DETAILED ACTION
This Office action is in response to application filed on 10/10/2024. Claim(s) 1-20 is/are pending.
Claim Objections
Claim(s) 1-10 is/are objected to because of the following informalities:
Claim 1 appears to contain a typographical error in line 5, where “configued” is misspelled.
Appropriate correction is required.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are:
“driver data collection module” in claim(s) 1, described in Applicant’s specification as “Referring to FIG. 1, a device 10 for controlling an integrated memory system according to an embodiment may include…a driver data collection module 12”, [0042], “The term “unit” or “module” used in this specification signifies one unit that processes at least one function or operation, and may be realized by hardware, software, or a combination thereof. The operations of the method or the functions described in connection with the forms disclosed herein may be embodied directly in a hardware or a software module executed by a processor, or in a combination thereof.”, [0038]).
“target position setting module” in claim(s) 1-6, described in Applicant’s specification as “Referring to FIG. 1, a device 10 for controlling an integrated memory system according to an embodiment may include…a target position setting module 13”, [0042], “The term “unit” or “module” used in this specification signifies one unit that processes at least one function or operation, and may be realized by hardware, software, or a combination thereof. The operations of the method or the functions described in connection with the forms disclosed herein may be embodied directly in a hardware or a software module executed by a processor, or in a combination thereof.”, [0038]).
“driver identification module” in claim(s) 1, 7-10, described in Applicant’s specification as “Referring to FIG. 1, a device 10 for controlling an integrated memory system according to an embodiment may include a driver identification module 11”, [0042], “The term “unit” or “module” used in this specification signifies one unit that processes at least one function or operation, and may be realized by hardware, software, or a combination thereof. The operations of the method or the functions described in connection with the forms disclosed herein may be embodied directly in a hardware or a software module executed by a processor, or in a combination thereof.”, [0038]).
“target position reproduction module” in claim(s) 1, described in Applicant’s specification as “Referring to FIG. 1, a device 10 for controlling an integrated memory system according to an embodiment may include…target position reproduction module 14.”, [0042], “The term “unit” or “module” used in this specification signifies one unit that processes at least one function or operation, and may be realized by hardware, software, or a combination thereof. The operations of the method or the functions described in connection with the forms disclosed herein may be embodied directly in a hardware or a software module executed by a processor, or in a combination thereof.”, [0038]).
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
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.
Claim(s) 11, 17-20 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Penilla et al. (US 20200249822 A1).
Regarding claim 11, Penilla teaches A method for controlling an integrated memory system (IMS), the method comprising:
collecting driver data for at least one potential driver, the driver data including position information of a device used by each of the at least one potential driver when driving a vehicle (“FIG. 14 describes the stepped flow of events 2000 as a user interacts with an APP 104, in this case, an HVAC APP 104. The GUI shown for APP 104 describes the first step 2002 where a user physically interacts with a sensor, screen, voice system etc. polling to see if an input has been received.”, [0209], Fig. 14);
performing clustering on the collected driver data (“Generation or analysis can be by way of overlap processes, cluster analysis algorithms, Connectivity based clustering, centroid-based clustering, clustering model most closely related to statistics is based on distribution models, cluster validation, density-based clustering, KNN/profile similarity, collaborative filtering, content-based filtering, hybrid recommender systems, mobile recommender systems, cross-sectional analysis, similarities in particular data types or settings, concentration in similar settings by particular demographics, and other similarity analysis calculators and aggregators. These settings can then be recommended to the user or can be automatically added to the profile.”, [0216], see also [0211-0214], Figs. 14-15);
setting a target position of the IMS for each of the at least one potential driver from a clustering result (“Recommender systems can the user the analyzed data to generate the custom recommendations for settings to users' profiles.”, [0216], see also [0211-0214], Figs. 14-15);
identifying a driver of the vehicle (“In operation 452, the user in the vehicle may be detected, and the face of the driver or other biometric data can be used to identify the specific user sitting in the car.”, [0180], “In operation 454, the user may be identified and the users profile can be automatically retrieved from cloud services and the user profile 160.”, [0181], Fig. 10); and
reproducing the set target position based on the identified driver of the vehicle (“The preferences settings for the user can be identified from the database in operation 456, and the settings can be applied in operation 458. The settings can be applied to the vehicle for the identified user.”, [0181], Fig. 10).
Regarding claim 17, Penilla teaches The method of claim 1, wherein
identifying the driver includes
receiving information on which driver drives the vehicle at a specific time (“FIG. 7 illustrates an example of a user (Bob) that may wish to utilize a car 200, in accordance with one embodiment of the present invention. For example, the car 200 may be a shared vehicle, such as those commonly shared in urban cities. Shared vehicles are those that belong to a company and where the company provides accounts to users to access the vehicles for specific trips, specific times, periods of time, etc.”, [0159]), and
identifying a corresponding driver for a current time as the driver of the vehicle based on the information (“Once the user has located a proximate vehicle, such as car 200, the user may approach the vehicle so as to utilize the vehicle 200. In one embodiment, when the user approaches the vehicle, and comes in close proximity to the vehicle as detected by the geo-location of the users mobile device, a pairing request can be detected.”, [0160]).
Regarding claim 18, Penilla teaches The method of claim 1, wherein
identifying the driver includes
receiving information on a driver behavior pattern (see “biometrics, login credentials,…voice detection, or combinations thereof.”, [0125] citation below), and
identifying a corresponding driver for the driver behavior pattern as the driver of the vehicle based on the information (“The user can be detected using biometrics, login credentials, image detection of the face, fingerprint detection, retina scans, etc. In some embodiments, biometrics can include data used to identify the user, such as face recognition, fingerprint reading, retina scans, voice detection, or combinations thereof.”, [0125]).
Regarding claim 19, Penilla teaches The method of claim 1, wherein
in identifying the driver,
the driver of the vehicle by using at least one of a driver condition monitoring device, a facial recognition device, a fingerprint recognition device, or a combination thereof (“IG. 10 illustrates a user (Bob) entering the vehicle, such as a shared vehicle 200, in accordance with one embodiment of the present invention. In this example, the user has been identified by the vehicle, such as using a camera 402. The camera 402 may use face detection 406 to automatically identify the user”, [0177]).
Regarding claim 20, Penilla teaches The method of claim 1, wherein
in identifying the driver,
identifying the driver of the vehicle by using a pressure sensor mounted on a driver seat (“the method further includes sending data for rendering on the user interface that indicates occupancy of selected ones of the one or more passenger seats of the vehicle as determined by sensors of the vehicle; wherein selection of the passenger seat is for one of the passenger seats that is indicated to be occupied…the sensors include one of a weight sensor, a heat sensor, a motion sensor, a sound sensor, an inertial sensor, a compression sensor, a camera sensor, a proximity sensor, or combinations of two or more thereof.”, [0035-0036]).
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.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 1, 7-10 is/are rejected under 35 U.S.C. 103 as being unpatentable over Penilla et al. (US 20200249822 A1).
Regarding claim 1, Penilla teaches A device for controlling an integrated memory system (IMS), the device comprising:
a driver data collection module configured to collect driver data for at least one potential driver, the driver data including position information of a device used by each of the at least one potential driver when driving a vehicle (“FIG. 14 describes the stepped flow of events 2000 as a user interacts with an APP 104, in this case, an HVAC APP 104. The GUI shown for APP 104 describes the first step 2002 where a user physically interacts with a sensor, screen, voice system etc. polling to see if an input has been received.”, [0209], Fig. 14);
a target position setting module configured to set a target position of the IMS for each of the at least one potential driver by performing clustering on the collected driver data (“Generation or analysis can be by way of overlap processes, cluster analysis algorithms, Connectivity based clustering, centroid-based clustering, clustering model most closely related to statistics is based on distribution models, cluster validation, density-based clustering, KNN/profile similarity, collaborative filtering, content-based filtering, hybrid recommender systems, mobile recommender systems, cross-sectional analysis, similarities in particular data types or settings, concentration in similar settings by particular demographics, and other similarity analysis calculators and aggregators. These settings can then be recommended to the user or can be automatically added to the profile. Recommender systems can the user the analyzed data to generate the custom recommendations for settings to users' profiles.”, [0216], see also [0211-0214], Figs. 14-15);
a driver identification module configured to identify a driver of the vehicle (“In operation 452, the user in the vehicle may be detected, and the face of the driver or other biometric data can be used to identify the specific user sitting in the car.”, [0180], “In operation 454, the user may be identified and the users profile can be automatically retrieved from cloud services and the user profile 160.”, [0181], Fig. 10); and
a target position reproduction module configured to reproduce the set target position based on the identified driver of the vehicle (“The preferences settings for the user can be identified from the database in operation 456, and the settings can be applied in operation 458. The settings can be applied to the vehicle for the identified user.”, [0181], Fig. 10).
Penilla does not explicitly teach the “driver data collection module”, “target position setting module”, “driver identification module”, and “target position reproduction module”, but instead teaches the computing is accomplished through a combination of servers and an on-board computer. However, it would have been obvious to one of ordinary skill in the art before the effective filing date to make these computing devices separate modules since it has been held that constructing a formerly integral structure in various elements involves only routine skill in the art. In re Dulberg, 289 F.2d 522, 523, 129 USPQ 348, 349 (CCPA 1961) (The claimed structure, a lipstick holder with a removable cap, was fully met by the prior art except that in the prior art the cap is "press fitted" and therefore not manually removable. The court held that "if it were considered desirable for any reason to obtain access to the end of [the prior art’s] holder to which the cap is applied, it would be obvious to make the cap removable for that purpose.").
Regarding claim 7, Penilla teaches The device of claim 1, wherein
the driver identification module is configured to
receive information on which driver drives the vehicle at a specific time (“FIG. 7 illustrates an example of a user (Bob) that may wish to utilize a car 200, in accordance with one embodiment of the present invention. For example, the car 200 may be a shared vehicle, such as those commonly shared in urban cities. Shared vehicles are those that belong to a company and where the company provides accounts to users to access the vehicles for specific trips, specific times, periods of time, etc.”, [0159]), and
identify a corresponding driver for a current time as the driver of the vehicle based on the information (“Once the user has located a proximate vehicle, such as car 200, the user may approach the vehicle so as to utilize the vehicle 200. In one embodiment, when the user approaches the vehicle, and comes in close proximity to the vehicle as detected by the geo-location of the users mobile device, a pairing request can be detected.”, [0160]).
Regarding claim 8, Penilla teaches The device of claim 1, wherein
the driver identification module is configured to
receive information on a driver behavior pattern (see “biometrics, login credentials,…voice detection, or combinations thereof.”, [0125] citation below), and
identify a corresponding driver for the driver behavior pattern as the driver of the vehicle based on the information (“The user can be detected using biometrics, login credentials, image detection of the face, fingerprint detection, retina scans, etc. In some embodiments, biometrics can include data used to identify the user, such as face recognition, fingerprint reading, retina scans, voice detection, or combinations thereof.”, [0125]).
Regarding claim 9, Penilla teaches The device of claim 1, wherein
the driver identification module is configured to identify the driver of the vehicle by using at least one of a driver condition monitoring device, a facial recognition device, a fingerprint recognition device, or a combination thereof (“IG. 10 illustrates a user (Bob) entering the vehicle, such as a shared vehicle 200, in accordance with one embodiment of the present invention. In this example, the user has been identified by the vehicle, such as using a camera 402. The camera 402 may use face detection 406 to automatically identify the user”, [0177]).
Regarding claim 10, Penilla teaches The device of claim 1, wherein
the driver identification module is configured to identify the driver of the vehicle by using a pressure sensor mounted on a driver seat (“the method further includes sending data for rendering on the user interface that indicates occupancy of selected ones of the one or more passenger seats of the vehicle as determined by sensors of the vehicle; wherein selection of the passenger seat is for one of the passenger seats that is indicated to be occupied…the sensors include one of a weight sensor, a heat sensor, a motion sensor, a sound sensor, an inertial sensor, a compression sensor, a camera sensor, a proximity sensor, or combinations of two or more thereof.”, [0035-0036]).
Claim(s) 6, 16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Penilla et al. (US 20200249822 A1) in view of Jain et al. (US 10214118 B1).
Regarding claim 6, and similarly claim 16, Penilla teaches The device of claim 1, wherein
However, Jain teaches
the target position setting module configured to stop the reproduction when receiving a driver input while reproducing the target position (“a manual override switch 499 is located within an arm length reach of the passengers in the front and rear seat as well as the driver…The manual override switch 499 since activated or deactivated by a manual operation by the passenger or driver provides an immediate way by a quick action of a physical touch movement to deactivate or activate the automated seat belt adjustment system and therefore provides enhanced protection to stop seat adjustments that may result in contact with the passengers.”, C13, lines 18-54).
Thus, it would have been obvious to one of ordinary skill in the art before the effective filing date to modify the invention of Penilla with the teachings of Jain such that the reproduction of the set target position of Penilla is canceled when a driver input is received during reproduction, as suggested by Jain, with a reasonable expectation of success. The motivation for doing so would be to “provide[] enhanced protection to stop seat adjustments that may result in contact with the passengers” (C13, lines 18-54), as taught by Jain.
Claim(s) 2, 4-5, 12, 14-15 is/are rejected under 35 U.S.C. 103 as being unpatentable over Penilla et al. (US 20200249822 A1) in view of Köhler et al. (US 20200180534 A1).
Regarding claim 2, and similarly claim 12, Penilla teaches The device of claim 1, wherein
However, Köhler teaches
the target position setting module is configured to set an average value of the driver data belonging to a cluster as the target position when the cluster is determined as a result of performing the clustering (“Thereafter, a (desired) vehicle setting is calculated 320 from the retrieved cluster item(s), i.e. from the retrieved setting(s). The calculating 320 of at least one occupant-specific vehicle setting 15 can comprise…calculating an average of a predefined number of vehicle settings 12 of the retrieved at least one cluster item”, [0050], see also “the calculating of at least one occupant-specific vehicle setting comprises…calculating an average or median or mode of a predefined (or predetermined) number of vehicle settings of the retrieved at least one cluster item, such as an average seat position or median or mode of seat positions, an average mirror position or median or mode of mirror positions, an average temperature setting or median or mode of temperature settings, etc.”, [0028], Figs. 1-2).
Thus, it would have been obvious to one of ordinary skill in the art before the effective filing date to modify the invention of Penilla with the teachings of Köhler such that the target position of Penilla is set as an average value of driver data of a cluster, as suggested by Köhler, with a reasonable expectation of success. The motivation for doing so would be to “vehicle item(s) can be set not only in accordance with the particular vehicle occupant, but also in accordance with further influencing factors” [0029], as taught by Köhler.
Regarding claim 4, and similarly claim 14, Penilla teaches The device of claim 1, wherein
However, Köhler teaches
the target position setting module is configured to set, as the target position, an average value of the most recent N data among the collected driver data when an amount of the collected driver data is insufficient to perform the clustering, wherein N is a natural number (“Thereafter, a (desired) vehicle setting is calculated 320 from the retrieved cluster item(s), i.e. from the retrieved setting(s). The calculating 320 of at least one occupant-specific vehicle setting 15 can comprise…calculating an average of a predefined number of vehicle settings 12 of the retrieved at least one cluster item”, [0050], see also “the calculating of at least one occupant-specific vehicle setting comprises…calculating an average or median or mode of a predefined (or predetermined) number of vehicle settings of the retrieved at least one cluster item, such as an average seat position or median or mode of seat positions, an average mirror position or median or mode of mirror positions, an average temperature setting or median or mode of temperature settings, etc.”, [0028], Figs. 1-2).
Thus, it would have been obvious to one of ordinary skill in the art before the effective filing date to modify the invention of Penilla with the teachings of Köhler such that the target position of Penilla is set as an average value of the most recent driver data if there’s insufficient data to perform the clustering, as suggested by Köhler, with a reasonable expectation of success. The motivation for doing so would be to “vehicle item(s) can be set not only in accordance with the particular vehicle occupant, but also in accordance with further influencing factors” [0029], as taught by Köhler.
Regarding claim 5, and similarly claim 15, Penilla teaches The device of claim 1, wherein
However, Köhler teaches
the target position setting module is configured to set the last collected driver data as the target position when an amount of the collected driver data is insufficient to perform the clustering (“Thereafter, a (desired) vehicle setting is calculated 320 from the retrieved cluster item(s), i.e. from the retrieved setting(s). The calculating 320 of at least one occupant-specific vehicle setting 15 can comprise determining the latest stored vehicle setting 12”, [0050], see also “the calculating of at least one occupant-specific vehicle setting comprises determining a latest stored vehicle setting”, [0028], Figs. 1-2).
Thus, it would have been obvious to one of ordinary skill in the art before the effective filing date to modify the invention of Penilla with the teachings of Köhler such that the target position of Penilla is set as the last collected driver data if there’s insufficient data to perform the clustering, as suggested by Köhler, with a reasonable expectation of success. The motivation for doing so would be to “vehicle item(s) can be set not only in accordance with the particular vehicle occupant, but also in accordance with further influencing factors” [0029], as taught by Köhler.
Allowable Subject Matter
Claim(s) 3 and 13 is/are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
The following is a statement of reasons for the indication of allowable subject matter: there is no prior art alone or in combination that discloses or teaches all the limitations of Applicant's claimed invention, including, and in combination with other recited limitations,
the target position setting module is configured to set a maximum or minimum value of the driver data belonging to a cluster as the target position when the cluster is determined as a result of performing the clustering (claim(s) 3),
in setting the target position, a maximum or minimum value of the driver data belonging to a cluster is set as the target position when the cluster is determined as a result of performing the clustering (claim(s) 13).
The closest prior art of record includes the following:
Regarding claim 3, and similarly claim 13, Penilla teaches The device of claim 1, wherein
As allowable subject matter has been indicated, applicant's reply must either comply with all formal requirements or specifically traverse each requirement not complied with. See 37 CFR 1.111(b) and MPEP § 707.07(a).
Conclusion
The prior art made of record and not relied upon is considered pertinent to Applicant's disclosure: See Notice of References Cited.
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/AMELIA VORCE/ Primary Examiner, Art Unit 3666