, is recited at a high level of generality (i.e., as a general means of gathering data from sensors on the vehicles), and amounts to mere data gathering, which is a form of insignificant extra-solution activity, and does not amount to significantly more than the judicial exception. Therefore, claim 15 is non-statutory.
Dependent claims 2-4, 7, 9-11, 14, 16-18, and 21-23 further describe the abstract idea of “insurance payout based on implemented risk mitigation”, which is insufficient to overcome the rejections of claims 1, 8, and 15.
Dependent claims 2, 4, 7, 9, 11, 14, 16, and 18 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 “insurance payout based on implemented risk mitigation”, when analyzed under Step 2A, Prong Two. And, as they do no more than employ a computer as a tool to implement the abstract idea, they do not improve computer functionality nor improve another technology or a technical field, when analyzed under Step 2B.
Dependent claims 3, 10, and 17 recite a new additional element of “a weather event database”, 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 nor improve another technology nor a technical field.
Dependent claims 21-23 recite a new additional element of “a second machine learning model”, 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 nor improve another technology nor a technical field.
Hence, claims 1-4, 7-11, 14-18, and 21-23 are not patent eligible.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Nagata et al (U. S. Patent Application Publication No. 2020320309 A1) – Camera System To Detect Unusual Activities.
Nagata discloses methods, systems, and apparatus for a detection system. The detection system includes a first camera configured to capture a first image data of a surrounding environment. The first image data includes multiple objects. The detection system includes a memory configured to store image data. The detection system includes an electronic control unit. The electronic control unit is configured to obtain the first image data. The electronic control unit is configured to recognize the multiple objects. The electronic control unit is configured to determine that an object among the multiple objects within the surrounding environment is different than a baseline of the surrounding environment. The electronic control unit is configured to record and capture, in the memory and using the camera, the first image data for a time period before and after the determination that the object is different than the baseline.
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 STEVEN CHISM whose telephone number is (571) 272-5915. The examiner can normally be reached during 9:00 AM – 3:00 PM Monday – Thursday, EST.
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/STEVEN R CHISM/Examiner, Art Unit 3692
/DAVID P SHARVIN/Primary Examiner, Art Unit 3692
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