DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Arguments
Applicant's arguments filed 1/21/2026 have been fully considered but they are not persuasive.
Claims 1, 3-7, and 9-12 are directed to an invention that is independent or distinct from the invention originally claimed for the following reasons:
For at least, previously independent claims 1, 11 and 12 were previously directed toward an insurance claim reviewing system on an insurance benefit from insurance with respect to an incident and approving the claim when a predicted probability of occurrence of the incident is lower than or equal to a predetermined value.
The same independent claims 1, 11 and 12 as now amended and presented are directed toward:
A system and method for “determine[ing], based at least in part on the determination that an operable device is at least partially inoperable, whether the operable device is at least partially inoperable due to a malfunction having a likelihood of occurrence, wherein the likelihood of occurrence of the malfunction is calculated based at least in part on one or more of a type of the operable device, a usage rate of the operable device, an operational environment of the operable device, a maintenance status of the operable device, or a failure rate of the operable device, and in response to determining that the operable device is at least partially inoperable due to the malfunction having the likelihood of occurrence, in response to determining that the likelihood of occurrence of the malfunction is less than or equal to the predetermined threshold likelihood of occurrence of the malfunction, approve the execution of the conditional interaction with respect to the operable device, and execute, based at least in part on the approval, the conditional interaction with respect to the operable device to satisfy the request.
The previous independent claims have different scope than the claims as now presented, and would require new consideration and a burden on the Examiner for examination purpose.
Since applicant has received an action on the merits for the originally presented invention, this invention has been constructively elected by original presentation for prosecution on the merits. Accordingly, the claims as now presented are withdrawn from consideration. See 37 CFR 1.142(b) and MPEP § 821.03.
The prior Office action remains outstanding and is repeated below.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1-13 is/are rejected under 35 U.S.C. 103 as being unpatentable over Matsumoto et al (JP-2005190271-A) in view of Fuchs et al (US-20160189303-A1).
As per claims 1, 11 and 12, Matsumoto et al teach/disclose a system and method for
insuring a factory or power plant in case of an incident or disaster, as Matsumoto et al state:
“The plant maintenance and the insurance contract system involves: conducting operation for an exact plant risk inherent in each plant of the plant owner 12 by a plant maker 11; calculating an insurance premium based on data on the plant risk by a nonlife insurance company 13; and meanwhile, sending data on the latest operation history, or the like to the plant maker 11 by the plant owner 12 to update, one by one, data on a database, establishing the rational low-cost insurance premium”.
Matsumoto et al do not explicitly state “approve a claim when a predicted probability of occurrence of an incident is lower than or equal to a predetermined value”.
In approving a claim, it is essential to establish the validity of the claim based on some attributes or parameters or threshold.
Fuchs et al teach a system and method for insuring a driver of a vehicle and determines claim approval based on road traveled and the conditions of the road traveled among many parameters.
Fuchs et al teach determining the probability an insured will make a claim or involved in an accident, as Fuchs et al state “[0013] Driver Insurance Risk: The probability that an insured will make a claim and for how much given a variety of measured factors. It could also refer simply to the probability of being in an accident”..
. Fuchs et al further state at paragraph [0004] “There is a need in the automotive insurance industry to accurately predict the risk of claims being made and the costliness of claims being made and adjusting the insurance rate charged to an individual or for a vehicle accordingly. The more accurate the prediction, the lower the premiums can become, making the insurer more competitive and presumably profitable and/or the insurer may choose to not insure individuals or vehicles of the perceived greatest risk or smallest profit potential”.
Fuchs et al also state at paragraph [0024]:
“Threshold: In multivariate analysis, several factors contribute to the predictive model. Some factors can be more relevant or more influential than others. For example the number of accidents in the past along a particular road segment, may be a better predictor of insurance risk of driving that segment than the average vehicle speed along the segment. However a relative weighting of the two parameters may predict better than either one used singly. So if a predictive model, when using a particular factor in the prediction, does not perform appreciably better than if the factor was not incorporated in the model, the factor can be removed from consideration. When this happens is when the difference in the two predictions is less than a preset threshold value”.
It would have been obvious to one of ordinary skill in the art at the effective filing date of the invention to incorporate the teachings of Fuchs et al into the system and method of Matsumoto et al in order to more accurately determine the validity of a claim.
As per Claim 2, Matsumoto et al teach or disclose “an incident prediction unit configured to calculate the predicted probability of occurrence of the incident” as Matsumoto et al state :
“The plant maker 11 stores various data 14 for storing basic data for calculating the damage probability of each equipment part of the target plant, and generates a damage probability diagram for time based on the plant data of the various databases 14. A plant risk obtained as a result of a calculation (for example, multiplication of both) based on the probability of damage based on the probability calculation tool 15 and the damage probability diagram created by the damage probability calculation tool and the amount of loss when the equipment part is damaged calculate. Data representing the plant risk is transmitted as basic data of the insurance premium calculation tool 17 of the nonlife insurance company 12.”
Fuchs et al also provide a similar teaching as Fuchs et al state at paragraph [0024]:
“Threshold: In multivariate analysis, several factors contribute to the predictive model. Some factors can be more relevant or more influential than others. For example the number of accidents in the past along a particular road segment, may be a better predictor of insurance risk of driving that segment than the average vehicle speed along the segment. However a relative weighting of the two parameters may predict better than either one used singly. So if a predictive model, when using a particular factor in the prediction, does not perform appreciably better than if the factor was not incorporated in the model, the factor can be removed from consideration. When this happens is when the difference in the two predictions is less than a preset threshold value”.
As per claim 4, Matsumoto et al teach or disclose registering or tracking the maintenance of work performed on an object covered by the insurance for the intended determination of approving/or rejecting a claim based on the calculated prediction of the occurrence of an incident as Matsumoto et al state:
“More specifically, as shown in FIG. 2, the various databases 14 include an operation history database 18 constructed based on the operation history data of the target plant, a design data database 19 constructed based on the design data of the equipment parts of the plant, Evaluation line database 20 for each failure mode that builds an evaluation diagram for each failure mode that evaluates the failure mode of the equipment parts of the plant, and target parts that are constructed with data of the target device parts that are subject to risk evaluation Database 21, maintenance history database 22 constructed with data representing the maintenance history of the plant, and data based on damage status of parts similar to the target equipment parts for each type of creep, fatigue, corrosion, wear, etc. causing damage The similar unit damage situation database 23 constructed by”.
As per claim 5, Matsumoto et al meet the limitation of :
“The insurance claim payment reviewing system according to claim 1, further comprising a detection unit configured to detect the occurrence of the incident with reference to a record of maintenance work performed on an object covered by the insurance”, as Matsumoto et al state:
“More specifically, as shown in FIG. 2, the various databases 14 include an operation history database 18 constructed based on the operation history data of the target plant, a design data database 19 constructed based on the design data of the equipment parts of the plant, Evaluation line database 20 for each failure mode that builds an evaluation diagram for each failure mode that evaluates the failure mode of the equipment parts of the plant, and target parts that are constructed with data of the target device parts that are subject to risk evaluation Database 21, maintenance history database 22 constructed with data representing the maintenance history of the plant, and data based on damage status of parts similar to the target equipment parts for each type of creep, fatigue, corrosion, wear, etc. causing damage The similar unit damage situation database 23 constructed by”.
As per claim 7, the combination of Matsumoto et al and Fuchs et al are discussed above. The combination does not explicitly state:
“a prediction accuracy calculation unit configured to calculate an accuracy of the predicted probability of occurrence of the incident”.
Fuchs et al teach at paragraph [0031] “Statistically Significant: refers to a minimum amount of information that can be used to achieve acceptable predictions of risk or hazard. For example if a predictive function relies heavily on a variable such as the average speed of vehicle passage for each road segment, then wherever there is no information concerning the average speed for any segment, then an average speed would have to be assumed. You could default to the speed limit for example. The more road segments that have an estimated average speed, the poorer the prediction of risk will be. A threshold needs to be in place to exclude information that is below a pre-defined value of percent coverage.”.
Matsumoto et al state:
“The plant risk data supplied as basic data to the insurance premium calculation tool of the insurance company can be made accurate and specific to the plant, and the calculated premium is reasonable and accurately reflects the risk. It becomes”.
In view of the teachings of Matsumoto et al and Fuchs et al, it would have been obvious to one of ordinary skill in the art at the effective filing date of the invention to incorporate features of “a prediction accuracy calculation unit configured to calculate an accuracy of the predicted probability of occurrence of the incident” in order to positively identify an incident so as to also accurately charge a premium and/also respond to an incident.
As per claim 8, Matsumoto et al meet the claimed limitation of :
“wherein the predicted probability of occurrence of the incident is based on a probability that a failure occurs in an object covered by the insurance”, as Matsumoto et al state:
“More specifically, as shown in FIG. 2, the various databases 14 include an operation history database 18 constructed based on the operation history data of the target plant, a design data database 19 constructed based on the design data of the equipment parts of the plant, Evaluation line database 20 for each failure mode that builds an evaluation diagram for each failure mode that evaluates the failure mode of the equipment parts of the plant, and target parts that are constructed with data of the target device parts that are subject to risk evaluation Database 21, maintenance history database 22 constructed with data representing the maintenance history of the plant, and data based on damage status of parts similar to the target equipment parts for each type of creep, fatigue, corrosion, wear, etc. causing damage The similar unit damage situation database 23 constructed by”.
As per claim 9, the combined teachings of Matsumoto et al and Fuchs et al are discussed above.
The combination does not explicitly state:
“the incident is an accident of a power transmission line, and the predicted probability of occurrence of the incident is based on a prediction of a timing at which a tree comes into contact with the power transmission line”. Matsumoto et al deal with providing insurance to a power plant. Power plants usually supply power to distant customers using cable lines or transmission line on many poles. Trees usually fall on transmission lines due to bad weather and dangerous wind speed. Fuchs et al teach obtaining weather data from a weather bureau. See paragraphs [0012] and [0058] of Fuchs et al..
Determining “the predicted probability of occurrence of the incident is based on a prediction of a timing at which a tree comes into contact with the power transmission line” in the combination of Matsumoto et al and Fuchs et al would have been obvious to one of ordinary skill in the art at the effective filing date of the invention to determine the likelihood of potential accidents related to the weather so as to properly assess a damage.
As per claim 10, in most plant facilities ,there would be a power failure as in most facilities, there would be also a demand.
As such, it would have been obvious to one of ordinary skill in the art to note that an incident may be a power failure, and the predicted probability of occurrence of the incident would be based on a prediction of a power demand”. The motivation to take account of this notion and to attribute this notion in the combination of Matsumoto et al and Fuchs et al in would have been to be informed and determined on how to react and/or prevent certain issues or catastrophic issues.
Claim(s) 3, 6 and 13 is/are rejected under 35 U.S.C. 103 as being unpatentable over Matsumoto et al (JP-2005190271-A) in view of Fuchs et al (US-20160189303-A1) as applied to claims 1, 4 and 12 above and further in view of Oehler et al (US 20220138700 A1).
As per claims 3, 6 and 13, the combined teachings of Matsumoto et al and Fuchs et al are discussed above.
Matsumoto et al teach or state:
“The plant maker 11 stores various data 14 for storing basic data for calculating the damage probability of each equipment part of the target plant, and generates a damage probability diagram for time based on the plant data of the various databases 14. A plant risk obtained as a result of a calculation (for example, multiplication of both) based on the probability of damage based on the probability calculation tool 15 and the damage probability diagram created by the damage probability calculation tool and the amount of loss when the equipment part is damaged calculate. Data representing the plant risk is transmitted as basic data of the insurance premium calculation tool 17 of the nonlife insurance company 12.
Matsumoto et al and Fuchs et al do not specifically state storing the occurrence of the incident on a distributed ledger or storing or recording the maintenance work on distributed ledgers.
Storing or recording data on a distributed ledger is old and well-practiced in the art at the effective filing date of the invention.
Oehler et al (US 20220138700 A1) disclose a system and method for determining a performance level of the transport based on the obtained data, dynamically revising, by the transport, the performance level based on a current use of the transport, and determining, by the transport, a next use of the transport, based on the dynamically revised performance level.
Ohler et al further teach storing vehicle data and maintenance data related to a transport vehicle ono a distributed ledger as Ohler et al state:
“[0055] Example embodiments provide a service to a particular vehicle and/or a user profile that is applied to the vehicle. For example, a user may be the owner of a vehicle or the operator of a vehicle owned by another party. The vehicle may require service at certain intervals and the service needs may require authorization prior to permitting the services to be received. Also, service centers may offer services to vehicles in a nearby area based on the vehicle's current route plan and a relative level of service requirements (e.g., immediate, severe, intermediate, minor, etc.). The vehicle needs may be monitored via one or more vehicle and/or road sensors or cameras, which report sensed data to a central controller computer device in and/or apart from the vehicle. This data is forwarded to a management server for review and action. A sensor may be located on one or more of the interior of the transport, the exterior of the transport, on a fixed object apart from the transport, and on another transport proximate the transport. The sensor may also be associated with the transport's speed, the transport's braking, the transport's acceleration, fuel levels, service needs, the gear-shifting of the transport, the transport's steering, and the like. A sensor, as described herein, may also be a device, such as a wireless device in and/or proximate to the transport. Also, sensor information may be used to identify whether the vehicle is operating safely and whether an occupant has engaged in any unexpected vehicle conditions, such as during a vehicle access and/or utilization period. Vehicle information collected before, during and/or after a vehicle's operation may be identified and stored in a transaction on a shared/distributed ledger, which may be generated and committed to the immutable ledger as determined by a permission granting consortium, and thus in a “decentralized” manner, such as via a blockchain membership group.”.
“[0183] FIG. 6C illustrates a blockchain configuration for storing blockchain transaction data, according to example embodiments. Referring to FIG. 6C, the example configuration 660 provides for the vehicle 662, the user device 664 and a server 666 sharing information with a distributed ledger (i.e., blockchain) 668. The server may represent a service provider entity inquiring with a vehicle service provider to share user profile rating information in the event that a known and established user profile is attempting to rent a vehicle with an established rated profile. The server 666 may be receiving and processing data related to a vehicle's service requirements. As the service events occur, such as the vehicle sensor data indicates a need for fuel/charge, a maintenance service, etc., a smart contract may be used to invoke rules, thresholds, sensor information gathering, etc., which may be used to invoke the vehicle service event. The blockchain transaction data 670 is saved for each transaction, such as the access event, the subsequent updates to a vehicle's service status, event updates, etc. The transactions may include the parties, the requirements (e.g., 18 years of age, service eligible candidate, valid driver's license, etc.), compensation levels, the distance traveled during the event, the registered recipients permitted to access the event and host a vehicle service, rights/permissions, sensor data retrieved during the vehicle event operation to log details of the next service event and identify a vehicle's condition status, and thresholds used to make determinations about whether the service event was completed and whether the vehicle's condition status has changed”.
It would have been obvious to one of ordinary skill in the art at the effective filing date of the invention to use a distributed ledger to store insurance data in the combined system Matsumoto et al and Fuchs et al as taught by Oehler et al in order to obtain a more secure database.
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 1-13 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Subject Matter Eligibility Standard
When considering subject matter eligibility under 35 U.S.C. 101, it must be determined whether the claim is directed to one of the four statutory categories of invention, i.e., process, machine, manufacture, or composition of matter.
Specifically, claim 1 is directed to a system. Claims 11 and 12 are directed to a method. Each of the claims falls under one of the four statutory classes of invention.
If the claim does fall within one of the statutory categories, it must then be determined whether the claim is directed to a judicial exception (i.e., law of nature, natural phenomenon, and abstract idea).
The claims when the bolded limitations are removed recite the following limitations:
Claim 1 recites: An insurance claim payment reviewing system comprising a determination unit configured to:
receive a claim on an insurance benefit from insurance with respect to an incident; and
approve the claim when a predicted probability of occurrence of the incident is lower than or equal to a predetermined value.
Claim 2 recites: The insurance claim payment reviewing system according to claim 1, further comprising:
an incident prediction unit configured to calculate the predicted probability of occurrence of the incident.
Claim 3 recites: The insurance claim payment reviewing system according to claim 1, wherein the determination unit acquires the predicted probability of occurrence of the incident with reference to distributed ledgers in which the predicted probability of occurrence calculated by the incident prediction device, which calculates the predicted probability of occurrence, is recorded.
Claim 4 recites: The insurance claim payment reviewing system according to claim 1, wherein referring to a record of maintenance work performed on an object covered by the insurance, the determination unit performs a process of rejecting the claim when predetermined maintenance work has not been performed on the object covered by the insurance.
Claim 5 recites: The insurance claim payment reviewing system according to claim 1, further comprising a detection unit configured to detect the occurrence of the incident with reference to a record of maintenance work performed on an object covered by the insurance.
Claim 6 recites: The insurance claim payment reviewing system according to claim 4 or 5, wherein the maintenance work is recorded in distributed ledgers.
Claim 7 recites: The insurance claim payment reviewing system according to claim 1, further comprising a prediction accuracy calculation unit configured to calculate an accuracy of the predicted probability of occurrence of the incident.
Claim 8 recites: The insurance claim payment reviewing system according to claim 1, wherein the predicted probability of occurrence of the incident is based on a probability that a failure occurs in an object covered by the insurance.
Claim 9 recites: The insurance claim payment reviewing system according to claim 1, wherein the incident is an accident of a power transmission line, and the predicted probability of occurrence of the incident is based on a prediction of a timing at which a tree comes into contact with the power transmission line.
Claim 10 recites: The insurance claim payment reviewing system according to claim 1, wherein the incident is a power failure, and the predicted probability of occurrence of the incident is based on a prediction of a power demand.
Claim 11 recites: A program for causing a computer to execute a process as a smart contract on a blockchain network, the process including:
receiving a claim on an insurance benefit from insurance with respect to an incident; and
approving the claim when a predicted probability of occurrence of the incident is lower than or equal to a predetermined value.
Claim 12 recites: An insurance claim payment reviewing method of an insurance claim payment reviewing system, the insurance claim payment reviewing method comprising:
by the insurance claim payment reviewing system,
receiving a claim on an insurance benefit from insurance with respect to an incident; and
approving the claim when a predicted probability of occurrence of the incident is lower than or equal to a predetermined value.
Claim 13 recites: wherein the maintenance work is recorded in distributed ledgers.
As per claims 1, 11 and 12, applicant is to be noted that the steps or functions of :
“receive” or “receiving” involves a data gathering function. The “approving” or “approve” involve mental processes.
The functions also performed by the determination unit noted in claims 3, 4 , 5 also involve mental processes with minimal and/or generic computer functions.
The functions perform by the “ calculating unit” of claims 2, 7 involve a mental process and/or a mathematical function.
The recordation of data of claims 6 and 13 involves mental processes and/or minimum generic computer functions.
The limitations of claims 6, 8, 9, 10 involve descriptive data for performing the functions of claim 1.
Here, the claimed concept falls into the category of grouping of abstract ideas of performing mental processes such as concepts performed in the human mind (including an observation, evaluation, judgment, opinion).
The claimed concept also falls into the category of grouping of abstract ideas a certain method of organizing human activity such as a fundamental economic principle of practices (including hedging, insurance, migrating risk) because it amounts to the functions of :
receiving a claim on an insurance benefit from insurance with respect to an incident, and approving the claim when a predicted probability of occurrence of the incident is lower than or equal to a predetermined value.
The BRI of the claimed limitations describes functions of :
“receiving a claim on an insurance benefit from insurance with respect to an incident, and approving the claim when a predicted probability of occurrence of the incident is lower than or equal to a predetermined value”.
Step 2A, Prong Two: The judicial exception is not integrated into a practical application, In particular, the clams recite the bolded limitations noted above as understood to be the additional limitations:
Claims 1-13 recite a broad recitation of a system (where it is unclear if it is a computer system or a system of performing a series of functions).
The claimed “prediction unit”, “determination unit”, “detection unit” and “distributed ledger (which is viewed as a memory for recording data) are similarly understood in light of applicant's specification as mere usage of any arrangement of computer software or hardware intermediate components potentially using networks to communicate with instructions are properly understood to be mere instructions to apply the abstraction using a computer or device or computer system.
Performing steps or functions by a system (assuming such is a computerized system) merely limits the abstraction to a computer field by execution by generic computers. See MPEP 2106.05.
As noted in MPEP 2106.04(d), limitations which amount to instructions to implement an abstract idea on a computer or merely using a computer as a tool, limitations which amount to insignificant extra-solution activity, and limitations which amount to generally linking to a particular technological environment do not integrate a practical exception into a practical application.
“Determining data”, “approving” and “calculating data) are similar to Alappat, which as noted in MPEP 2106. 05(b)(1) is superseded, and the correct analysis is to look whether the added elements integrate the exception into a practical application or provide significantly more than the judicial exception. The functions of the claims in the instant application are performed by one or more processors or computing system which receives and approves data.
Consideration of these steps as a combination does not change the analysis as they do not add anything compared to when the steps are considered separately. The claims recite a particular sequence of functions of “ receiving a claim on an insurance benefit from insurance with respect to an incident, and approving the claim when a predicted probability of occurrence of the incident is lower than or equal to a predetermined value”.
Performance of these steps or functions technologically may present a meaningful limit to the scope of the claim does not reasonably integrate the abstraction into a practical application.
Step 2B: The elements discussed above with respect to the practical application in Step 2A, prong 2 are equally applicable to consideration of whether the claims amount to significantly more. Accordingly, the clams fail to recite additional elements which, when considered individually and in combination, amount to significantly more. Reconsideration of these elements identified as insignificant extra-solution activity as part of Step 2B does not change the analysis.
Positively reciting a “system”, a “detection unit” and a “calculating unit” does not change the analysis as these aspects are properly considered as additional elements which amount to instructions to apply it with a computer.
These claimed elements also as found in the dependent claims are also recited at a high level of generality such that they amount to no more than mere instructions to apply the exception using a generic component.
In processing the claims, it is noted that the recitation of these additional elements do not impact the analysis of the claims because these elements in combination are noted only to be a general purpose computer for performing basic or routine computer functions. The claimed system and “detecting unit” and “calculation unit” are noted to a be a generic computer for receiving data and approving and performing routine and expected computer functions therein. These additional elements do not overcome the analysis as these elements are merely considered as additional elements which amount to instructions to be applied to the generic system or computer.
The judicial exception is not integrated into a practical application. In particular, the claimed “system” and “determining unit” and “calculating unit” are recited at a high level of generality such they amount to no more than mere instructions to apply the exception using generic components. Accordingly, the 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.
Accordingly, claims 1, 11 and 12 are directed to an abstract idea.
The dependent claim(s) when analyzed and each taken as a whole are held to be patent ineligible under 35 U.S.C. 101 because the additional recited limitation(s) fail(s) to establish that the claim(s) is/are not directed to an abstract idea.
THIS ACTION IS MADE FINAL. 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.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to FRANTZY POINVIL whose telephone number is (571)272-6797. The examiner can normally be reached M-Th 7:00AM to 5:30PM.
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, Michael Anderson can be reached at 571-270-0508. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/fp/
/FRANTZY POINVIL/Primary Examiner, Art Unit 3693
March 7, 2026