DETAILED ACTION
This Final Office Action is in response to the application filed on 04/17/2024 and the Amendment & Remark filed on 12/17/2025.
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 .
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 1-20 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
An original claim may lack written description support when (1) the claim defines the invention in functional language specifying a desired result but the disclosure fails to sufficiently identify how the function is performed or the result is achieved or (2) a broad genus claim is presented but the disclosure only describes a narrow species with no evidence that the genus is contemplated. See Ariad Pharms., Inc. v. Eli Lilly & Co., 598 F.3d 1336, 1349-50 (Fed. Cir. 2010) (en banc).
While the Applicant specifies in claims 1, 9 and 17 that “generate, via machine learning, an operator model for the user based upon historical telematics data including patterns of telematics data corresponding to periods when the user is operating the vehicle, the operator model configured to output data indicating whether the user is operating vehicle based upon an input of telematics data”, there is no written content as to how or what specific process of determination are performed (i.e. formulas, algorithms, sequence of mathematical steps, process of determination, for example) in order to generate an operator model determining whether a user is operating a vehicle. The examiner noted the amended claim recites “via machine learning”, but the disclosure only includes a plurality machine learning that “may be used”. There is no written content describing the process of how the specific operator model is generated “via machine learning”. As such, the disclosure does not objectively demonstrate that the applicant actually invented—was in possession of—the claimed subject matter.
While the Applicant specifies in claims 1, 9 and 17 that “generate, via machine learning, an operator model for the user based upon historical telematics data including patterns of telematics data corresponding to periods when the user is operating the vehicle, the operator model configured to output data indicating whether the user is operating vehicle based upon an input of telematics data”, “input the telematics data into the operator model causing the operator model to output one or more periods of time during which the user is operating the vehicle” and “”generate a driver profile including user data representing (i) the one or more periods of time and (ii') the mobile device mode associated with each of the one or more periods of time, there is no written content as to how or what specific process of determination are performed (i.e. formulas, algorithms, sequence of mathematical steps, process of determination, for example) in order to generate an operator model determining whether a user is operating a vehicle nor the further generating of the driver profile. The examiner noted that Specification Paragraph 0060 recite “AI/DL module 210 may include any rules, algorithms, training data sets/programs, and/or any other suitable data and/or executable instructions that enable user analytics computing device 110 employ artificial intelligence and/or deep learning to determine when a user is driving, generate user profiles 222, user offerings, and the like.” However, it should be noted that open-ended description specifying a desired result does not sufficiently identify how the function is performed or the result is achieved. As such, the disclosure does not objectively demonstrate that the applicant actually invented—was in possession of—the claimed subject matter.
The written description requirement can be satisfied if the particular steps, i.e., algorithm, necessary to perform the claimed function were “described in the specification.” In re Hayes Microcomputer Prods, Inc. Patent Litigation, 982 F.2d 1527, 1533-34, 25 USPQ2d 1241, (Fed. Cir. 1992).
As such, claims 1-20 are rejected as failing the written description requirement.
Claims 1, 9 and 17 each include the limitation “content”, which represents claim language in scope that is not supported by the written specification. At best, the Applicant has only disclosed one particular species regarding a diversity strategy in the written specification. Throughout the Specification the “content” to be generated and delivered to a user is only limited to “offerings”, while the Applicant is claiming the entire genus of content.
See MPEP 2161 “For example, in LizardTech, the claim was directed to a method of compressing digital images using seamless discrete wavelet transformation ("DWT"). The court found that the claim covered all ways of performing DWT-based compression processes that lead to a seamless DWT because there were no limitations as to how the seamless DWT was to be accomplished. However, the specification provided only one method for creating a seamless DWT, and there was no evidence that the specification contemplated a more generic way of creating a seamless array of DWT coefficients. Therefore, the written description requirement was not satisfied in this case because the specification did not provide sufficient evidence that the inventor invented the generic claim”. LizardTech, 424 F.3d at 1346, 76 USPQ2d at 1733.
As such, the written specification does not support the scope of claims 1-20 as claimed, and the claims are rejected as failing to comply with the written description requirement.
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 a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
As an initial matter, the claims as a whole are to an apparatus, a process and a manufacture, which falls within one or more statutory categories. (Step 1: YES) The recitation of the claimed invention is then further analyzed as follow, in which the abstract elements are boldfaced.
The claims recites:
A user analytics computing device for processing mobile device telematics data and to verify a status of a mobile device of a user during operation of a vehicle, the user analytics computing device comprising at least one processor in communication with a memory device, the at least one processor programmed to:
generate, via machine learning, an operator model for the user based upon historical telematics data including patterns of telematics data corresponding to periods when the user is operating the vehicle, the operator model configured to output data indicating whether the user is operating a vehicle based upon an input of telematics data;
receive, from a mobile device of the user, telematics data;
input the telematics data into the operator model causing the operator model to output one or more periods of time during which the user is operating the vehicle;
determine, based on the telematics data, a mobile device mode of the mobile device during each of the one or more periods of time;
generate a driver profile including user data representing (i) the one or more periods of time and (ii) the mobile device mode associated with each of the one or more periods of time; and
cause the mobile device to present user content generated based upon the driver profile.
wherein the operator model is configured to determine whether the device of the user is in do not disturb mode.
wherein the telematics data is first telematics data, the mobile device mode data is first mobile device mode data and the period of time is a first period of time, and wherein at least one processor is further programmed to: receive, from a mobile device of the user, second telematics data associated with movement of the user over a second period of time and second mobile device mode data over the second period of time; and input the second telematics data into the operator model, and in response to determining the user is operating the vehicle, build upon the driver profile based upon the second telematics data and the second mobile device mode data.
wherein the at least one processor is further programmed to train the operator model using a training dataset that includes one or more training variables, the training dataset comprising historical data.
wherein the at least one processor is further programmed to update the training dataset to include new historical data and re-train the trained operator model using the updated training set.
wherein the at least one processor is further programmed to, in response to determining the device of the user is within a predetermined distance of a vehicle, cause to be displayed on the user computing device, a notification to turn the device into a do not disturb mode before driving.
wherein the notification is a pop-up or push-notification.
wherein the user offering is generated based upon real-time data.
A computer-implemented method for processing vehicle-based telematics data and to verify a status of a mobile device of a user during operation of a vehicle, the method comprising: …
A non-transitory computer-readable storage medium having computer-executable instructions embodied thereon, when executed by a user analytics computing device having at least one processor in communication with at least one memory, the computer-executable instructions cause the at least one processor to: …
Based on the limitations above and the Specification disclosing no type of content other than an offering, the claims describe a process that covers analyzing user data and generating and delivering content (offering) to the user. Analyzing user data and generating and delivering offering to the user are considered to be a commercial interaction, which falls within the “Certain Methods of Organizing Human Activities” grouping of abstract ideas. As such, the claim(s) recite(s) a Judicial Exception. (Step 2A prong one: Yes)
This analysis then evaluates whether the claims as a whole integrates the recited Judicial Exception into a practical application of the exception. In particular, the claims recite the additional element(s) of “processor” as a mere tool to perform the steps of the Judicial Exception, which encompasses no more than Mere Instruction to Apply.
For example, the limitation “generate, via machine learning, an operator model for the user based upon historical telematics data including patterns of telematics data corresponding to periods when the user is operating the vehicle, the operator model configured to output data indicating whether the user is operating a vehicle based upon an input of telematics data” encompasses no more than generically invoking a generic processor to apply the Judicial Exception step of generating an operator model to determine whether the user is operating a vehicle;
the limitation “receive, from a mobile device of the user, telematics data” encompasses no more than generically invoking a generic processor to apply the Judicial Exception step of receiving user telematics data;
the limitation “input the telematics data into the operator model causing the operator model to output one or more periods of time during which the user is operating the vehicle” encompasses no more than generically invoking a generic processor to apply the Judicial Exception step of inputting the received data into the operator model;
the limitation “determine, based on the telematics data, a mobile device mode of the mobile device during each of the one or more periods of time” encompasses no more than generically invoking a generic processor to apply the Judicial Exception step of determining the mobile device mode of mobile device during the one or more period of time;
the limitation “generate a driver profile including user data representing (i) the one or more periods of time and (ii) the mobile device mode associated with each of the one or more periods of time” encompasses no more than generically invoking a generic processor to apply the Judicial Exception step of generating a driver profile based upon the received data;
the limitation “cause the mobile device to present user content generated based upon the driver profile” encompasses no more than generically invoking a generic processor to apply the Judicial Exception step of presenting offerings to the user;
the limitation “wherein the operator model is configured to determine whether the device of the user is in do not disturb mode” encompasses no more than generically invoking a generic processor to apply the Judicial Exception step of determining whether the user’s mobile device is do not disturb mode;
the limitation “wherein the telematics data is first telematics data, the mobile device mode data is first mobile device mode data and the period of time is a first period of time, and wherein at least one processor is further programmed to: receive, from a mobile device of the user, second telematics data associated with movement of the user over a second period of time and second mobile device mode data over the second period of time; and input the second telematics data into the operator model, and in response to determining the user is operating the vehicle, build upon the driver profile based upon the second telematics data and the second mobile device mode data” encompasses no more than generically invoking a generic processor to apply the Judicial Exception step of receiving a second set of telematics data and user mobile device mode data over a second period of time;
the limitation “wherein the at least one processor is further programmed to train the operator model using a training dataset that includes one or more training variables, the training dataset comprising historical data” encompasses no more than generically invoking a generic processor to apply the Judicial Exception step of training the model using a training data set;
the limitation “wherein the at least one processor is further programmed to update the training dataset to include new historical data and re-train the trained operator model using the updated training set” encompasses no more than generically invoking a generic processor to apply the Judicial Exception step of updating the training data set;
the limitation “wherein the at least one processor is further programmed to, in response to determining the device of the user is within a predetermined distance of a vehicle, cause to be displayed on the user computing device, a notification to turn the device into a do not disturb mode before driving” encompasses no more than generically invoking a generic processor to apply the Judicial Exception step of determining the user’s device within distance of the a vehicle then notifying the user to turn on the do not disturb mode;
the limitation “wherein the notification is a pop-up or push-notification” encompasses no more than generically invoking a generic processor to apply the Judicial Exception step of sending notification;
the limitation “wherein the user offering is generated based upon real-time data” encompasses no more than generically invoking a generic processor to apply the Judicial Exception step of providing offering upon real-time data.
Other than being generally linked to the steps of the Judicial Exception, the additional elements in the above step(s) is/are recited at a high-level of generality, without technological detail of how the particular steps are performed technologically.
The additional element(s) of “memory” and/or “non-transitory storage medium” are generically recited to store data and/or instructions of the Judicial Exception.
The additional element(s) of “push notification” and “cause to be displayed on the user computing device” are generically recited to perform communication steps such as transmitting and display without insufficient detail how they are accomplished.
The additional element(s) of “via machine learning”, “operator model” and “train the operator model using a training dataset” are generically recited to perform generating or decisioning steps described only by a result-oriented solution with insufficient detail how the generating and training are accomplished.
The examiner found the recitation of the above additional elements to be mere instructions to implement the Judicial Exception idea on a computer.
Indeed, the instant claims (1) attempted to cover a solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result; (2) used of a computer or other machinery in its ordinary capacity for economic or other tasks or simply added a general purpose computer or computer components after the fact to the Judicial Exception and (3) generally applied the Judicial Exception to a generic computing environment without limitation indicative of practical application (See MPEP 2106.04(d)I). Thus, the claims are no more than Mere Instruction to Apply the Judicial Exception (See MPEP 2106.05(f)) or adding insignificant extra-solution activity to the judicial exception (See MPEP 2106.05(g)), which do not integrate the cited Judicial Exception into practical application (Step 2A prong two: No) The claims are directed to a Judicial Exception.
The claim does 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 processor to analyze user data to provide offering to no more than mere instructions to apply the exception using generic computer components. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. No additional element currently recited in the claims amount the claims to be significantly more than the cited abstract idea. (Step 2B: No)
Therefore, claims 1-20 are rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
Response to Arguments
Applicant's arguments filed on 12/17/2025 have been fully considered but they are not persuasive.
Regarding the applicant’s argument that the amendment addressed the rejection under 35 USC 112(a), the examiner respectfully disagrees. The nominally invoked “via machine learning” do not provide adequate written description as the disclosure only includes a plurality machine learning that “may be used”. There is no written content describing the process of how the specific operator model is generated “via machine learning”. As such, the disclosure does not objectively demonstrate that the applicant actually invented—was in possession of—the claimed subject matter.
Regarding the applicant’s argument that the claims do not fall within any of the enumerated categories of abstract ideas, the examiner respectfully disagrees. While the applicant amended “offerings” to “user content”, the entire disclosure do not describe generating and delivering any “user content” other than “offerings”. In fact, the disclosure is literally silent on “user content”. The evaluating of user data and the presenting of offerings (emphasis added) recites a Judicial Exception under the enumerated categories as identified in the rejection. As such, the argument is not persuasive.
Regarding the applicant’s argument that the claims integrate the Judicial Exception into practical application, the examiner respectfully disagrees. The applicant asserted that the claims provide improvement to another technology “by utilizing an operator model that is trained based upon historical telematics data including patterns of telematics data corresponding to period when the user is operating the vehicle and that is configured to output data indicating whether the user is operating the vehicle based upon an input telematics data”. However, the examiner found no disclosure of technological detail on what this desired “operator model” is or specifically how the operator model is generated. It should be noted generically invoking an additional element to perform a desired function without providing technological detail of how the desired function is achieved would be considered as Mere Instruction to Apply, which is an ineligible drafting effort. As such, the argument is not persuasive.
Regarding the applicant’s argument that the claims are directed “significantly more” than the abstract idea, the examiner respectfully disagrees. The applicant asserted that the claims are not well-known, routine or conventional. It should be note that “even newly discovered judicial exceptions are still exceptions, despite their novelty. For example, the mathematical formula in Flook, the laws of nature in Mayo, and the isolated DNA in Myriad were all novel, but nonetheless were considered by the Supreme Court to be judicial exceptions because they were “‘basic tools of scientific and technological work’ that lie beyond the domain of patent protection.” (See July 2015 Update of IGPSME Page 3) Furthermore, as explained above, mere invoking an additional element to perform steps of a Judicial Exception do not result in eligibility. As such, the argument is not persuasive.
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 CHO KWONG whose telephone number is (571)270-7955. The examiner can normally be reached 9am - 5pm EST M-F.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, MICHAEL W 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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/CHO YIU KWONG/Primary Examiner, Art Unit 3693