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 .
Status of claims
No new claim is added.
No amendment has been made.
Claims 1-20 are pending.
Response to arguments
With respect to Applicant’s remarks filed on 12/10/2025; Applicant's “Amendments and Remarks” have been fully considered. Applicant’s remarks will be addressed in sequential order as they were presented.
Applicant remarks:
Regarding claims 18-20 rejected under 101:
“Querying a social network server”-cannot performed mentally. “Determining an association based on data”-this is performed by a computing device, and is not a mere mental act. “Generating second data based on the association”-this step is performed by a machine, not a human mind. “Causing a vehicle to perform at least one action based on the second data”-is inherently technological and cannot be performed mentally.
Claims require a particular machine.
Claims are rooted in vehicle technology
Dependent claims 19-20 do not “apply it” or use a computer as a tool to perform and abstract idea.
Regarding claims 1-2,4-5,7-8,10-11, 13-14 and 17 rejected under 102:
Mehdi fails to teach “under different conditions”
Mehdi fails to teach “based on the output, at least one action for the vehicle”
Mehdi fails to teach “plurality of local profiles”
Mehdi fails to teach “remote profile linked to a local profile”
Regarding claims 3, 15-16 and 18-20 rejected under 103:
Mehdi fails to teach “social network server”, Ricci’s social network in para[0402] concerns cosmetic “avatar” presentation and never discloses ant “server query”.
Mehdi and Ricci do no teach “determining an association…server”.
Mehdi and Ricci do no teach “generating second data …” and “causing a vehicle…second data”.
Office Response:
Please see new mapping above, specifically the mapping for the independent claims.
Examiner stated in the previous Non-Final rejection that highlighted terms imply to abstract idea and underlined terms imply to additional elements. See below the previous office action:
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Querying a social network server is not an abstract idea. Determining an association based on data is simply doing association between the first and second occupant’s using first data which is a mental process, the claim can be performed mentally or in a computer (which Applicant agrees in the remark page 1). According to MPEP 2106.04(a)(2) (iii) (c), claims can recite a mental process even if they are claimed as being performed on a computer.
Generating second data based on the association can be performed in human mind or in a computer (which applicant agrees in the remark page 2). The claims do not define the “action” that the vehicle is performed based on the second data (controlling the vehicle). Examiner respectfully traverse the argument.
Regarding the argument that Claims require a particular machine.
According to MPEP 2106.04(a)(2) (iii) (c), claims can recite a mental process even if they are claimed as being performed on a computer.
Regarding the argument that claims are rooted in vehicle technology (improvement of vehicle system) is not persuasive. The additional claim elements do not teach the improvement details regarding how a computer aids the method, the extent to which the computer aids the method, or the significance of a computer to the performance of the method (MPEP 2106.05 (a) (ii).
Regarding claims 1-2,4-5,7-8,10-11, 13-14 and 17 rejected under 102:
Regarding claim 1 rejection under 35 U.S.C. 102, Mehdi states in para[0055] that the gaze tracking sensor used to detect where the occupant is looking based on the light source reflections between the cornea and the pupil. Claim 1 recites an occupant captured under “different conditions” but claim 1 does not clarify what the different conditions mean. Applicant clarify the term “different conditions” in the dependent claim 3.
Regarding the argument based on “based on the output, at least one action for the vehicle”, Mehdi states in paras [0044]-[0051] that “Each ECU controls subsystems and each subsystem 14 may include on or more sensors to sense data from one or more components of the subsystem. The ECU 12 may control one or more actuators of the corresponding subsystem 14 based on the data received from the one or more sensors and/or the one or more inputs from an occupant of the vehicle 10 (see para[0048]). Regarding claim 10, Mehdi states in para[0083] “control matches the detected identities to the corresponding profiles of the occupants (e.g., the profiles stored in a database in the remote server)”, para[0043] Throughout the present disclosure, references to terms such as servers, applications, and so on are for illustrative purposes only. The term server is to be understood broadly as representing a computing device comprising one or more processors and memory configured to execute machine readable instructions. The terms applications and computer programs are to be understood broadly as representing machine readable instructions executable by the computing devices.
Mehdi teaches (plurality of local profiles)- See Abstract “corresponding profiles of the occupants”.
(remote profile linked to a local profile)-See Abstract “The method comprises matching the detected identities to corresponding profiles of the occupants.”
Regarding claims 3, 15-16 and 18-20 rejected under 103:
Social network server mentioned in Ricci in para[0046] so claim 18 is still valid rejection under Mehdi in view of Ricci. Regarding the argument on “querying a social network server to obtain first data”, Ricci teaches in para[0240] that the profile identification module 848 may receive requests from a user or device to access a profile stored in profile data, in para[0113] the profile data may include one or more user profile, user profile may be generated based on data gathered from private information (such as user information from a social network).
Based on the arguments: an association between a first and second occupant… Ricci teaches in para [0383] The recognition of facial features may include comparing identified facial features associated with a user 216 with one or more identification characteristics stored in a memory. The one or more identification characteristics can be stored in a memory of a social networking site, facial recognition data memory, profile data memory 252 and/or other memory location. Additionally, in para[0319], Ricci teaches a device may be associated with one or more users (used by multiple members of a family), user identification portion may include a set of features like physical characteristics of particular user.
Ricci teaches in para[0387] The virtual personality may be generated by the personality module 2004 in conjunction with the personality matching module 2008, para[0013] determining whether the identified facial features associated with the person match user characteristics stored in a memory, para [0387] he matching engine 2012 may determine that the virtual personality should be generated to match the user's 216 happiness. In any event, the virtual personality is generated by the personality module 2004 in communication with the personality matching module 2008. The method 2100 can then present the generated virtual personality in step 2124, as previously described.
Applicant further argues that the other independent claims which recite similar features are allowable and the dependent claims are also allowable since they depend on allowable subject and the Office respectfully disagrees. It is the Office's stance that all of the claimed subject matter has been properly rejected; therefore, the Office's respectfully disagrees with applicant’s arguments.
Therefore, Examiner maintains the 35.U.S.C 101, 102 and 103 rejection and repeat the rejection as before with additional citation for the convenience and made FINAL rejection.
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 18-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Analysis for claim 18:
In January, 2019 (updated October 2019), the USPTO released new examination guidelines setting forth a two-step inquiry for determining whether a claim is directed to non-statutory subject matter. According to the guidelines, a claim is directed to non-statutory subject matter if:
STEP 1: the claim does not fall within one of the four statutory categories of invention (process, machine, manufacture or composition of matter), or
STEP 2: the claim recites a judicial exception, e.g. an abstract idea, without reciting additional elements that amount to significantly more than the judicial exception, as determined using the following analysis:
STEP 2A (PRONG 1): Does the claim recite an abstract idea, law of nature, or natural phenomenon?
STEP 2A (PRONG 2): Does the claim recite additional elements that integrate the judicial exception into a practical application?
STEP 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception?
Using the two-step inquiry, it is clear that claim 18 is directed toward non-statutory subject matter, as shown below:
STEP 1: Does claim 18 falls within one of the statutory categories?
Yes. Claim 18 is directed to a method.
STEP 2A (PRONG 1): Is the claim directed to a law of nature, a natural phenomenon or an abstract idea?
Yes, the claim is directed to an abstract idea.
With regard to STEP 2A (PRONG 1), the guidelines provide three groupings of subject matter that are considered abstract ideas:
Mathematical concepts – mathematical relationships, mathematical formulas or equations, mathematical calculations;
Certain methods of organizing human activity – fundamental economic principles or practices (including hedging, insurance, mitigating risk); commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations); managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions); and
Mental processes – concepts that are practicably performed in the human mind (including an observation, evaluation, judgment, opinion).
Claim 18:
A method comprising: querying a social network server to obtain first data; determining, based on the first data, an association between a first occupant and a second occupant; generating second data based on the association; and causing a vehicle to perform at least one action based on the second data.
The method in claim 18 is a mental process that can be practicably performed in the human mind and, therefore, an abstract idea. Specifically, the limitations of claim 18 highlighted above merely consist of determining an association based on first data between first occupant and second occupant and generating second data based on the association. More specifically, a person can mentally decide the association between first and second occupant. Thus, the claims recite a mental process.
STEP 2A (PRONG 2): Does the claim recite additional elements that integrate the judicial exception into a practical application? No, the claim does not recite additional elements that integrate the judicial exception into a practical application.
With regard to STEP 2A (prong 2), whether the claim recites additional elements that integrate the judicial exception into a practical application, the guidelines provide the following exemplary considerations that are indicative that an additional element (or combination of elements) may have integrated the judicial exception into a practical application:
an additional element reflects an improvement in the functioning of a computer, or an improvement to other technology or technical field;
an additional element that applies or uses a judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition;
an additional element implements a judicial exception with, or uses a judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim;
an additional element effects a transformation or reduction of a particular article to a different state or thing; and
an additional element 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.
While the guidelines further state that the exemplary considerations are not an exhaustive list and that there may be other examples of integrating the exception into a practical application, the guidelines also list examples in which a judicial exception has not been integrated into a practical application:
an additional element merely recites the words “apply it” (or an equivalent) with the judicial exception, or merely includes instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea;
an additional element adds insignificant extra-solution activity to the judicial exception; and
an additional element does no more than generally link the use of a judicial exception to a particular technological environment or field of use.
Claim 18:
A method comprising: querying a social network server to obtain first data; determining, based on the first data, an association between a first occupant and a second occupant; generating second data based on the association; and causing a vehicle to perform at least one action based on the second data.
Claim 18 does not recite any of the exemplary considerations that are indicative of an abstract idea having been integrated into a practical application. In particular, claim 18 only recites additional elements – “a vehicle to perform at least one action based on the second data” and “querying a social network server to obtain first data”. There are no further details in the claim that specify how the actions are performed, such that it amounts to no more than insignificant extra solution activity of data gathering. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
Further, claim 18 does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above, the additional elements of “to perform at least one action based on the second data” and “querying a social network server to obtain first data” amounts to no more than insignificant extra solution activity of data gathering. Therefore, claim 18 is not patent eligible.
Dependent claims 19-20, when analyzed as a whole, are held to be patent ineligible under 35 U.S.C. 101 because the additional recited limitations fail to establish that the claims are not directed to an abstract idea. The additional elements, if any, in the dependent claims are not sufficient to amount to significantly more than the judicial exception.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1-2, 4-5, 7-8, 10-11,13-14, 17 are rejected under 35 U.S.C. 102 (a)(2) as being anticipated by US 20210284175 A1 to Mehdi et al. (herein after “Mehdi”).
Regarding claim 1, Mehdi discloses A system comprising: at least one sensor; and at least one processing device configured to: collect, using the sensor, data from an interior of a vehicle (See Mehdi para[0004] “…detecting identities of occupants of a vehicle using any of a camera system, an audio system, a biometric sensing system, and a mobile device detection system in the vehicle.”); generate an output from a machine-learning model (see Mehdi “collecting data about an occupant and learning their preferences “(i.e. a machine-learned model): using the collected data as input (See Mehdi para[0041] “The systems and methods of the present disclosure can monitor driver/passenger activity during a ride such as where are they pointing (e.g., using hand or head motion), how long their eyes linger on an advertisement on a billboard or on a building, whether a person expressed interest in what is being observed, etc. to enable data collection for content in the real world similar to data collection performed for content that appears online., wherein the machine-learning model is trained using images of an occupant captured under different conditions(see Mehdi para[0014] “…by recognizing any of faces…”, para[0055] that the gaze tracking sensor used to detect where the occupant is looking based on the light source reflections between the cornea and the pupil);
; and perform, based on the output, at least one action for the vehicle (see Mehdi see para[0073] , paras [0044]-[0051]“Each ECU controls subsystems and each subsystem 14 may include on or more sensors to sense data from one or more components of the subsystem. The ECU 12 may control one or more actuators of the corresponding subsystem 14 based on the data received from the one or more sensors and/or the one or more inputs from an occupant of the vehicle 10 (see para[0048]).
Regarding claim 2, Mehdi discloses wherein the output is used to identify the occupant, and performing the at least one action comprises controlling operation of the vehicle. (see Mehdi see para[0073] control/detect where the person is looking; para[0074] looking based on the vehicles GPS data or by detecting the person’s gaze; para[0076] control optionally estimates the person's reaction/emotion indicating the person's liking/disliking for the content being viewed. Control estimates the person's reaction/emotion's based on audiovisual data of the person collected using microphone/camera while the person views the content, paras [0044]-[0051]) .
Regarding claim 4, Mehdi discloses wherein the output indicates whether the occupant is a driver, and the action includes selection of a manner of driving (see Mehdi para [0039] The collected data can be appended to user profiles. Inferences of driver's/passengers' actions drawn based on the collected data can be used to determine their likings and dis-likings (i.e., preferences).).
Regarding claim 5, Mehdi discloses wherein the machine-learning model (see Mehdi “collecting data about an occupant and learning their preferences” (i.e. a machine-learned model):) is trained using at least one of images of the occupant gathered by the sensor (see Mehdi para[0014] “…by recognizing any of faces…; para[0054] For example, the cameras may be focused on headrests of each seat in the vehicle 10 to capture the facial images and other gestures of occupants of the vehicle 10.), or voice recordings of the occupant collected by the sensor (see Mehdi para[0014] The identity detection system is configured to detect identities occupants of the vehicle by recognizing any of faces, voices, fingerprints, or mobile devices of the occupants.).
Regarding claim 7, Mehdi discloses wherein the machine-learning model is configured to determine whether an occupant is present in the vehicle based on collected data (see Mehdi [0004] “The method comprises matching the detected identities to corresponding profiles of the occupants.”);
Regarding claim 8, Mehdi discloses wherein the sensor includes a camera (see Mehdi para[0004] “…detecting identities of occupants of a vehicle using any of a camera system, an audio system, a biometric sensing system, and a mobile device detection system in the vehicle.”).
Regarding claim 10, Mehdi teaches An apparatus comprising: memory storing a database(see Mehdi para[0044] “In each ECU, the microcontroller includes a … memory…”); and at least one processing device configured to: store a plurality of local profiles in the database(see Mehdi para[0023] “…and store the information in the profile of the one of the occupants, Abstract ”), each local profile including data regarding an occupant of a vehicle(See Mehdi para[0068] “At 208, control detects faces (or fingerprints, voices, mobile devices) of all occupants of the vehicle (e.g., by capturing images of their faces, or data about their fingerprints, voices, or mobile devices and matching them to the corresponding data stored in a database in the remote server).”),; and receive a first remote profile from a computing device (see Mehdi para[0068] “At 212, control perceives each occupant's preferences (as explained below) and adds them to their respective profiles if settings in the profiles allow.”)
wherein the first remote profile is linked to a first local profile (see Mahdi [0014] “The identity detection system is configured to match the detected identities to corresponding profiles of the occupants.”);
Regarding claim 11, Mehdi remains applied as Claim 10. Mehdi teaches wherein the data regarding the occupant includes biometric data of the occupant (see Mehdi para[0004] A method comprises detecting identities of occupants of a vehicle using any of a camera system, an audio system, a biometric sensing system,).
Regarding claim 13, Mehdi remains applied as Claim 10. Mehdi discloses wherein each local profile is generated in response to detection of the respective occupant. (see Mehdi para[0014] “The identity detection system is configured to match the detected identities to corresponding profiles of the occupants.”).
Regarding claim 14, Mehdi remains applied as Claim 10. Mehdi discloses wherein the first remote profile stores configuration data for a first occupant. (see Mehdi para[0068] “…corresponding data stored in a database in the remote server…”)
Regarding claim 17, Mehdi remains applied as Claim 10. Mehdi discloses wherein the computing device is configured to determine a correlation between the first local profile and the first remote profile. (see Mehdi para ([0090] “Alternatively, some of the above processing can be performed at the vehicle as well. For example, profiles of identified occupants can be downloaded via the network from the remote server to the vehicle. The profiles updated with any preference data can be subsequently uploaded via the network to the remote server.”).
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.
Claims 3, 15-16 and 18-20 are rejected under 35 U.S.C. 103 as being unpatentable over Mehdi in view of US 20170247000 A1 to Ricci (herein after “Ricci”).
Regarding claim 3, Mehdi remains applied as Claim 1. However, Mehdi does not expressly disclose or otherwise teach wherein the different conditions include at least one of different lighting conditions or different clothing of the occupant. Nevertheless, in a related field of invention, Ricci teaches wherein the different conditions include at least one of different lighting conditions (see Ricci para [0016] Aspects of the above method include wherein the one or more settings include at least one of a vehicle interior environment, temperature, air composition, oxygen level, sound level, window position, seat position, and lighting level) or different clothing of the occupant.
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention with a reasonable expectation of success to combine Mehdi’s detecting system identities of occupants of a vehicle using any of a camera system with Ricci’s different conditions include at least one of different lighting conditions and clothing in order to allow to address the deviation is provided by the vehicle (see Ricci para[0016]).
Regarding claim 15, Mehdi remains applied as Claim 10. However, Mehdi does not expressly disclose or otherwise teach wherein the configuration data is generated by the computing device based on an association between the first occupant and a second occupant. Nevertheless, Ricci same field of endeavor teaches wherein the configuration data is generated by the computing device based on an association between the first occupant and a second occupant (see Ricci para[0402] “…generating a group avatar that represents two or more users 216 in the group of two or more users (step 2220). This group avatar may include at least one common setting and/or preference shared between the avatars of the group of users 216. For example, a brother and sister may be seated in a passenger area (e.g., area 2 508B) of a vehicle 104. The brother may like rock music and dark colors (e.g., stored in the brother's user profile), while the sister may like pop music and pastel colors (e.g., stored in the sister's user profile). As provided above, a group avatar may be created to appeal to both users (e.g., without alienating at least one user 216.”).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention with a reasonable expectation of success to combine Mehdi’s detecting system identities of occupants of a vehicle using any of a camera system with Ricci’s different conditions include at least one of different lighting conditions and clothing in order to allow to address the deviation is provided by the vehicle (see Ricci para[0016]).
Regarding claim 16, Mehdi remains applied as Claim 10. However, Mehdi does not expressly disclose or otherwise teach wherein the processing device is further configured to perform, based on the configuration data, at least one action for the vehicle. Nevertheless, Ricci same field of endeavor teaches wherein the processing device is further configured to perform, based on the configuration data, at least one action for the vehicle (see Ricci[0459] “In some cases, the adjustment of one or more settings associated with the infotainment system 870 may be allowed, denied, and/or limited based on one or more access priorities. Users 216 may have an access priority assigned by the infotainment system 870.”).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention with a reasonable expectation of success to combine Mehdi’s detecting system identities of occupants of a vehicle using any of a camera system with Ricci’s different conditions include at least one of different lighting conditions and clothing in order to allow to address the deviation is provided by the vehicle (see Ricci para[0016]).
Regarding claim 18, Mehdi remains applied as Claim 10. However, Mehdi does not expressly disclose or otherwise teach querying a social network server to obtain first data, determining, based on the first data, an association between a first occupant and a second occupant; generating second data based on the association. Nevertheless, Ricci same field of endeavor teaches A method comprising: querying a social network server to obtain first data (Ricci in para[0046], Ricci teaches in para[0240] that the profile identification module 848 may receive requests from a user or device to access a profile stored in profile data, in para[0113] the profile data may include one or more user profile, user profile may be generated based on data gathered from private information (such as user information from a social network)
determining, based on the first data, an association between a first occupant and a second occupant (Ricci teaches in para [0383] The recognition of facial features may include comparing identified facial features associated with a user 216 with one or more identification characteristics stored in a memory. The one or more identification characteristics can be stored in a memory of a social networking site, facial recognition data memory, profile data memory 252 and/or other memory location. Additionally, para[0319]); generating second data based on the association and causing a vehicle to perform at least one action based on the second data (see Ricci para[0402] “…generating a group avatar that represents two or more users 216 in the group of two or more users (step 2220). This group avatar may include at least one common setting and/or preference shared between the avatars of the group of users 216. For example, a brother and sister may be seated in a passenger area (e.g., area 2 508B) of a vehicle 104. The brother may like rock music and dark colors (e.g., stored in the brother's user profile), while the sister may like pop music and pastel colors (e.g., stored in the sister's user profile). As provided above, a group avatar may be created to appeal to both users (e.g., without alienating at least one user 216.”).),
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention with a reasonable expectation of success to combine Mehdi’s detecting system identities of occupants of a vehicle using any of a camera system with Ricci’s different conditions include at least one of different lighting conditions and clothing in order to allow to address the deviation is provided by the vehicle (see Ricci para[0016]).
Regarding claim 19, Mehdi and Ricci remain applied as Claim 18. However, Mehdi does not expressly disclose or otherwise teach wherein the association corresponds to a configuration for at least one function of a vehicle used by the first occupant or the second occupant. Nevertheless, Ricci same field of endeavor teaches wherein the association corresponds to a configuration for at least one function of a vehicle used by the first occupant or the second occupant (see Ricci para[0402] “…generating a group avatar that represents two or more users 216 in the group of two or more users (step 2220). This group avatar may include at least one common setting and/or preference shared between the avatars of the group of users 216. For example, a brother and sister may be seated in a passenger area (e.g., area 2 508B) of a vehicle 104. The brother may like rock music and dark colors (e.g., stored in the brother's user profile), while the sister may like pop music and pastel colors (e.g., stored in the sister's user profile). As provided above, a group avatar may be created to appeal to both users (e.g., without alienating at least one user 216.”).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention with a reasonable expectation of success to combine Mehdi’s detecting system identities of occupants of a vehicle using any of a camera system with Ricci’s different conditions include at least one of different lighting conditions and clothing in order to allow to address the deviation is provided by the vehicle (see Ricci para[0016]).
Regarding claim 20, Mehdi and Ricci remain applied as Claim 18. Nevertheless, Ricci same field of endeavor teaches A method comprising: querying a social network server to obtain first data (Ricci in para[0046], Ricci teaches in para[0240] that the profile identification module 848 may receive requests from a user or device to access a profile stored in profile data, in para[0113] the profile data may include one or more user profile, user profile may be generated based on data gathered from private information (such as user information from a social network) wherein is performed in response to determining that the occupant is present in the vehicle (see Mehdi para [0014] “The identity detection system is configured to match the detected identities to corresponding profiles of the occupants.”).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention with a reasonable expectation of success to combine Mehdi’s detecting system identities of occupants of a vehicle using any of a camera system with Ricci’s different conditions include at least one of different lighting conditions and clothing in order to allow to address the deviation is provided by the vehicle (see Ricci para[0016]).
Claims 6 and 12 are rejected under 35 U.S.C. 103 as being unpatentable over Mehdi in view of US 20090082926 A1 to Klein (herein after “Klein”).
Regarding claim 6, Mehdi remains applied as Claim 1. However, Mehdi does not expressly disclose or otherwise teach wherein the machine-learning model is configured to identify a first occupant and a second occupant as being in conflict regarding restrictions on the first or second occupant. Nevertheless, in a related field of invention, Klein teaches wherein the machine-learning model is configured to identify a first occupant and a second occupant as being in conflict regarding restrictions on the first or second occupant (See Klein [abstract] “A automotive vehicle safety system for seat belt securement that prevents the transmission from being engaged until all seated occupants have buckled their seat belts includes a weight sensing pad for each seat cushion interconnected in circuit to a buckle switch in each seat belt buckle with the buckle switches electrically interconnected to a solenoid that allows or disallows transmission engagement such that if each weight sensing pad detects no weight upon the seat the corresponding buckle switch stays open but when any weight sensing pad detects a predetermined weight (the weight of the occupant upon the seat) that weight sensing pad opens the circuit thereby causing the corresponding buckle switch to close only after that seat belt is buckled thus causing the solenoid interconnected to the transmission to close and enabling access to the transmission so that the vehicle can be shifted out of the parking gear).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention with a reasonable expectation of success to combine Mehdi’s detecting system identities of occupants of a vehicle using any of a camera system with Klein’s a first occupant and a second occupant as being in conflict regarding restrictions on the first or second occupant in order to allow to the transmission to close and enabling access to the transmission so that the vehicle can be shifted out of the parking gear (see Klein abstract).
Regarding claim 12, Mehdi remains applied as Claim 10. However, Mehdi does not expressly disclose or otherwise teach wherein the data regarding the occupant includes a classification of the occupant. Nevertheless, Klein same field of endeavor teaches wherein the data regarding the occupant includes a classification of the occupant ( see Klein [abstract] “A automotive vehicle safety system for seat belt securement that prevents the transmission from being engaged until all seated occupants have buckled their seat belts includes a weight sensing pad for each seat cushion interconnected in circuit to a buckle switch in each seat belt buckle with the buckle switches electrically interconnected to a solenoid that allows or disallows transmission engagement such that if each weight sensing pad detects no weight upon the seat the corresponding buckle switch stays open but when any weight sensing pad detects a predetermined weight (the weight of the occupant upon the seat) that weight sensing pad opens the circuit thereby causing the corresponding buckle switch to close only after that seat belt is buckled thus causing the solenoid interconnected to the transmission to close and enabling access to the transmission so that the vehicle can be shifted out of the parking gear.”; the occupant in the driver’s seat of Klein is a first occupant, and the state of an occupant’s seat belt is their classification.).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention with a reasonable expectation of success to combine Mehdi’s detecting system identities of occupants of a vehicle using any of a camera system with Klein’s a first occupant and a second occupant as being in conflict regarding restrictions on the first or second occupant in order to allow to the transmission to close and enabling access to the transmission so that the vehicle can be shifted out of the parking gear (see Klein abstract).
Claim 9 is rejected under 35 U.S.C. 103 as being unpatentable over Mehdi in view of US 20170313322 A1 to Onorato et al. (herein after “Onorato”).
Regarding claim 9, Mehdi remains applied as Claim 1. However, Mehdi does not expressly disclose or otherwise teach wherein the machine-learning model is configured to use data from a remote server to augment data for a person stored locally. Nevertheless, in a related field of invention, Onorato teaches wherein the machine-learning model is configured to use data from a remote server to augment data for a person stored locally (see Onorato Fig. 1, Network Servers 130, Driver Social Network 160; [0008] “…a social network to share one or more portions of the vehicle setting data with…”).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention with a reasonable expectation of success to combine Mehdi’s detecting system identities of occupants of a vehicle using any of a camera system with Onorato’s the machine-learning model is configured to use data from a remote server to augment data for a person stored locally in order to allow to share vehicle setting values with fans through one or more social media networks specified in the driver preferences (see Onorato para[0005]).
Conclusion
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to NAZIA AFRIN whose telephone number is (703)756-1175. The examiner can normally be reached Monday-Friday 7:30-6.
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, Scott A Browne can be reached at 5712700151. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/NAZIA AFRIN/Examiner, Art Unit 3666
/SCOTT A BROWNE/Supervisory Patent Examiner, Art Unit 3666