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
This Office action is in reply to filing by applicant on 01/23/2026.
Claims 1 – 3, 5, 9 – 12, 18, and 19 were amended by Applicant.
Claims 4, 6 – 8, 13 – 17, and 20 remain as original.
Claims 1 – 20 are currently pending and have been examined.
The prior 35 USC 101 claim rejections set forth in the Non-Final rejection of 10/24/2025 as to claims 9 – 17 are withdrawn in view of Applicant's arguments and amendments.
The prior 35 USC 103 claim rejections set forth in the Non-Final rejection of 10/24/2025 as to claims 1 – 21 are maintained in view of Applicant's arguments and amendments.
THIS ACTION IS MADE FINAL
Response to Arguments
There are no new grounds of rejection herein as to any of the claims.
Examiner notes that due to the substantial amendments by Applicant, new art combinations were needed to properly analyze the claims as amended. As such, Applicant’s arguments per 35 USC 103 are moot, as they address combinations no longer used in the analysis.
Generally as to obviousness, examiner submits that it is determined on the basis of the evidence as a whole and the relative persuasiveness of the arguments. See In re Oetiker, 977 F.2d 1443, 1445, 24 USPQ2d 1443, 1444 (Fed. Cir. 1992); In re Hedges, 783 F.2d 1038, 1039, 228 USPQ 685,686 (Fed. Cir. 1992); In re Piasecki, 745 F.2d 1468, 1472, 223 USPQ 785,788 (Fed. Cir. 1984); and In re Rinehart, 531 F.2d 1048, 1052, 189 USPQ 143,147 (CCPA 1976). Using this standard, examiner submits that the burden of presenting a prima facie case of obviousness was successfully established in the prior Office Action of 10/24/2025, and also respecting the pending amended claim set of 01/23/2026, as seen below.
Examiner recognizes that references cannot be arbitrarily altered or modified, and that there must be some reason why a person having ordinary skill in the relevant art would be motivated to make the proposed modifications. Although the motivation or suggestion to make modifications must be articulated, it is respectfully submitted that there is no requirement that the motivation to make modifications must be expressly articulated within the references themselves. References are evaluated by what they suggest to one versed in the art, rather than by their specific disclosures, In re Bozek, 163 USPQ 545 (CCPA 1969).
Examiner also notes that the motivation to combine the applied references is, where appropriate in the below detailed analysis pursuant to 35 USC 103, additionally accompanied by select passages from the respective references which specifically support that particular motivation. It is also respectfully submitted that motivation based on the logic and scientific reasoning of one ordinarily skilled in the art at the time of the invention, which evidence can also support a finding of obviousness, is otherwise provided in the detailed 35 USC 103 analysis of the claim set below. In re Nilssen, 851 F.2d 1401, 1403, 7 USPQ2d 1500, 1502 (Fed. Cir. 1988) (references do not have to explicitly suggest combining teachings); Ex parte Clapp, 227 USPQ 972 (Bd. Pat. App. & Inter. 1985) (examiner must present convincing line of reasoning supporting rejection); and Ex parte Levengood, 28 USPQ2d 1300 (Bd. Pat. App. & Inter. 1993) (reliance on logic and sound scientific reasoning).
Examiner recognizes that obviousness can only be established by combining or modifying the teachings of the prior art to produce the claimed invention where there is some teaching, suggestion, or motivation to do so found either in the references themselves or in the knowledge generally available to a person of ordinary skill in the art. See In re Fine, 837 F.2d 1071, 5 USPQ2d 1596 (Fed. Cir. 1988) and In re Jones, 958 F.2d 347.
Claim Rejections – 35 USC 103
In the event the determination of the status of the application as subject to AIA 35 USC 102 and 103 is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 USC 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 USC 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.
Claims 1, 2, 4 – 10, and 12 – 19 and 21, are rejected pursuant to 35 USC 103 as being unpatentable over Lavie (US20160133066A1) in view of Lim (US20210232704A1) and in further view of Ferrieres (US20150343993A1).
Examiner notes under the following 35 USC 103 analysis that the data storage, sending, receiving, predicting, and ID naming elements involved with maintaining a group / fleet of vehicles vis a vis this their respective maintenance paradigms are analyzed by Lavie / Ferrieres but the pseudonymous naming elements of such groups of vehicles are addressed in Lim.
Regarding claims 1, 9, 12, 18 (claim 1 reads on 9, 12, and 18):
Lavie discloses:
one or more computing processors and memories for executing computer- executable instructions to implement a vehicle data service, wherein the vehicle data service is configured to: (“In some embodiments, the present invention includes a computer program product which is a non-transitory storage medium (media) having instructions stored thereon/in which can be used to program a computer to perform any of the processes of the present invention. The storage medium can include, but is not limited to, any type of disk including floppy disks, optical discs, DVD, CD-ROMs, micro drive, and magneto-optical disks, ROMs, RAMs, EPROMs, EEPROMs, DRAMs, VRAMs, flash memory devices, magnetic or optical cards, nanosystems (including molecular memory ICs), or any type of media or device suitable for storing instructions and/or data.”, [0134]);
receive vehicle data from a plurality of vehicles, … Examiner notes that Lavie clearly encompasses a plurality of vehicles, … (“The maintenance review module 110 receives all the pertinent information concerning vehicle usage and driving conditions, categorizes the information; inputs the information into a predictive function (statistical correlation), then predicts required maintenance and service and optionally, the anticipated cost.”, [043]) and (“Embodiments of the invention are generally related to systems and methods to predict vehicle part longevity based on historical records and sensor output. Another object of the invention is to schedule maintenance to reduce catastrophic failure and maximize uptime of vehicles. In an embodiment, the system monitors in-vehicle sensor output acquired during vehicle operation, and then compares that output with a database of information on previous similar vehicles operating under similar conditions”, [004]) and (“In the historical vehicle maintenance and service database, there must exist actual maintenance and service records for many vehicles.” [0102]) and (“Based on the amount of vehicles within a geographic area, and the other factors that go into the predictive model/s, the amount of parts that need to be on hand at any given time can be predicted.”, [0130]) and see claim 6, published 5/12/2016).
store the vehicle data to a vehicle data store; (“Once an initial database is configured and populated, statistical correlations are formulated based on the historic information in order to develop predictive model for required maintenance for a given vehicle, or class of vehicles or particular components common to numerous types of vehicles. In operation, an in-vehicle data collection model 102 comprises a sensor interface capable of receiving and storing data from sensors within the vehicle or part of the vehicle. The data collection module can communicate with a maintenance review module 110 which can either be located in the vehicle or remote to the vehicle. Communication can be either by wired or wireless methods. In addition the maintenance review module 110 can acquire information from external sensors networks such as weather feeds and traffic.”, [043]);
analyze the stored vehicle data for a prognostication of vehicles associated with the pseudonymous identifiers; Examiner broadly interprets this limitation to include the meaning that the above noted stored vehicle data may be analyzed at least so that it can predict something or the other about this or that vehicle within the pertinent group, for example, predicting (i.e., prognosticating) that a vehicle needs maintenance, again noting that the pseudonymous aspects of this claim are treated below in Lim … (“In an embodiment of this invention, it is an object to create a better method of predicting parts longevity as well as predicting required maintenance of vehicles and vehicle …” [009], and see Fig. 1 and see Abstract, published 5/12/2016]);
receive, from one or more vehicles of the plurality of vehicles, a request for an issuance of vehicle directives by pseudonym identifiers corresponding to the prognostication; and
receive a request for an issuance of vehicle directives by pseudonym identifiers [which identifiers are addressed below by the secondary reference as above noted] corresponding to the prognostication of the vehicles; and Examiner broadly interprets this limitation (sans pseudonyms, as noted above) to include the meaning that the server can receive a prognostications / directives requesting for example a maintenance mission, … (“In operation, an in-vehicle data collection model 102 comprises a sensor interface capable of receiving and storing data from sensors within the vehicle or part of the vehicle. The data collection module can communicate with a maintenance review module 110 which can either be located in the vehicle or remote to the vehicle. Communication can be either by wired or wireless methods. In addition the maintenance review module 110 can acquire information from external sensors networks such as weather feeds and traffic.”, [043]) and (“an in-vehicle transceivers in the vehicle and similar vehicles configured to transmit at least one of the collected information and derivatives of the collected information to the maintenance and service review module and to receive from the maintenance and service review module, one of new and updated statistical correlations.”, [claim 6, published May 12, 2016]);
post vehicle directives, Examiner broadly interprets this limitation to include the meaning that it includes the creation / display of (aka, posting) info associated with a request / directive regarding one of the vehicles in the group, … (“An analysis continually happens within the estimator module 210 and if a correlation is found between the sensor information and required maintenance or repair, then the event is noted and optionally displayed 212 to the driver …”, [044]);
Lavie does not expressly disclose, but Lim teaches:
wherein the vehicle data is associated with pseudonymous identifiers; (“A system for collecting and managing vehicle-generated data from multiple vehicles are provided. The vehicle-generated data is pseudonymized by pseudonymized identifiers, and the pseudonymized vehicle-generated data is collected and managed by a neutral data server operated by an operator who is independent of vehicle manufacturers. Vehicle manufacturers can reestablish the link of the pseudonymized event data with the vehicle that had generated the event data and the vehicle driver.”, [Abstract, published 7/29/2021]) and (“According to at least one aspect, the present disclosure provides a method of operating a vehicle to process vehicle-generated data. The method may include applying a hash function to a combination of a first salt and personally identifiable information that uniquely identifies a driver to generate a driver pseudonymized identifier, and applying the hash function to a combination of a second salt and a vehicle identification information that uniquely identifies the vehicle to generate a vehicle pseudonymized identifier, and transmitting a salt generation information for a reconstruction of the first salt and the second salt to a vehicle manufacturer server having the personally identifiable information and the vehicle identification information, and transmitting pseudonymized vehicle-generated data identified by the driver pseudonymized identifier and the vehicle pseudonymized identifier to a data server operated by an operator who is independent of a vehicle manufacturer of the vehicle.”, [006]);
wherein the vehicle directives include a set of pseudonymous identifiers associated with the request, and (“Vehicle manufacturers, under the law or court order, or with the consent of the vehicle owner or driver, may reestablish the link of the pseudonymized event data with the vehicle that had generated the event data and the vehicle owner/driver.”, [030]);
It would have been obvious to one of ordinary skill in the art before the effective filing date of this application to have modified Lavie to incorporate the teachings of Lim because Lavie could better protect the privacy of vehicle owners by using a vehicle pseudonym (i.e., “alias”) naming paradigm to identify each of its vehicles in the fleet as was done in Lim . (“The pseudonymized vehicle-generated data stored in the data server does not contain any meaningful information that enables a third party to identify the vehicle or individual involved and may be freely used without compromising the privacy of the individual.”, see Lim at [030]).
The combination of Lavie and Lim does not expressly disclose, but Ferrieres teaches:
wherein the vehicle data service is configured to authorize the request for the issuance of vehicle directives prior to issuance of the vehicle directives. (“According to another advantageous feature of the method for making a vehicle available according to the invention, said remote vehicle management server sends said message authorizing the starting of said vehicle only when said remote user server has received from said user a value of a variable parameter relating to said vehicle, and said value corresponds to a value previously recorded by said remote vehicle management server or by said remote user server.”, [022]);
It would have been obvious to one of ordinary skill in the art before the effective filing date of this application to have modified Lavie to incorporate the teachings of Ferrieres because Lavie could tighten up and otherwise take positive steps concerning security by better ensuring that authorization for vehicle use occurred before vehicle directives (to start, for example) were given as done in Ferrieres . (“Thus, the starting [a vehicle directive] authorization is given by the control system of an engine of the vehicle only when the user supplies the remote user server with a value relating to the vehicle such as the mileage displayed on the vehicle odometer, or the vehicle fuel level, the charge level of a traction battery of the vehicle. This provides for re-identifying the user when this authorization is given, and for giving this authorization when the user is close to or even inside the vehicle, since the value to be provided requires viewing the instrument panel of the vehicle.” see Ferrieres at [ 023]).
Regarding claims 2, 10, 19:
The combination of Lavie, Lim, and Ferrieres disclose the limitations of claims 1, 9, and 18, respectively:
Lavie further teaches:
grouping vehicles based on criteria; (“Maintenance or service must be classified or grouped together, so that information based on observed parameters recorded in an historical maintenance and service database can be used to predict and assess maintenance and service requirements for vehicle in operation currently.”, [033]);
monitoring the vehicle data received from the vehicles in the groups; (“Embodiments of the invention are generally related to systems and methods to predict vehicle part longevity based on historical records and sensor output. Another object of the invention is to schedule maintenance to reduce catastrophic failure and maximize uptime of vehicles. In an embodiment, the system monitors in-vehicle sensor output acquired during vehicle operation, and then compares that output with a database of information on previous similar vehicles operating under similar conditions to predict parts ware.”, [004])
performing the vehicle prognostication for vehicles in the groups; and (“In an embodiment of this invention, it is an object to create a better method of predicting parts longevity as well as predicting required maintenance of vehicles and vehicle parts.”, [009]);
and Lim further teaches:
generating vehicle prognostication result associated with the pseudonym identifiers. (“Vehicle manufacturers, under the law or court order, or with the consent of the vehicle owner or driver, may reestablish the link of the pseudonymized event data with the vehicle that had generated the event data and the vehicle owner/driver.”, [030]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of this application to have modified Lavie to incorporate the teachings of Lim because Lavie could better protect the privacy of vehicle owners by using a vehicle pseudonym (i.e., “alias”) naming paradigm to identify each of its vehicles in the fleet as was done in Lim . (“The pseudonymized vehicle-generated data stored in the data server does not contain any meaningful information that enables a third party to identify the vehicle or individual involved and may be freely used without compromising the privacy of the individual.”, see Lim at [030]).
Regarding claims 4, 13, and 21:
The combination of Lavie, Lim, and Ferrieres disclose the limitations of claims 1, 9, and 18, respectively:
Lavie further teaches:
wherein the vehicle directives include commands that are executed by the vehicle in a response to identifying the vehicle directives associated with the vehicle, such as diagnostics, repairs, or updating processes. (“It is further object of this invention to both stock and reserve parts and consumables that are anticipated to be needed based on monitoring of vehicle usage and prediction of maintenance and service requirements.”, [034]).
Regarding claims 5 and 14:
The combination of Lavie, Lim, and Ferrieres disclose the limitations of claims 1 and 9, respectively:
Lim further teaches:
wherein the pseudonymous identifier is corresponding to one of variety of unique or semi-unique identifier associated with each vehicle of the plurality of vehicles. (“The driver pseudonymized identifier may be generated by applying a cryptographic hash function to a combination of personally identifiable information (PII) that uniquely identifies an individual, i.e., the owner or driver of the vehicle and a salt that is a random string. The PII, or personally identifiable information may be, for example, an individual's resident registration number or social security number, a driver's license number, a mobile phone number, a unique identifier assigned to an individual's fob key associated with the vehicle, or an individual's assigned user ID from the VM server 20.”, [046]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of this application to have modified Lavie to incorporate the teachings of Lim because Lavie could better protect the privacy of vehicle owners by using a vehicle pseudonym (i.e., “alias”) naming paradigm to identify each of its vehicles in the fleet as was done in Lim . (“The pseudonymized vehicle-generated data stored in the data server does not contain any meaningful information that enables a third party to identify the vehicle or individual involved and may be freely used without compromising the privacy of the individual.”, see Lim at [030]).
Regarding claims 6 and 15:
The combination of Lavie, Lim, and Ferrieres disclose the limitations of claims 1 and 9, respectively:
Lavie further teaches:
wherein each vehicle of the plurality of vehicles includes a plurality of sensors, components, and data stores for obtaining, generating, and maintaining the vehicle data. (“In operation, an in-vehicle data collection model 102 comprises a sensor interface capable of receiving and storing data from sensors within the vehicle or part of the vehicle. The data collection module can communicate with a maintenance review module 110 which can either be located in the vehicle or remote to the vehicle. Communication can be either by wired or wireless methods).”, [043]).
Regarding claims 7 and 16:
The combination of Lavie, Lim, and Ferrieres disclose the limitations of claims 1 and 9, respectively:
Lim further teaches:
wherein the posted vehicle directives is publishing the vehicle directives and associated set of pseudonymous identifiers. (“Vehicle manufacturers, under the law or court order, or with the consent of the vehicle owner or driver, may reestablish the link of the pseudonymized event data with the vehicle that had generated the event data and the vehicle owner/driver.”, [030]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of this application to have modified Lavie to incorporate the teachings of Lim because Lavie could better protect the privacy of vehicle owners by using a vehicle pseudonym (i.e., “alias”) naming paradigm to identify each of its vehicles in the fleet as was done in Lim . (“The pseudonymized vehicle-generated data stored in the data server does not contain any meaningful information that enables a third party to identify the vehicle or individual involved and may be freely used without compromising the privacy of the individual.”, see Lim at [030]).
Regarding claims 8 and 17:
The combination of Lavie, Lim, and Ferrieres disclose the limitations of claims 1 and 9, respectively:
Lavie further teaches:
perform a vehicle data transmission to the vehicle data service; and request vehicle directives from the vehicle data service. (“Additional functionality of the accident review module in embodiments can do one or more of determining the availability of parts, materials and labor and/or request bids for each from providers that have the part/s, materials or time.”, [0128]); and
and Lim further teaches
perform a pseudonymous identifiers management, wherein each of the pseudonymous identifiers is associated with an individual vehicle; (“As described above, according to the present disclosure, in the VM server 20 and the neutral server 30 operated by operators who are independent of each other, pseudonymized event data and information that may generate pseudonymized identifiers are stored separately from each other. As described above, the vehicle-generated data management system 100 of FIG. 1 may be configured to apply event data, and also to other types of vehicle-generated data generated, recorded, or stored in other types of devices than the EDR in the vehicle in relation to vehicle operation or driver behavior. In some exemplary embodiments, vehicle-generated data may be periodically transmitted to the neutral server 30.”, [045]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of this application to have modified Lavie to incorporate the teachings of Lim because Lavie could better protect the privacy of vehicle owners by using a vehicle pseudonym (i.e., “alias”) naming paradigm to identify each of its vehicles in the fleet as was done in Lim . (“The pseudonymized vehicle-generated data stored in the data server does not contain any meaningful information that enables a third party to identify the vehicle or individual involved and may be freely used without compromising the privacy of the individual.”, see Lim at [030]).
Claims 3, 11, and 20 are rejected pursuant to 35 USC 103 as being unpatentable over Lavie (US20160133066A1) in view of Lim (US20210232704A1) in further view of Ferrieres (US20150343993A1) and in further view of Ho (US9430882B2).
Regarding claims 3, 11, and 20:
The combination of Lavie, Lim, and Ferrieres disclose the limitations of claims 2, 10, and 19, respectively:
That combination does not expressly disclose, but Ho teaches:
wherein the vehicle prognostication is performed using a machine learned component, wherein the machine learned component includes at least vehicle prognostication algorithms and training algorithms. (“The present invention provides a system that combines repair and maintenance failure data with real-time telematics sensor data in a way that allows machine learning and stochastic predictive models to be applied to data collected from groups of like vehicles across different fleets, for the purpose of optimizing fleet maintenance costs by providing a prediction as to when it would be most cost effective to perform preventive replacement work, …”, [col. 2: 40 – 47]) and (“By embedding Stochastic modeling directly within the logical multi-tenant database, the system of the invention can model data and apply machine learning techniques to determine whether maintenance optimization changes are necessary at the point of data capture.”, [col. 3: 60 – 64]) and (“According to the invention, the database is modified so that as data is stored it is processed by embedded stochastic predictive modeling algorithms which access the data within the database, compare the data to historical comparators, and return a prediction model to the data provider (the user), in real time.”, [col. 3: 29 – 34]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of this application to have modified Lavie to incorporate the teachings of Ho because Lavie could better learn this or that thing about the specific vehicle data that it was processing via machine learning as was done in Ho. (“the system of the invention can model data and apply machine learning techniques to determine whether maintenance optimization changes are necessary “, [col. 3: 59 – 64]).
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 extension fee 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.
The following prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Please see attached form 892.
Kleve (US20110230165A1) – A vehicle tracking system includes a remote portable wireless device. The system also includes a wireless transceiving device included in each of a plurality of vehicles, the wireless transceiving device in communication with a GPS device. The system further includes a server, capable of communicating with both the remote portable wireless device and each wireless transceiving device. The at least one server may receive a plurality of vehicle selections from the remote portable wireless device. The server may also determine a vehicle that corresponds to each of the plurality of selections, including a cellular phone number for each determined vehicle. The server may further transmit tracking instructions to each determined vehicle and receive GPS coordinates from each vehicle. The server may compare the received coordinates from each vehicle and report a deviance beyond a predetermined threshold to the remote portable wireless device.
Grover (US20160116293A1) - A vehicle computer system in an autonomous vehicle includes a wireless transceiver configured to communicate with a remote device. The vehicle computer system also includes a processor in communication with the wireless transceiver. The processor is configured to receive instructions from the remote device to initiate an automatic valet-mode, receive data from the remote device indicative of a user's pick-up location, and send instructions to a vehicle module instructing the vehicle to drive to the user's pick-up location.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MATTHEW COBB whose telephone number is (571) 272-3850. The examiner can normally be reached 9 - 5, M - F.
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 call examiner Cobb as above, or 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, Peter Nolan, can be reached at (571) 270-7016. The fax phone number for the organization where this application or proceeding is assigned is (571) 273-8300.
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/MATTHEW COBB/Examiner, Art Unit 3661
/PETER D NOLAN/Supervisory Patent Examiner, Art Unit 3661
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