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 .
DETAILED CORRESPONDENCE
Claim Objections
Claim 11 is objected to because of the following informalities: the second “for” in line 2 should be removed. Appropriate correction is required.
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 – 20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claims recite:
Claim 1:
receive sensor data associated with an appliance, the data corresponding to a measurement of one or more aspects related to a functioning of the appliance;
apply the sensor data to output an identified issue causing the appliance to improperly function by analyzing the received data associated with the appliance;
identify a part for the appliance to address the improper functioning of the appliance;
generate and transmit an alert to a stakeholder of the appliance, the alert identifying a skill level associated with fixing the issue associated with the appliance and a description of the issue associated with the appliance;
generate and transmit one or more questions to the stakeholder, the one or more questions related to fixing the issue and configured to facilitate assessing whether the stakeholder has the skill level to implement the fixing of the issue
in response to one or more inputs from the stakeholder responding to the one or more questions, generate recommendation including a proposed fix to be implemented by the stakeholder or a recommendation of a professional service provider to address the issue; and
in response to an election by the stakeholder of one of the recommendations, generate additional outputs to address fixing the issue.
Claim 11:
receiving sensor data, the sensor data corresponding to a measurement of one or more aspects related to the functioning of the appliance or system;
applying the sensor data to output an identified issue causing the appliance or system to improperly function;
based upon the received data, identifying a part associated with the improper functioning of the appliance or system;
generating and transmitting an alert to a stakeholder of the appliance or system, the alert identifying a skill level associated with fixing the issue associated with the appliance or system and a description of the issue associated with the appliance or system;
generating and transmitting one or more questions to the stakeholder device, the one or more questions related to fixing the issue and configured to facilitate assessing whether the stakeholder has the skill level to implement the fixing of the issue;
in response to one or more inputs from the stakeholder responding to the one or more questions, generating a recommendation including a proposed fix to be implemented by the stakeholder or a recommendation of a professional service provider to address the issue; and
in response to an election by the stakeholder of one of the recommendations, performing additional steps to facilitate fixing the improperly functioning appliance or system
Claim 20:
receive sensor data corresponding to an issue related to an appliance or system, the sensor data including at least one of: audio data, video data, or text data;
apply the sensor data to an output an identified issue causing the appliance or system to improperly function;
identify a part associated with the improperly functioning appliance or system that requires replacing or repairing;
generate and transmit one or more questions to a stakeholder device associated with a stakeholder of the appliance or system, the one or more questions related to fixing the issue and configured to facilitate assessing whether the stakeholder has a skill level to implement the fixing of the issue
based upon one or more inputs from the stakeholder responding to the one or more questions, generate a recommendation including a proposed fix to be implemented by the stakeholder or a recommendation of a professional service provider to address the issue
in response to an election by the stakeholder of one of the recommendations, provide additional information to facilitate fixing the issue with the improperly functioning appliance or system
The invention is directed towards the abstract idea of product maintenance assistance, which corresponds to “Mental Processes” and “Certain Methods of Organizing Human Activities” as it is directed towards steps that can be performed by a human(s), in the human mind, and/or with the aid of pen and paper, e.g., having a consumer contact a service provider to be provided with information to address an issue that the consumer is having with their product based on symptoms the product is having. The invention corresponds to “Mental Processes” because it is directed towards the collection and comparison of information and, based a rule, identify options, in this case, collecting product related information, comparing the information to known information, and, based on a rule(s), identify and provide information to resolve an issue, which are steps that can be performed by a huma in their mind and/or with the aid of pen and paper. The invention also corresponds to “Certain Methods of Organizing Human Activities” because it encompasses a commercial interaction between a consumer and service provider (or the like) to resolve a product issue and/or managing interactions between peoples, in this case, a service provider (or the like) providing a recommendation (teaching) to the consumer to resolve an issue.
The limitations of:
Claim 1:
receive sensor data associated with an appliance, the data corresponding to a measurement of one or more aspects related to a functioning of the appliance;
apply the sensor data to output an identified issue causing the appliance to improperly function by analyzing the received data associated with the appliance;
identify a part for the appliance to address the improper functioning of the appliance;
generate and transmit an alert to a stakeholder of the appliance, the alert identifying a skill level associated with fixing the issue associated with the appliance and a description of the issue associated with the appliance;
generate and transmit one or more questions to the stakeholder, the one or more questions related to fixing the issue and configured to facilitate assessing whether the stakeholder has the skill level to implement the fixing of the issue
in response to one or more inputs from the stakeholder responding to the one or more questions, generate recommendation including a proposed fix to be implemented by the stakeholder or a recommendation of a professional service provider to address the issue; and
in response to an election by the stakeholder of one of the recommendations, generate additional outputs to address fixing the issue.
Claim 11:
receiving sensor data, the sensor data corresponding to a measurement of one or more aspects related to the functioning of the appliance or system;
applying the sensor data to output an identified issue causing the appliance or system to improperly function;
based upon the received data, identifying a part associated with the improper functioning of the appliance or system;
generating and transmitting an alert to a stakeholder of the appliance or system, the alert identifying a skill level associated with fixing the issue associated with the appliance or system and a description of the issue associated with the appliance or system;
generating and transmitting one or more questions to the stakeholder device, the one or more questions related to fixing the issue and configured to facilitate assessing whether the stakeholder has the skill level to implement the fixing of the issue;
in response to one or more inputs from the stakeholder responding to the one or more questions, generating a recommendation including a proposed fix to be implemented by the stakeholder or a recommendation of a professional service provider to address the issue; and
in response to an election by the stakeholder of one of the recommendations, performing additional steps to facilitate fixing the improperly functioning appliance or system
Claim 20:
receive sensor data corresponding to an issue related to an appliance or system, the sensor data including at least one of: audio data, video data, or text data;
apply the sensor data to an output an identified issue causing the appliance or system to improperly function;
identify a part associated with the improperly functioning appliance or system that requires replacing or repairing;
generate and transmit one or more questions to a stakeholder device associated with a stakeholder of the appliance or system, the one or more questions related to fixing the issue and configured to facilitate assessing whether the stakeholder has a skill level to implement the fixing of the issue
based upon one or more inputs from the stakeholder responding to the one or more questions, generate a recommendation including a proposed fix to be implemented by the stakeholder or a recommendation of a professional service provider to address the issue
in response to an election by the stakeholder of one of the recommendations, provide additional information to facilitate fixing the issue with the improperly functioning appliance or system,
are processes that, under its broadest reasonable interpretation, covers performance of the limitation performed by a human(s), in the human mind, and/or with the aid of pen and paper, but for the recitation of a generic processor executing computer code stored on a computer medium and generic artificial intelligence model. That is, other than reciting a generic processor executing computer code stored on a computer medium and generic artificial intelligence model nothing in the claim element precludes the step from practically being performed in the mind. For example, but for the generic processor executing computer code stored on a computer medium and generic artificial intelligence model in the context of this claim encompasses a consumer can observe how their appliance is performing, report (verbally, written, or the like) their findings to another entity (e.g., service provider), and have the service provider provide (verbally, written, or etc.) information to the consumer to resolve the issue. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of a generic processor executing computer code stored on a computer medium, then it falls within the “Mental Processes” and “Certain Methods of Organizing Human Activities” groupings of abstract ideas. Accordingly, the claims recite an abstract idea.
This judicial exception is not integrated into a practical application. In particular, the claim only recites additional elements – a generic processor executing computer code stored on a computer medium to communicate information, as well as performing operations that a human can perform in their mind and/or pen and paper, i.e. identifying and providing information regarding an issue and its fix. The generic processor executing computer code stored on a computer medium in the steps are recited at a high-level of generality (i.e., as a generic processor executing computer code stored on a computer medium can perform the insignificant extra solution steps of communicating information (See MPEP 2106.05(g) while also reciting that the a generic processor executing computer code stored on a computer medium are merely being applied to perform the steps that can be performed by a human(s), in the human mind, and/or with the aid of pen and paper; "[use] of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more.” Therefore, according to the MPEP, this is not solely limited to computers but includes other technology that, recited in an equivalent to “apply it,” is a mere instruction to perform the abstract idea on that technology (See MPEP 2106.05(f)) such that it amounts no more than mere instructions to apply the exception using a generic processor executing computer code stored on a computer medium.
Although the claim recites “artificial intelligence (AI) models,” the claims and specification fail to provide sufficient disclosure regarding an improvement to AI, but simply recites a high-level generic recitation that applying AI to produce a result, i.e. recommendation or additional outputs. There is insufficient evidence from the specification to indicate that the use of the AI involves anything other than the generic application of a known technique or that the claimed invention purports to improve the functioning of the computer itself or the AI. None of the limitations reflects an improvement in the functioning of a computer, or an improvement to other technology or technical field, applies or uses a judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition, implements a judicial exception with, or uses a judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim, effects a transformation or reduction of a particular article to a different state or thing, or applies or uses 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.
Applying AI is simply application of a computer model, itself an abstract idea manifestation. Further, such training and applying of a model is no more than putting data into a black box machine learning operation. The specification does not contend it invented any of these activities, or the creation and use of such machine learning models (See ¶ 6, 25, 33, 35, 48, 60, 94 of the applicant’s specification). In short, each step does no more than require a generic computer to perform generic computer functions. As to the data operated upon, "even if a process of collecting and analyzing information is 'limited to particular content' or a particular 'source,' that limitation does not make the collection and analysis other than abstract." SAP America, Inc. v. InvestPic LLC, 898 F.3d 1161, 1168 (Fed. Cir. 2018).
The Examiner asserts that the scope of the disclosed invention, as presented in the originally filed specification, is not directed towards the improvement of machine learning, but directed towards providing the necessary information to service a product based on the collection and comparison of information and, based on a rule(s), identify options to resolve an issue that a product is having by providing information to a user. The specification’s disclosure on machine learning is nothing more than a high general explanation of generic technology and applying it to the abstract idea. Referring to MPEP § 2106.05(f), the generating the information using an AI model is merely being used to facilitate the tasks of the abstract idea, which provides nothing more than a results-oriented solution that lacks detail of the mechanism for accomplishing the result and is equivalent to the words “apply it,” per MPEP § 2106.05(f). The Examiner asserts that in light of the 2024 Guidance Update on Patent Subject Matter Eligibility, Including on Artificial Intelligence, the claimed invention is analogous to Example 47, Claim 2.
Further, the combination of these elements is nothing more than a generic computing system with AI. Because the additional elements are merely instructions to apply the abstract idea to a computer, as described in MPEP § 2106.05(f), they do not integrate the abstract idea into a practical application.
Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claims are directed to an abstract idea.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of using a generic processor executing computer code stored on a computer medium to perform the steps of:
Claim 1:
receive sensor data associated with an appliance, the data corresponding to a measurement of one or more aspects related to a functioning of the appliance;
apply the sensor data to output an identified issue causing the appliance to improperly function by analyzing the received data associated with the appliance;
identify a part for the appliance to address the improper functioning of the appliance;
generate and transmit an alert to a stakeholder of the appliance, the alert identifying a skill level associated with fixing the issue associated with the appliance and a description of the issue associated with the appliance;
generate and transmit one or more questions to the stakeholder, the one or more questions related to fixing the issue and configured to facilitate assessing whether the stakeholder has the skill level to implement the fixing of the issue
in response to one or more inputs from the stakeholder responding to the one or more questions, generate recommendation including a proposed fix to be implemented by the stakeholder or a recommendation of a professional service provider to address the issue; and
in response to an election by the stakeholder of one of the recommendations, generate additional outputs to address fixing the issue.
Claim 11:
receiving sensor data, the sensor data corresponding to a measurement of one or more aspects related to the functioning of the appliance or system;
applying the sensor data to output an identified issue causing the appliance or system to improperly function;
based upon the received data, identifying a part associated with the improper functioning of the appliance or system;
generating and transmitting an alert to a stakeholder of the appliance or system, the alert identifying a skill level associated with fixing the issue associated with the appliance or system and a description of the issue associated with the appliance or system;
generating and transmitting one or more questions to the stakeholder device, the one or more questions related to fixing the issue and configured to facilitate assessing whether the stakeholder has the skill level to implement the fixing of the issue;
in response to one or more inputs from the stakeholder responding to the one or more questions, generating a recommendation including a proposed fix to be implemented by the stakeholder or a recommendation of a professional service provider to address the issue; and
in response to an election by the stakeholder of one of the recommendations, performing additional steps to facilitate fixing the improperly functioning appliance or system
Claim 20:
receive sensor data corresponding to an issue related to an appliance or system, the sensor data including at least one of: audio data, video data, or text data;
apply the sensor data to an output an identified issue causing the appliance or system to improperly function;
identify a part associated with the improperly functioning appliance or system that requires replacing or repairing;
generate and transmit one or more questions to a stakeholder device associated with a stakeholder of the appliance or system, the one or more questions related to fixing the issue and configured to facilitate assessing whether the stakeholder has a skill level to implement the fixing of the issue
based upon one or more inputs from the stakeholder responding to the one or more questions, generate a recommendation including a proposed fix to be implemented by the stakeholder or a recommendation of a professional service provider to address the issue
in response to an election by the stakeholder of one of the recommendations, provide additional information to facilitate fixing the issue with the improperly functioning appliance or system,
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.
Additionally:
Claim 2 is directed towards description subject matter describing the information that is included in the recommendation.
Claim 3 is directed towards human activities that encompass a user electing the manner to resolve an issue and providing the necessary information to identify and provide a list of solutions, e.g., list of service providers.
Claim 4 is directed towards collecting and organizing information, descriptive subject matter describing information (e.g., predetermined criteria), and extra-solution activity of presenting (displaying) and communicating information.
Claim 5 is directed towards the human activity of contacting a service provider to receive a quote and/or service scheduling.
Claims 6, 7, 8 are directed towards human activities that encompass a user electing the manner to resolve an issue and providing the necessary information to resolve the issue, e.g., do-it-yourself (DIY) instructions, pricing information, availability, delivery, and/or part information.
Claim 9 is directed towards the collection and storage of information, as well as reviewing the information, which can be performed by a human, in this case, collecting additional information after a product has been serviced, reviewing the collected information to determine if the issue has been resolved, and describing details regarding the servicing of the product.
Claim 10 is directed towards reciting generic technology at a high level of generality and applying it to the abstract idea.
Although the claim recites “generative artificial intelligence (AI) models,” the claims and specification fail to provide sufficient disclosure regarding an improvement to AI, but simply recites a high-level generic recitation that applying AI to produce a result, i.e. recommendation or additional outputs. There is insufficient evidence from the specification to indicate that the use of the AI involves anything other than the generic application of a known technique or that the claimed invention purports to improve the functioning of the computer itself or the AI. None of the limitations reflects an improvement in the functioning of a computer, or an improvement to other technology or technical field, applies or uses a judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition, implements a judicial exception with, or uses a judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim, effects a transformation or reduction of a particular article to a different state or thing, or applies or uses 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.
Applying AI is simply application of a computer model, itself an abstract idea manifestation. Further, such training and applying of a model is no more than putting data into a black box machine learning operation. The specification does not contend it invented any of these activities, or the creation and use of such machine learning models (See ¶ 6, 25, 33, 35, 48, 60, 94 of the applicant’s specification). In short, each step does no more than require a generic computer to perform generic computer functions. As to the data operated upon, "even if a process of collecting and analyzing information is 'limited to particular content' or a particular 'source,' that limitation does not make the collection and analysis other than abstract." SAP America, Inc. v. InvestPic LLC, 898 F.3d 1161, 1168 (Fed. Cir. 2018).
The Examiner asserts that the scope of the disclosed invention, as presented in the originally filed specification, is not directed towards the improvement of machine learning, but directed towards providing the necessary information to service a product based on the collection and comparison of information and, based on a rule(s), identify options to resolve an issue that a product is having by providing information to a user. The specification’s disclosure on machine learning is nothing more than a high general explanation of generic technology and applying it to the abstract idea. Referring to MPEP § 2106.05(f), the generating the information using a generative AI model is merely being used to facilitate the tasks of the abstract idea, which provides nothing more than a results-oriented solution that lacks detail of the mechanism for accomplishing the result and is equivalent to the words “apply it,” per MPEP § 2106.05(f). The Examiner asserts that in light of the 2024 Guidance Update on Patent Subject Matter Eligibility, Including on Artificial Intelligence, the claimed invention is analogous to Example 47, Claim 2.
Further, the combination of these elements is nothing more than a generic computing system with AI. Because the additional elements are merely instructions to apply the abstract idea to a computer, as described in MPEP § 2106.05(f), they do not integrate the abstract idea into a practical application.
Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claims are directed to an abstract idea.
The remaining claims recite similar subject matter that has already been discussed above.
In summary, the dependent claims are simply directed towards providing additional descriptive factors that are considered for providing information to resolve an issue that a product is having. Accordingly, the claims are not patent eligible.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1 – 6, 8, 9, 11 – 16, 18 – 20 are rejected under 35 U.S.C. 103 as being unpatentable over Meyyappan et al. (US Patent 10,210,498 B1) in view of Patterson et al. (US PGPub 2022/0005083 A1).
In regards to claim 1, Meyyappan discloses an electronic device for automating home maintenance alerts and repair work, the electronic device comprising:
In regards to:
at least one memory; and
at least one processor in communication with the at least one memory, wherein the at least one processor is programmed to
(Fig. 1; Col. 15 Lines 7 – 41; Col. 15 – 16 Lines 57 – 28):
receive sensor data associated with an appliance, the data corresponding to a measurement of one or more aspects related to a functioning of the appliance (Col. 2 Lines 29 – 65; Col. 3 Lines 12 – 46; Col. 9 Lines 45 – 50 wherein data regarding the operation/performance/functioning of an appliance is received with the use of sensors);
apply the sensor data […] to output an identified issue causing the appliance to improperly function (Col. 2 Lines 29 – 65; Col. 3 Lines 35 – 46; Col. 9 Lines 45 – 50 wherein an issue causing the appliance to improperly function is determined by analyzing the received sensor data);
[…], identify a part for the appliance to address the improper functioning of the appliance (Col. 3 Lines 35 – 46; Col. 6 Lines 31 – 53; Col. 9 – 10 Lines 51 – 3 wherein a part to address the issue is identified);
generate and transmit an alert to a stakeholder device associated with a stakeholder of the appliance, the alert identifying a skill level associated with fixing the issue associated with the appliance and a description of the issue associated with the appliance (Col. 7 Lines 15 – 44; Col. 8 – 9 Lines 6 – 23, 56 – 3; Col. 10 Lines 14 – 25 wherein an alert is generated and transmitted to a user identifying, at least, a description of the appliance that is improperly functioning, the part identified to address the improper functioning of the appliance, and a skill level required to fix the issue associated with the appliance);
[…], generate and transmit one or more questions to the stakeholder device, the one or more questions related to fixing the issue and configured to facilitate assessing whether the stakeholder has the skill level to implement the fixing of the issue (Col. 8 – 9 Lines 17 – 3 “At 206, it is determined whether the service event is professional or DIY. In some embodiments, it is automatically determined whether the service event is either DIY or professional. For example, certain operational issues, such as replacing a light bulb or an easy-to-access filter may be automatically considered DIY due to their relative simplicity. Other operational issues may be automatically considered professional because they may require certain types of work to be performed by licensed professionals (e.g., plumbers or electricians), or because they require specialized tooling only available to professionals.
In some embodiments, the user can select whether the service event is professional or DIY. Upon receiving an alert 20 of the operational issue through the smart appliance payment application 122, the user may be prompted to select whether the user would like to pursue the DIY service event option or the professional service event option.
If at 206 the service event is determined, either automatically or based on a user selection, to be professional, at 208, service provider offers are presented to the user via the smart appliance payment application 122. As explained in further detail below, the service provider offers may be obtained via the service providers 128 and the services data 136 of the third-party computing systems 124. The service provider offers may be provided from multiple different service providers. The service provider offers may include various details, such as, for example, cost, availability, service provider location, customer reviews, promotional offers, etc. For example, the smart appliance payment system 116 may obtain customer ratings and reviews for service providers from websites such as Yelp™ or Angie's List™.
…
If at 206 the service event is determined, either automatically or based on a user selection, to be DIY, at 214, product offers are presented to the user via the smart appliance payment application 122. As explained in further detail 65 below, the product offers may be obtained via at least one of the manufacturers/OEMs 126 and the appliance data 134, and the merchants 130 and inventory data 138. The product offers may include various details, such as, for example, cost, availability, DIY instructions, customer reviews, promotional offers, etc.”);
in response to one or more inputs from the stakeholder responding to the one or more questions, generate recommendation including a proposed fix to be implemented by the stakeholder or a recommendation of a professional service provider to address the issue (Col. 8 – 9 Lines 17 – 3; Col. 10 Lines 4 – 25 wherein the user provides a response to the alert and recommendations are generated that include proposed fixes to address the issue;
“At 206, it is determined whether the service event is professional or DIY. In some embodiments, it is automatically determined whether the service event is either DIY or professional. For example, certain operational issues, such as replacing a light bulb or an easy-to-access filter may be automatically considered DIY due to their relative simplicity. Other operational issues may be automatically considered professional because they may require certain types of work to be performed by licensed professionals (e.g., plumbers or electricians), or because they require specialized tooling only available to professionals.
In some embodiments, the user can select whether the service event is professional or DIY. Upon receiving an alert 20 of the operational issue through the smart appliance payment application 122, the user may be prompted to select whether the user would like to pursue the DIY service event option or the professional service event option.
If at 206 the service event is determined, either automatically or based on a user selection, to be professional, at 208, service provider offers are presented to the user via the smart appliance payment application 122. As explained in further detail below, the service provider offers may be obtained via the service providers 128 and the services data 136 of the third-party computing systems 124. The service provider offers may be provided from multiple different service providers. The service provider offers may include various details, such as, for example, cost, availability, service provider location, customer reviews, promotional offers, etc. For example, the smart appliance payment system 116 may obtain customer ratings and reviews for service providers from websites such as Yelp™ or Angie's List™.
…
If at 206 the service event is determined, either automatically or based on a user selection, to be DIY, at 214, product offers are presented to the user via the smart appliance payment application 122. As explained in further detail 65 below, the product offers may be obtained via at least one of the manufacturers/OEMs 126 and the appliance data 134, and the merchants 130 and inventory data 138. The product offers may include various details, such as, for example, cost, availability, DIY instructions, customer reviews, promotional offers, etc.”); and
in response to an election by the stakeholder of one of the recommendations, generate additional outputs to address fixing the issue (Col. 8 – 9 Lines 17 – 3 wherein additional outputs are generated based on a response to the recommendation selected by the user, e.g., list of service providers or DIY related information, to address fixing the issue).
Meyyappan discloses a system and method for assisting a user with resolving appliance issues that can be resolved on their own (DIY) or by hiring a professional. Although Meyyappan discloses that the system analyzes a request and provides recommendations to a user, Meyyappan fails to explicitly disclose whether to use artificial intelligence (AI) models to assess the situation and provide a recommendation to resolve the situation.
To be more specific, Meyyappan fails to explicitly disclose:
apply the sensor data to an artificial intelligence (AI) model to output an identified issue causing the appliance to improperly function (Col. 2 Lines 29 – 65; Col. 3 Lines 35 – 46; Col. 9 Lines 45 – 50 wherein an issue causing the appliance to improperly function is determined by analyzing the received sensor data);
using the AI model, identify a part for the appliance to address the improper functioning of the appliance (Col. 3 Lines 35 – 46; Col. 6 Lines 31 – 53; Col. 9 – 10 Lines 51 – 3 wherein a part to address the issue is identified);
using the AI model, generate and transmit one or more questions to the stakeholder device, the one or more questions related to fixing the issue and configured to facilitate assessing whether the stakeholder has the skill level to implement the fixing of the issue
However, Patterson, which is also directed towards a system and method for evaluating and recommending a solution to an identified issue, as well as determining whether the resolution should be a DIY solution or a service provider provided solution, further teaches that it would have not only utilize a template of questions, but to also utilize machine learning models to evaluate and recommend a solution to an issue. Patterson teaches that machine learning models and receive issues that need to be diagnosed and generate questions to ask a customer, as well as generate questions based on received text. Patterson teaches that an advantage to incorporating machine learning is that if the template questions are not sufficient, the diagnostics system may use the machine learning model.
(For support see: Abstract; Fig. 7; ¶ 2, 3, 31, 32, 33, 35, 45, 46, 47, 49)
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to incorporate into the recommendation and resolution system and method of Meyyappan to incorporate artificial intelligence (AI) models to assist with evaluating and recommending a solution to an identified issue, as taught by Patterson, because template questions may not be enough to identify and resolve and issue and, accordingly, machine learning can evaluate received text and generate questions based on this text to facilitate resolution of the identified issue.
Further, one of ordinary skill in the art of analysis and recommendations systems and methods would have found it obvious to update the rule-based recommendation system and method of Meyyappan using modern electronic components, as taught in Patterson, in order to gain the commonly understood benefits of such adaptation, such as evaluating received text and generating questions based on the received text when a static knowledgebase or template of questions is insufficient for the particulars of an identified issue.
Accommodating the prior arts more manual and antiquated process with modern electronics, in this case, using artificial intelligence (AI) models, would have been obvious. As stated in Leapfrog, “applying modern electronics to older mechanical devices has been commonplace in recent years.”
In regards to claim 2, the combination of Meyyappan and Patterson discloses the electronic device of claim 1, wherein the at least one processor is further programmed to include an option in at least one of the recommendations comprising a mix of fixing the issue by the professional service provider and as a DIY project (Meyyappan – Col. 8 – 9 Lines 17 – 23 – 3 wherein the one or more recommendations include fixing the issue by a professional service provider or fixing the issue as a do-it-yourself (DIY) project; Patterson – ¶ 45 wherein the recommendation can include a DIY service, customer service agent support, remote technician support, or requires an onsite technician appointment.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to incorporate into the recommendation and resolution system and method of Meyyappan to incorporate artificial intelligence (AI) models to assist with evaluating and recommending a solution to an identified issue, as taught by Patterson, because template questions may not be enough to identify and resolve and issue and, accordingly, machine learning can evaluate received text and generate questions based on this text to facilitate resolution of the identified issue.
Further, one of ordinary skill in the art of analysis and recommendations systems and methods would have found it obvious to update the rule-based recommendation system and method of Meyyappan using modern electronic components, as taught in Patterson, in order to gain the commonly understood benefits of such adaptation, such as evaluating received text and generating questions based on the received text when a static knowledgebase or template of questions is insufficient for the particulars of an identified issue.
Accommodating the prior arts more manual and antiquated process with modern electronics, in this case, using artificial intelligence (AI) models, would have been obvious. As stated in Leapfrog, “applying modern electronics to older mechanical devices has been commonplace in recent years.”).
In regards to claim 3, the combination of Meyyappan and Patterson discloses the electronic device of claim 2, wherein:
the recommendation elected by the stakeholder includes fixing the issue by the professional service provider (Meyyappan – Col. 8 Lines 17 – 60 wherein the user selects a service provider to resolve the issue); and
In regards to:
the at least one processor is further programmed to:
generate a query for identifying a list of one or more professional service providers suitable to fix the issue, the query is generated based at least in part on the appliance identified as improperly functioning, or the part responsible for the improper functioning of the appliance; and
based upon a query response to the generated query, generate the list of one or more professional service providers suitable to fix the issue
(Meyyappan – Col. 8 Lines 17 – 60 wherein if the user elects to have a service provider resolve the issue, the system generates a prompt for the user to elect the service provider option and in response provides the user with a list of potential service providers to resolve the issue).
In regards to claim 4, the combination of Meyyappan and Patterson discloses the electronic device of claim 3, wherein the at least one processor is further programmed to:
In regards to:
generate a respective ranking score corresponding to each professional service provider on the list of one or more professional service providers based upon predetermined criteria, the predetermined criteria including at least one of a rating of each professional service provider, an experience level of each professional service provider, a charging rate of each professional service provider, or an availability of each professional service provider;
based upon the respective ranking score determined for each professional service provider on the list of one or more professional service providers, present a subset of professional service providers from the list of one or more professional service providers to the stakeholder ordered according to the respective ranking score of each professional service provider from the subset of professional service providers; and
receive information corresponding to one or more professional service providers selected by the stakeholder from the subset of professional service providers
(In light of ¶ 30 of the applicant’s specification, the ranking and list generation process is based on whether or not a particular service provider satisfies or exceeds a particular threshold.
With that said, Meyyappan – Col. 6 Lines 7 – 30 discloses that the system is in communication with a plurality of service providers, regardless of whether the service provider is available, capable of providing particular service capabilities, and etc. The system then transmits a query and receives a response from the service providers indicating whether they are, for example, capable or incapable of providing particular service capabilities. In other words, the system has access to a pool of service providers, filters those service providers according to specific parameters based on whether a service provider satisfies or exceeds a threshold (i.e. ranking score) and presents the list of the subset of service providers to a user to select from.;
Meyyappan – Col. 8 Lines 24 – 50 wherein the determination of service providers that are suitable to be presented on the list is based on, at least, pricing, availability, reviews, and/or experience level (i.e. capability)).
In regards to claim 5, the combination of Meyyappan and Patterson discloses the electronic device of claim 3, wherein the at least one processor is further programmed to contact and negotiate with a professional service provider for at least one of a quote or scheduling a date and a time to fix the issue (Meyyappan – Col. 6 Lines 7 – 30; Col. 8 Lines 24 – 50 wherein the system is in communication with service providers in order to receive cost and availability information to facilitate scheduling of a service).
In regards to claim 6, the combination of Meyyappan and Patterson discloses the electronic device of claim 2, wherein:
the recommendation elected by the stakeholder includes fixing the issue as a DIY project (Meyyappan – Col. 8 Lines 6 – 23; Col. 8 – 9 Lines 61 – 3 wherein the one or more recommendations include fixing the issue by a professional service provider or fixing the issue as a do-it-yourself (DIY) project); and
In regards to:
the at least one processor is further programmed to:
identify a list of instructional materials to fix the issue based upon at least in part the appliance identified as improperly functioning, the part associated with the improper functioning of the appliance, or the skill level
(Meyyappan – Col. 8 Lines 6 – 23; Col. 8 – 9 Lines 61 – 3 wherein the system identifies, generates, and provides, at least, DIY instructions to resolve the particular issue, cost, availability, part information, and etc. to the user).
In regards to claim 8, the combination of Meyyappan and Patterson discloses the electronic device of claim 2, wherein:
the recommendation elected by the stakeholder includes fixing the issue by the stakeholder as a DIY project (Meyyappan – Col. 8 Lines 6 – 23; Col. 8 – 9 Lines 61 – 3 wherein the one or more recommendations include fixing the issue by a professional service provider or fixing the issue as a do-it-yourself (DIY) project); and
In regards to:
the at least one processor is further programmed to:
identify a list of instructional materials to fix the issue including ordering a replacement part according to criteria including at least one of: a cost, availability, a delivery date, or a brand or a manufacturer of the replacement part (Meyyappan – Col. 8 Lines 6 – 23; Col. 8 – 9 Lines 61 – 9; Col. 9 – 10 Lines 51 – 3 wherein the system identifies, generates, and provides, at least, DIY instructions to resolve the particular issue, cost, availability, part information, and etc. to the user and the selected part is ordered).
In regards to claim 9, the combination of Meyyappan and Patterson discloses the electronic device of claim 2, wherein the at least one processor is further programmed to:
In regards to:
collect additional data relating to the improperly functioning appliance after the appliance has been fixed;
validate that the issue has been fixed; and
provide details corresponding to the fix, the details including at least one of: a description of one or more actions taken to fix the issue or warranty information associated with the fix
(Meyyappan – Col. 10 Lines 47 – 55 wherein additional information is collected upon completion of the service event to validate that the issue has been resolved based on details that include actions taken to resolve the issue, e.g., time it took to resolve the issue).
In regards to claim 11, Meyyappan discloses a computer-implemented method for for automating home maintenance alerts and repair work, the computer-implemented method implemented using a computing device including at least one processor and at least one memory, the computer-implemented method comprising:
receiving sensor data from an appliance or system, the sensor data corresponding to a measurement of one or more aspects related to the functioning of the appliance or system (Col. 2 Lines 29 – 65; Col. 3 Lines 12 – 46; Col. 9 Lines 45 – 50 wherein data regarding the operation/performance/functioning of an appliance is received with the use of sensors);
applying the sensor data [… ] to output an identified issue causing the appliance or system to improperly function (Col. 2 Lines 29 – 65; Col. 3 Lines 35 – 46; Col. 9 Lines 45 – 50 wherein an issue causing the appliance to improperly function is determined by analyzing the received sensor data);
[…], identifying a part associated with the improper functioning of the appliance or system (Col. 3 Lines 35 – 46; Col. 6 Lines 31 – 53; Col. 9 – 10 Lines 51 – 3 wherein a part to address the issue is identified);
generating and transmitting an alert to a stakeholder device associated with a stakeholder of the appliance or system, the alert identifying a skill level associated with fixing the issue associated with the appliance or system and a description of the issue associated with the appliance or system (Col. 7 Lines 15 – 44; Col. 8 – 9 Lines 6 – 23, 56 – 3; Col. 10 Lines 14 – 25 wherein an alert is generated and transmitted to a user identifying, at least, a description of the appliance that is improperly functioning, the part identified to address the improper functioning of the appliance, and a skill level required to fix the issue associated with the appliance);
[…], generating and transmitting one or more questions to the stakeholder device, the one or more questions related to fixing the issue and configured to facilitate assessing whether the stakeholder has the skill level to implement the fixing of the issue (Col. 8 – 9 Lines 17 – 3 “At 206, it is determined whether the service event is professional or DIY. In some embodiments, it is automatically determined whether the service event is either DIY or professional. For example, certain operational issues, such as replacing a light bulb or an easy-to-access filter may be automatically considered DIY due to their relative simplicity. Other operational issues may be automatically considered professional because they may require certain types of work to be performed by licensed professionals (e.g., plumbers or electricians), or because they require specialized tooling only available to professionals.
In some embodiments, the user can select whether the service event is professional or DIY. Upon receiving an alert 20 of the operational issue through the smart appliance payment application 122, the user may be prompted to select whether the user would like to pursue the DIY service event option or the professional service event option.
If at 206 the service event is determined, either automatically or based on a user selection, to be professional, at 208, service provider offers are presented to the user via the smart appliance payment application 122. As explained in further detail below, the service provider offers may be obtained via the service providers 128 and the services data 136 of the third-party computing systems 124. The service provider offers may be provided from multiple different service providers. The service provider offers may include various details, such as, for example, cost, availability, service provider location, customer reviews, promotional offers, etc. For example, the smart appliance payment system 116 may obtain customer ratings and reviews for service providers from websites such as Yelp™ or Angie's List™.
…
If at 206 the service event is determined, either automatically or based on a user selection, to be DIY, at 214, product offers are presented to the user via the smart appliance payment application 122. As explained in further detail 65 below, the product offers may be obtained via at least one of the manufacturers/OEMs 126 and the appliance data 134, and the merchants 130 and inventory data 138. The product offers may include various details, such as, for example, cost, availability, DIY instructions, customer reviews, promotional offers, etc.”);
in response to one or more inputs from the stakeholder responding to the one or more questions, generating a recommendation including a proposed fix to be implemented by the stakeholder or a recommendation of a professional service provider to address the issue (Col. 8 – 9 Lines 17 – 3; Col. 10 Lines 4 – 25 wherein the user provides a response to the alert and recommendations are generated that include proposed fixes to address the issue
“At 206, it is determined whether the service event is professional or DIY. In some embodiments, it is automatically determined whether the service event is either DIY or professional. For example, certain operational issues, such as replacing a light bulb or an easy-to-access filter may be automatically considered DIY due to their relative simplicity. Other operational issues may be automatically considered professional because they may require certain types of work to be performed by licensed professionals (e.g., plumbers or electricians), or because they require specialized tooling only available to professionals.
In some embodiments, the user can select whether the service event is professional or DIY. Upon receiving an alert 20 of the operational issue through the smart appliance payment application 122, the user may be prompted to select whether the user would like to pursue the DIY service event option or the professional service event option.
If at 206 the service event is determined, either automatically or based on a user selection, to be professional, at 208, service provider offers are presented to the user via the smart appliance payment application 122. As explained in further detail below, the service provider offers may be obtained via the service providers 128 and the services data 136 of the third-party computing systems 124. The service provider offers may be provided from multiple different service providers. The service provider offers may include various details, such as, for example, cost, availability, service provider location, customer reviews, promotional offers, etc. For example, the smart appliance payment system 116 may obtain customer ratings and reviews for service providers from websites such as Yelp™ or Angie's List™.
…
If at 206 the service event is determined, either automatically or based on a user selection, to be DIY, at 214, product offers are presented to the user via the smart appliance payment application 122. As explained in further detail 65 below, the product offers may be obtained via at least one of the manufacturers/OEMs 126 and the appliance data 134, and the merchants 130 and inventory data 138. The product offers may include various details, such as, for example, cost, availability, DIY instructions, customer reviews, promotional offers, etc.”); and
in response to an election by the stakeholder of one of the recommendations, performing additional steps to facilitate fixing the improperly functioning appliance or system (Col. 8 – 9 Lines 17 – 3 wherein additional outputs are generated based on a response to the recommendation selected by the user, e.g., list of service providers or DIY related information, to facilitate fixing the issue).
Meyyappan discloses a system and method for assisting a user with resolving appliance issues that can be resolved on their own (DIY) or by hiring a professional. Although Meyyappan discloses that the system analyzes a request and provides recommendations to a user, Meyyappan fails to explicitly disclose whether to use artificial intelligence (AI) models to assess the situation and provide a recommendation to resolve the situation.
To be more specific, Meyyappan fails to explicitly disclose:
applying the sensor data to an artificial intelligence (AI) model to output an identified issue causing the appliance or system to improperly function
using the AI model, identifying a part associated with the improper functioning of the appliance or system
using the AI model, generating and transmitting one or more questions to the stakeholder device, the one or more questions related to fixing the issue and configured to facilitate assessing whether the stakeholder has the skill level to implement the fixing of the issue
However, Patterson, which is also directed towards a system and method for evaluating and recommending a solution to an identified issue, as well as determining whether the resolution should be a DIY solution or a service provider provided solution, further teaches that it would have not only utilize a template of questions, but to also utilize machine learning models to evaluate and recommend a solution to an issue. Patterson teaches that machine learning models and receive issues that need to be diagnosed and generate questions to ask a customer, as well as generate questions based on received text. Patterson teaches that an advantage to incorporating machine learning is that if the template questions are not sufficient, the diagnostics system may use the machine learning model.
(For support see: Abstract; Fig. 7; ¶ 2, 3, 31, 32, 33, 35, 45, 46, 47, 49)
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to incorporate into the recommendation and resolution system and method of Meyyappan to incorporate artificial intelligence (AI) models to assist with evaluating and recommending a solution to an identified issue, as taught by Patterson, because template questions may not be enough to identify and resolve and issue and, accordingly, machine learning can evaluate received text and generate questions based on this text to facilitate resolution of the identified issue.
Further, one of ordinary skill in the art of analysis and recommendations systems and methods would have found it obvious to update the rule-based recommendation system and method of Meyyappan using modern electronic components, as taught in Patterson, in order to gain the commonly understood benefits of such adaptation, such as evaluating received text and generating questions based on the received text when a static knowledgebase or template of questions is insufficient for the particulars of an identified issue.
Accommodating the prior arts more manual and antiquated process with modern electronics, in this case, using artificial intelligence (AI) models, would have been obvious. As stated in Leapfrog, “applying modern electronics to older mechanical devices has been commonplace in recent years.”
In regards to claim 12, the combination of Meyyappan and Patterson discloses the computer-implemented method of claim 11, further comprising including an option in at least one of the recommendations comprising a mix of fixing the improperly functioning appliance or system by the professional service provider and by the stakeholder as a DIY project (Meyyappan – Col. 8 – 9 Lines 17 – 23 – 3 wherein the one or more recommendations include fixing the issue by a professional service provider or fixing the issue as a do-it-yourself (DIY) project; Patterson – ¶ 45 wherein the recommendation can include a DIY service, customer service agent support, remote technician support, or requires an onsite technician appointment.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to incorporate into the recommendation and resolution system and method of Meyyappan to incorporate artificial intelligence (AI) models to assist with evaluating and recommending a solution to an identified issue, as taught by Patterson, because template questions may not be enough to identify and resolve and issue and, accordingly, machine learning can evaluate received text and generate questions based on this text to facilitate resolution of the identified issue.
Further, one of ordinary skill in the art of analysis and recommendations systems and methods would have found it obvious to update the rule-based recommendation system and method of Meyyappan using modern electronic components, as taught in Patterson, in order to gain the commonly understood benefits of such adaptation, such as evaluating received text and generating questions based on the received text when a static knowledgebase or template of questions is insufficient for the particulars of an identified issue.
Accommodating the prior arts more manual and antiquated process with modern electronics, in this case, using artificial intelligence (AI) models, would have been obvious. As stated in Leapfrog, “applying modern electronics to older mechanical devices has been commonplace in recent years.”).
In regards to claim 13, the combination of Meyyappan and Patterson discloses the computer-implemented method of claim 12, wherein the recommendation elected by the stakeholder includes fixing the improperly functioning appliance or system by the professional service provider, and wherein the performing of the additional steps further comprises (Meyyappan – Col. 8 Lines 17 – 60 wherein the user selects a service provider to resolve the issue):
In regards to:
generating a query for identifying a list of one or more professional service providers suitable to fix the improperly functioning appliance or system, the query is generated based upon at least in part the appliance or system identified as improperly functioning, or the part associated with the improperly functioning appliance or system; and
based upon a query response to the generated query, generating the list of one or more professional service providers suitable to fix the improperly functioning appliance or system
(Meyyappan – Col. 8 Lines 17 – 60 wherein if the user elects to have a service provider resolve the issue, the system generates a prompt for the user to elect the service provider option and in response provides the user with a list of potential service providers to resolve the issue).
In regards to claim 14, the combination of Meyyappan and Patterson discloses the computer-implemented method of claim 13, wherein the performing additional steps further comprises:
In regards to:
generating a respective ranking score corresponding to each professional service provider in the list of one or more professional service providers based upon predetermined criteria, the predetermined criteria including at least one of a rating of each professional service provider, an experience level of each professional service provider, a charging rate of each professional service provider, or availability of each professional service provider;
based upon the respective ranking score determined for each professional service provider in the list of one or more professional service providers, presenting a subset of professional service providers from the list of one or more professional service providers to the stakeholder ordered by the respective ranking score of each professional service provider from the subset of professional service providers; and
receiving information corresponding to one or more professional service providers selected by the stakeholder from the subset of professional service providers
(In light of ¶ 30 of the applicant’s specification, the ranking and list generation process is based on whether or not a particular service provider satisfies or exceeds a particular threshold.
With that said, Meyyappan – Col. 6 Lines 7 – 30 discloses that the system is in communication with a plurality of service providers, regardless of whether the service provider is available, capable of providing particular service capabilities, and etc. The system then transmits a query and receives a response from the service providers indicating whether they are, for example, capable or incapable of providing particular service capabilities. In other words, the system has access to a pool of service providers, filters those service providers according to specific parameters based on whether a service provider satisfies or exceeds a threshold (i.e. ranking score) and presents the list of the subset of service providers to a user to select from.;
Meyyappan – Col. 8 Lines 24 – 50 wherein the determination of service providers that are suitable to be presented on the list is based on, at least, pricing, availability, reviews, and/or experience level (i.e. capability)).
In regards to claim 15, the combination of Meyyappan and Patterson discloses the computer-implemented method of claim 13, wherein the performing additional steps further comprises contacting and negotiating with a professional service provider for at least one of a quote or scheduling a date and a time to fix the improperly functioning appliance or system (Meyyappan – Col. 6 Lines 7 – 30; Col. 8 Lines 24 – 50 wherein the system is in communication with service providers in order to receive cost and availability information to facilitate scheduling of a service).
In regards to claim 16, the combination of Meyyappan and Patterson discloses the computer-implemented method of claim 12, wherein the recommendation elected by the stakeholder includes fixing the improperly functioning appliance or system as a DIY project, and wherein the performing the additional steps further comprises (Meyyappan – Col. 8 Lines 6 – 23; Col. 8 – 9 Lines 61 – 3 wherein the one or more recommendations include fixing the issue by a professional service provider or fixing the issue as a do-it-yourself (DIY) project):
based upon at least (i) the appliance being identified as improperly functioning, (ii) the part associated with the improperly functioning appliance or system, or (iii) skill level, identifying a list of instructional materials to facilitate fixing the improperly functioning appliance or system (Meyyappan – Col. 8 Lines 6 – 23; Col. 8 – 9 Lines 61 – 3 wherein the system identifies, generates, and provides, at least, DIY instructions to resolve the particular issue, cost, availability, part information, and etc. to the user).
In regards to claim 18, the combination of Meyyappan and Patterson discloses the computer-implemented method of claim 16, wherein the performing additional steps further comprises ordering a replacement part to address the improperly functioning appliance or system based upon criteria that includes at least one of: a cost, availability, a delivery date, or a brand or a manufacturer of the replacement part (Meyyappan – Col. 8 Lines 6 – 23; Col. 8 – 9 Lines 61 – 9; Col. 9 – 10 Lines 51 – 3 wherein the system identifies, generates, and provides, at least, DIY instructions to resolve the particular issue, cost, availability, part information, and etc. to the user and the selected part is ordered).
In regards to claim 19, the combination of Meyyappan and Patterson discloses the computer-implemented method of claim 11, further comprising:
based upon the sensor data, identifying that the appliance or system requires maintenance in addition to the appliance or the system functioning improperly (Meyyappan – Col. 3 Lines 35 – 46; Col. 6 Lines 31 – 53; Col. 9 – 10 Lines 51 – 3 wherein a part to address the issue is identified, which results in the appliance requiring maintenance); and
generating and transmitting a notification to the stakeholder, the notification including a description of the maintenance (Meyyappan – Col. 8 – 9 Lines 6 – 23, 56 – 3; Col. 10 Lines 14 – 25 wherein an alert is generated and transmitted to a user identifying, at least, a description of the appliance that is improperly functioning, the part identified to address the improper functioning of the appliance, and a skill level required to fix the issue associated with the appliance).
In regards to claim 20, Meyyappan discloses at least one non-transitory computer-readable storage media having computer-executable instructions embodied thereon for automating home maintenance alerts and repair work, wherein when executed by a computing device including at least one processor and at least one memory device, the computer-executable instructions cause the at least one processor to:
receive sensor data corresponding to an issue related to an appliance or system, the sensor data including at least one of: audio data, video data, or text data (Col. 2 Lines 29 – 65; Col. 3 Lines 12 – 46; Col. 6 Lines 31 – 53; Col. 9 – 10 Lines 45 – 3 wherein data regarding the operation/performance/functioning of an appliance is received with the use of sensors, wherein the data further includes information about the particulars of the appliances and stores the information to identify an issue based on operational parameters monitored over time to assist with diagnosing a root, e.g., identify the particular component that is broken that so that the system can inform a user of the component that needs to be ordered. This also allows for users to access the appliance direction to further assist with the identification of an issue.; Col. 8 – 9 Lines 6 – 23, 56 – 3; Col. 10 Lines 14 – 25 wherein an alert is generated and transmitted to a user identifying, at least, a description of the appliance that is improperly functioning, the part identified to address the improper functioning of the appliance, and a skill level required to fix the issue associated with the appliance. In other words, the stored and transmitted data is at least one of audio, video, or text.);
apply the sensor data to an […] to output an identified issue causing the appliance or system to improperly function (Col. 2 Lines 29 – 65; Col. 3 Lines 35 – 46; Col. 9 Lines 45 – 50 wherein an issue causing the appliance to improperly function is determined by analyzing the received sensor data);
[…], identify a part associated with the improperly functioning appliance or system that requires replacing or repairing (Col. 3 Lines 35 – 46; Col. 6 Lines 31 – 53; Col. 9 – 10 Lines 51 – 3 wherein a part to address the issue is identified; Col. 8 – 9 Lines 6 – 23, 56 – 3; Col. 10 Lines 14 – 25 wherein an alert is generated and transmitted to a user identifying, at least, a description of the appliance that is improperly functioning, the part identified to address the improper functioning of the appliance, and a skill level required to fix the issue associated with the appliance);
[…], generate and transmit one or more questions to a stakeholder device associated with a stakeholder of the appliance or system, the one or more questions related to fixing the issue and configured to facilitate assessing whether the stakeholder has a skill level to implement the fixing of the issue (Col. 8 – 9 Lines 17 – 3 “At 206, it is determined whether the service event is professional or DIY. In some embodiments, it is automatically determined whether the service event is either DIY or professional. For example, certain operational issues, such as replacing a light bulb or an easy-to-access filter may be automatically considered DIY due to their relative simplicity. Other operational issues may be automatically considered professional because they may require certain types of work to be performed by licensed professionals (e.g., plumbers or electricians), or because they require specialized tooling only available to professionals.
In some embodiments, the user can select whether the service event is professional or DIY. Upon receiving an alert 20 of the operational issue through the smart appliance payment application 122, the user may be prompted to select whether the user would like to pursue the DIY service event option or the professional service event option.
If at 206 the service event is determined, either automatically or based on a user selection, to be professional, at 208, service provider offers are presented to the user via the smart appliance payment application 122. As explained in further detail below, the service provider offers may be obtained via the service providers 128 and the services data 136 of the third-party computing systems 124. The service provider offers may be provided from multiple different service providers. The service provider offers may include various details, such as, for example, cost, availability, service provider location, customer reviews, promotional offers, etc. For example, the smart appliance payment system 116 may obtain customer ratings and reviews for service providers from websites such as Yelp™ or Angie's List™.
…
If at 206 the service event is determined, either automatically or based on a user selection, to be DIY, at 214, product offers are presented to the user via the smart appliance payment application 122. As explained in further detail 65 below, the product offers may be obtained via at least one of the manufacturers/OEMs 126 and the appliance data 134, and the merchants 130 and inventory data 138. The product offers may include various details, such as, for example, cost, availability, DIY instructions, customer reviews, promotional offers, etc.”);
based upon one or more inputs from the stakeholder responding to the one or more questions, generate a recommendation including a proposed fix to be implemented by the stakeholder or a recommendation of a professional service provider to address the issue (Col. 8 – 9 Lines 17 – 23 – 3; Col. 10 Lines 4 – 25 wherein the user provides a response to the alert and recommendations are generated and presented to a user that include proposed fixes to address the issue
“At 206, it is determined whether the service event is professional or DIY. In some embodiments, it is automatically determined whether the service event is either DIY or professional. For example, certain operational issues, such as replacing a light bulb or an easy-to-access filter may be automatically considered DIY due to their relative simplicity. Other operational issues may be automatically considered professional because they may require certain types of work to be performed by licensed professionals (e.g., plumbers or electricians), or because they require specialized tooling only available to professionals.
In some embodiments, the user can select whether the service event is professional or DIY. Upon receiving an alert 20 of the operational issue through the smart appliance payment application 122, the user may be prompted to select whether the user would like to pursue the DIY service event option or the professional service event option.
If at 206 the service event is determined, either automatically or based on a user selection, to be professional, at 208, service provider offers are presented to the user via the smart appliance payment application 122. As explained in further detail below, the service provider offers may be obtained via the service providers 128 and the services data 136 of the third-party computing systems 124. The service provider offers may be provided from multiple different service providers. The service provider offers may include various details, such as, for example, cost, availability, service provider location, customer reviews, promotional offers, etc. For example, the smart appliance payment system 116 may obtain customer ratings and reviews for service providers from websites such as Yelp™ or Angie's List™.
…
If at 206 the service event is determined, either automatically or based on a user selection, to be DIY, at 214, product offers are presented to the user via the smart appliance payment application 122. As explained in further detail 65 below, the product offers may be obtained via at least one of the manufacturers/OEMs 126 and the appliance data 134, and the merchants 130 and inventory data 138. The product offers may include various details, such as, for example, cost, availability, DIY instructions, customer reviews, promotional offers, etc.”); and
in response to an election by the stakeholder of one of the recommendations, provide additional information to facilitate fixing the issue with the improperly functioning appliance or system (Col. 8 – 9 Lines 17 – 3 wherein additional outputs are generated based on a response to the recommendation selected by the user, e.g., list of service providers or DIY related information, to facilitate fixing the issue).
Meyyappan discloses a system and method for assisting a user with resolving appliance issues that can be resolved on their own (DIY) or by hiring a professional. Although Meyyappan discloses that the system analyzes a request and provides recommendations to a user, Meyyappan fails to explicitly disclose whether to use artificial intelligence (AI) models to assess the situation and provide a recommendation to resolve the situation.
To be more specific, Meyyappan fails to explicitly disclose:
apply the sensor data to an artificial intelligence (AI) model to output an identified issue causing the appliance or system to improperly function
using the AI model, identify a part associated with the improperly functioning appliance or system that requires replacing or repairing
using the AI model, generate and transmit one or more questions to a stakeholder device associated with a stakeholder of the appliance or system, the one or more questions related to fixing the issue and configured to facilitate assessing whether the stakeholder has a skill level to implement the fixing of the issue
However, Patterson, which is also directed towards a system and method for evaluating and recommending a solution to an identified issue, as well as determining whether the resolution should be a DIY solution or a service provider provided solution, further teaches that it would have not only utilize a template of questions, but to also utilize machine learning models to evaluate and recommend a solution to an issue. Patterson teaches that machine learning models and receive issues that need to be diagnosed and generate questions to ask a customer, as well as generate questions based on received text. Patterson teaches that an advantage to incorporating machine learning is that if the template questions are not sufficient, the diagnostics system may use the machine learning model.
(For support see: Abstract; Fig. 7; ¶ 2, 3, 31, 32, 33, 35, 45, 46, 47, 49)
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to incorporate into the recommendation and resolution system and method of Meyyappan to incorporate artificial intelligence (AI) models to assist with evaluating and recommending a solution to an identified issue, as taught by Patterson, because template questions may not be enough to identify and resolve and issue and, accordingly, machine learning can evaluate received text and generate questions based on this text to facilitate resolution of the identified issue.
Further, one of ordinary skill in the art of analysis and recommendations systems and methods would have found it obvious to update the rule-based recommendation system and method of Meyyappan using modern electronic components, as taught in Patterson, in order to gain the commonly understood benefits of such adaptation, such as evaluating received text and generating questions based on the received text when a static knowledgebase or template of questions is insufficient for the particulars of an identified issue.
Accommodating the prior arts more manual and antiquated process with modern electronics, in this case, using artificial intelligence (AI) models, would have been obvious. As stated in Leapfrog, “applying modern electronics to older mechanical devices has been commonplace in recent years.”
______________________________________________________________________
Claims 7, 17 are rejected under 35 U.S.C. 103 as being unpatentable over Meyyappan et al. (US Patent 10,210,498 B1) in view of Patterson et al. (US PGPub 2022/0005083 A1) in further view of Window World (Should You DIY or Hire a Home Contractor).
In regards to claim 7, the combination of Meyyappan and Patterson discloses the electronic device of claim 2, wherein:
the recommendation elected by the stakeholder includes fixing the issue by the stakeholder as a DIY project (Col. 8 Lines 6 – 23; Col. 8 – 9 Lines 61 – 3 wherein the one or more recommendations include fixing the issue by a professional service provider or fixing the issue as a do-it-yourself (DIY) project); and
In regards to:
the at least one processor is further programmed to:
identify a list of instructional materials to fix the issue including: generate a […] of a cost of resources required to fix the issue by the professional service provider with a cost of resources required to fix the issue as a DIY project; and
present the generated [selected recommendation] to the stakeholder
(Col. 8 Lines 6 – 23; Col. 8 – 9 Lines 61 – 3 wherein the system identifies, generates, and provides, at least, DIY instructions, cost, availability, part information, and etc. to the user).
The combination of Meyyappan and Patterson discloses a system and method for assisting a user with resolving appliance issues that can be resolved on their own (DIY) or by hiring a professional. the combination of Meyyappan and Patterson discloses that the system provides information for both options when an option is selected, but fails to disclose whether it would have been obvious to provide the information together to allow a user to determine which option to go with.
To be more specific, the combination of Meyyappan and Patterson fails to explicitly disclose:
identify a list of instructional materials to fix the issue including: generate a comparison of a cost of resources required to fix the issue by the professional service provider with a cost of resources required to fix the issue as a DIY project; and
present the generated comparison to the stakeholder.
However, Window World, which is a service provider that provides window replacement services, teaches that it would have been obvious to one of ordinary skill in the art for a service provider to provide users with factors that must be considered when determining whether to take on a project on their own (DIY) or by hiring a service provider as material that can be provided together. Window World teaches that providing cost information if a project is done by a user or by a professional, as well as other factors, allows a user to determine which option is best for them.
The combination of Meyyappan and Patterson already discloses that factors that a user can consider when choosing a DIY option or service provider option are known to be provided to a user, but fails to disclose whether such considerations could be provided simultaneously to allow a user to consider and weigh each option before making a selection. Accordingly, one of ordinary skill in the art would have been motivated to look to Window World because Window World, who is a service provider, teaches that providing the pros and cons of each option upfront allows a user to be more educated before determining how to tackle a project. Window World teaches that there are various types of projects that each have an associated cost for performing the project by the customer or by a professional. Similar to the combination of Meyyappan and Patterson, which discloses that installing a light bulb or changing a filter can be performed by the customer whereas other projects may be more complex and require specialized tooling only available to professionals (Col. 8 Lines 6 – 16),
Window World explicitly teaches, for example, that tool and material acquisition and time to do the project (assuming that the user gets it right the first time) can be more costly and that paying a professional may be cheaper in the long run. Window World provides numerous examples, some similar to the combination of Meyyappan and Patterson, where the cost to perform the project is simply the components of the project or minimal cost expenses for the tools/materials to perform the project (e.g., painting only requires paint (component of the project), paint brushes, painter’s tape (if one chooses to), floor protection (if one chooses to), and sandpaper (if needed), which would be cheaper than hiring a professional; simple upgrades which can be as simple as replacing drawer hardware and cheaper than hiring a professional; versus professional work that would require specialized equipment).
Window World provides information regarding the pros and cons, factors to consider, cost considerations, and etc. upfront rather than after a user makes a decision. One of ordinary skill in the art would have been motivated to modify the system and method of the combination of Meyyappan and Patterson, which provides such considerations and other useful information after the user has made a selection, to provide such valuable information before a user makes a decision as this allows a user to be better educated before a poor and costly decision is elected, thereby providing cost and time savings for the user.
(Pages 1 – 8)
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify the DIY or service provider selection process in the system and method of the combination of Meyyappan and Patterson to provide information regarding what a particular job will entail before a user makes a selection of whether to perform a project on their own or deciding to hire a professional, as taught by Window World, as this can result in cost savings, time savings, and preventing a user from choosing to perform a project that results in being bigger and more costly than they thought or choosing a professional and paying more for a job that would have been cheaper and within their capabilities. Window World discloses that providing information regarding these considerations upfront before a user makes a selection can save the user time, money, and stress.
In regards to claim 17, the combination of Meyyappan and Patterson discloses the computer-implemented method of claim 16, wherein the performing additional steps further comprises:
In regards to:
generating a […] of a cost of resources required to fix the improperly functioning appliance or system by the professional service provider with a cost of resources required to fix the improperly functioning appliance or system as a DIY project; and
presenting to the stakeholder the generated [selected recommendation]
(Col. 8 Lines 6 – 23; Col. 8 – 9 Lines 61 – 3 wherein the system identifies, generates, and provides, at least, DIY instructions, cost, availability, part information, and etc. to the user).
The combination of Meyyappan and Patterson discloses a system and method for assisting a user with resolving appliance issues that can be resolved on their own (DIY) or by hiring a professional. The combination of Meyyappan and Patterson discloses that the system provides information for both options when an option is selected, but fails to disclose whether it would have been obvious to provide the information together to allow a user to determine which option to go with.
To be more specific, the combination of Meyyappan and Patterson fails to explicitly disclose:
generating a comparison of a cost of resources required to fix the improperly functioning appliance or system by the professional service provider with a cost of resources required to fix the improperly functioning appliance or system as a DIY project; and
presenting to the stakeholder the generated comparison
However, Window World, which is a service provider that provides window replacement services, teaches that it would have been obvious to one of ordinary skill in the art for a service provider to provide users with factors that must be considered when determining whether to take on a project on their own (DIY) or by hiring a service provider as material that can be provided together. Window World teaches that providing cost information if a project is done by a user or by a professional, as well as other factors, allows a user to determine which option is best for them.
The combination of Meyyappan and Patterson already discloses that factors that a user can consider when choosing a DIY option or service provider option are known to be provided to a user, but fails to disclose whether such considerations could be provided simultaneously to allow a user to consider and weigh each option before making a selection. Accordingly, one of ordinary skill in the art would have been motivated to look to Window World because Window World, who is a service provider, teaches that providing the pros and cons of each option upfront allows a user to be more educated before determining how to tackle a project. Window World teaches that there are various types of projects that each have an associated cost for performing the project by the customer or by a professional. Similar to the combination of Meyyappan and Patterson, which discloses that installing a light bulb or changing a filter can be performed by the customer whereas other projects may be more complex and require specialized tooling only available to professionals (Col. 8 Lines 6 – 16),
Window World explicitly teaches, for example, that tool and material acquisition and time to do the project (assuming that the user gets it right the first time) can be more costly and that paying a professional may be cheaper in the long run. Window World provides numerous examples, some similar to the combination of Meyyappan and Patterson, where the cost to perform the project is simply the components of the project or minimal cost expenses for the tools/materials to perform the project (e.g., painting only requires paint (component of the project), paint brushes, painter’s tape (if one chooses to), floor protection (if one chooses to), and sandpaper (if needed), which would be cheaper than hiring a professional; simple upgrades which can be as simple as replacing drawer hardware and cheaper than hiring a professional; versus professional work that would require specialized equipment).
Window World provides information regarding the pros and cons, factors to consider, cost considerations, and etc. upfront rather than after a user makes a decision. One of ordinary skill in the art would have been motivated to modify the system and method of the combination of Meyyappan and Patterson, which provides such considerations and other useful information after the user has made a selection, to provide such valuable information before a user makes a decision as this allows a user to be better educated before a poor and costly decision is elected, thereby providing cost and time savings for the user.
(Pages 1 – 8)
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify the DIY or service provider selection process in the system and method of the combination of Meyyappan and Patterson to provide information regarding what a particular job will entail before a user makes a selection of whether to perform a project on their own or deciding to hire a professional, as taught by Window World, as this can result in cost savings, time savings, and preventing a user from choosing to perform a project that results in being bigger and more costly than they thought or choosing a professional and paying more for a job that would have been cheaper and within their capabilities. Window World discloses that providing information regarding these considerations upfront before a user makes a selection can save the user time, money, and stress.
______________________________________________________________________
Claim 10 is rejected under 35 U.S.C. 103 as being unpatentable over Meyyappan et al. (US Patent 10,210,498 B1) in view of Patterson et al. (US PGPub 2022/0005083 A1) in further view of Nield (Here’s how to use ChatGPT in your everyday life).
In regards to claim 10, the combination of Meyyappan and Patterson discloses a system and method for assisting a user with resolving appliance issues that can be resolved on their own (DIY) or by hiring a professional utilizing AI. Although the combination of Meyyappan and Patterson discloses that the system analyzes a request and provides recommendations to a user utilizing AI, the combination of Meyyappan and Patterson fails to explicitly disclose whether to use generative artificial intelligence (AI) models to perform these actions.
To be more specific, the combination of Meyyappan and Patterson fails to explicitly disclose:
the electronic device of claim 1, wherein the AI model comprises a generative AI model.
However, Nield teaches that generative artificial intelligence (AI) models, such as ChatGPT, can be used for a wide range of scenarios, such as, but not including, providing recommendations and advice. Nield teaches, “Obviously, ChatGPT won’t know the intricacies of your own situation, but it can generate a list of considerations to weigh up, some of which you might not otherwise have thought about. We wouldn’t recommend living your life entirely based on ChatGPT’s opinions, but it can still be helpful if you don’t know where to start tackling a particular problem.”
(Pages 1 – 6)
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to incorporate into the AI-based recommendation and resolution system and method of the combination of Meyyappan and Patterson to incorporate generative artificial intelligence (AI) models, such as ChatGPT, as taught by Nield, as this can assist a user with a problem they are facing and can be presented with considerations they may not have thought about.
Further, one of ordinary skill in the art of analysis and recommendations systems and methods would have found it obvious to update the AI based recommendation system and method of the combination of Meyyappan and Patterson using modern electronic components, as taught in Nield, in order to gain the commonly understood benefits of such adaptation, such as an increase knowledge base of information that results in providing additional information that a user may not have considered.
Accommodating the prior arts more manual and antiquated process with modern electronics, in this case, using generative artificial intelligence (AI) models, such as ChatGPT, would have been obvious. As stated in Leapfrog, “applying modern electronics to older mechanical devices has been commonplace in recent years.”
Response to Arguments
Applicant's arguments filed 4/6/2026 have been fully considered but they are not persuasive.
Claim Objections
The claim objections have been withdrawn due to amendments.
A new claim objection has been provided due to amendments.
Rejection under 35 USC 101
The rejection under 35 USC 101 has been maintained.
The Examiner asserts that the claimed invention does not improve upon artificial intelligence, resolve an issue that arose in artificial intelligence, nor is it deeply rooted in artificial intelligence. The claimed invention recites artificial intelligence at a high level of generality and applies it to the abstract idea. Additionally, the claimed invention and specification do not contend that the applicant invented, improved, or the created artificial intelligence, but that generic machine learning models are being applied to the abstract idea (See ¶ 6, 25, 33, 35, 48, 60, 94 of the applicant’s specification). The claimed invention and specification are not directed towards artificial intelligence, but directed towards product maintenance assistance, which corresponds to “Mental Processes” and “Certain Methods of Organizing Human Activities” as it is directed towards steps that can be performed by a human(s), in the human mind, and/or with the aid of pen and paper, e.g., having a consumer contact a service provider to be provided with information to address an issue that the consumer is having with their product based on symptoms the product is having. The invention corresponds to “Mental Processes” because it is directed towards the collection and comparison of information and, based a rule, identify options, in this case, collecting product related information, comparing the information to known information, and, based on a rule(s), identify and provide information to resolve an issue, which are steps that can be performed by a huma in their mind and/or with the aid of pen and paper. The invention also corresponds to “Certain Methods of Organizing Human Activities” because it encompasses a commercial interaction between a consumer and service provider (or the like) to resolve a product issue and/or managing interactions between peoples, in this case, a service provider (or the like) providing a recommendation (teaching) to the consumer to resolve an issue.
Rejections under 35 USC 102/103
The Examiner asserts that the applicant’s arguments are directed towards newly amended limitations and are, therefore, considered moot. However, the Examiner has responded to the newly submitted amendments, which the arguments are directed to, in the rejection above, thereby addressing the applicant’s arguments.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure can be found in the attached PTO-892 Notice of References Cited.
Williams et al. (US Patent 12,548,095 B2); Harvey et al. (US Patent 12,516,781 B2); Matsuoka et al. (US PGPub 2025/0363541 A1) – which disclose the use of machine learning/artificial intelligence to assist with diagnosing and resolving asset issues
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) 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 mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to GERARDO ARAQUE JR whose telephone number is (571)272-3747. The examiner can normally be reached Monday - Friday 8-4:30.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Sarah Monfeldt can be reached at 571-270-1833. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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GERARDO ARAQUE JR
Primary Examiner
Art Unit 3629
/GERARDO ARAQUE JR/Primary Examiner, Art Unit 3629 4/9/2026
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