DETAILED ACTION
Status of the Application
This Non-Final Office Action is in response to Application Serial 18/186,407. Claims 1-20 are pending. Examiner notes the Application was suspended for three years.
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 . In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) 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.
Information Disclosure Statement
Applicant did not submit an information disclosure statements (IDS) to be considered by the examiner.
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.
Claim(s) 1-8 is/are process.
Claim(s) 9-15 is/are machine.
Claim(s) 16-20 is/are manufacture.
The claims (claim 1 and similarly claim 9 and claim 16) recite, “… monitoring vehicle service features …, wherein the vehicle service features are based on vehicle data captured …; monitoring … to determine transportation matching features …; generating, utilizing … , a notification … based on the vehicle service features … and the transportation matching features …; and providing the notification for display … wherein the notification comprises at least one of: a vehicle management notification, a transportation recommendation, or a transportation match notification indicating a transportation match with a provider computing device… .” The claims recite the abstract concept of matching vehicle services. The limitations recite certain methods of organizing human activity – managing personal behavior, commercial activities. Accordingly, the claims recite certain methods of organizing human activity, and thus, the claims are directed to an abstract idea under the first prong of Step 2A.
This judicial exception are not integrated into a practical application under the second prong of Step 2A. In particular, the claims recite the additional elements beyond the recited abstract idea of, “A computer-implemented method comprising”, “a plurality of service management computing devices”, “a plurality of provider computing devices, via a transportation matching application”, “a notification model”, “a transportation application of a client device”, “via a graphical user interface of the transportation application on the client device”; however, when viewed as an ordered combination, and pursuant to the broadest reasonable interpretation, each of the additional elements are computing elements recite adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer or merely uses a computer as a tool to perform an abstract idea – see MPEP 2106.05 (f).
The dependent claims do not recite additional elements that are not recited in the dependent
The Applicant is encouraged to clarify “ a notification module” see the instant specification [030].
Accordingly, the additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claims also fails to recite any improvements to another technology or technical field, improvements to the functioning of the computer itself, use of a particular machine, effecting transformation or reduction of a particular article to a different state or thing, and/or 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.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above, because the additional elements when considered both individually and as an ordered combination do not amount to significantly more. (See MPEP 2106.05 (f) Mere Instruction to Apply an Exception – Thus, for example, claims that amount to nothing more than an instruction to apply the abstract idea using a generic computer do not render an abstract idea eligible.” Alice Corp., 134 S. Ct at 235).
At Step 2B, it is MPEP 2106.05 (d) – Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information).
Examiner concludes that the additional elements in combination fail to amount to significantly more than the abstract idea based on findings that each element merely performs the same function (s) in combination as each element performs separately. The claim is not patent eligible. Thus, taken alone, the additional elements do not amount to significantly more than the above-identified exception (the abstract idea). Looking at the limitation as an ordered combination adds nothing that is not already present when looking at the elements taken individually.
Dependent claims 2-8 further narrow the abstract idea of independent claim 1. The claims 1-8 are not patent eligible.
Dependent claims 10-15 further narrow the abstract idea of independent claim 9. The claims 9-15 are not patent eligible.
Dependent claims 17-20 further narrow the abstract idea of independent claim 9. The claims 16-20 are not patent eligible.
Moreover, aside from the aforementioned additional elements, the remaining elements of dependent claims 2-8, 10 -15, 17-20 do not transform the recited abstract idea into a patent eligible invention because these claims merely recite further limitations that provide no more than simply narrowing the recited abstract idea.
Since there are no limitations in these claims that transform the exception into a patent eligible application such that these claims amount to significantly more than the exception itself, claims 1-20 are rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
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) 1, 2, 4, 5, 7, 9, 10, 12, 13, 16, 17 and 20 is/are rejected under 35 U.S.C. 102(a)(1) and 102(a)(2) as being anticipated by Hinduja (WO 2022/0,911,120 A1).
Regarding Claim 1,
A computer-implemented method comprising: monitoring vehicle service features from a plurality of service management computing devices, wherein the vehicle service features are based on vehicle data captured by the plurality of service management computing devices;
Hinduja [abstract] teaches a method for dynamic maintenance scheduling includes receiving, by a server, first maintenance data, first vehicle data, first booking data, and a plurality of maintenance plans associated with a plurality of vehicles., Hinduja [abstract],
Hinduja [p.3 lines 16-19] discloses the server is further configured to determine a plurality of features and a corresponding plurality of feature values for each of the plurality of vehicles based on the first maintenance data, the first vehicle data, the first booking data, and the plurality of maintenance plans. The server is further configured to train a prediction model based on the plurality of features and the corresponding plurality of feature values.
Hinduja [p.4 lines 9-20] teaches features include a meantime between consecutive failures of a vehicle, a count of major accidents, a count of non-scheduled maintenance, and thus, Hinduja teaches vehicle service features.
Hinduja [p.8 lines 24-30] teaches the booking data may be further indicative of utilization and inactivity period of each vehicle 102a-102d. For example, the booking data of a vehicle may indicate whether the vehicle is overutilized, under-utilized, or as expected utilized. Over-utilization of the vehicle may negatively impact the health of the vehicle and may warrant unnecessary scheduled maintenances.
monitoring a plurality of provider computing devices, via a transportation matching application, to determine transportation matching features for the plurality of provider computing devices;
Hinduja [p. 5 lines 6-10] disclose FIG. 1A is a block diagram that illustrates a system environment 100A for dynamic maintenance scheduling for vehicles. The system environment 100 A includes a plurality of vehicles 102a-102d, an application server 104, a database server 106, a maintenance center 108 having a maintenance system 110, and a communication network 112., Hinduja [Figure 1A], [Figure 2A], [p. 5 lines 6-10].
Hinduja [p.8 lines 20-23] teaches driver device may include a mobile phone, a smartphone, a laptop, a tablet, a phablet, or the like. The database server 106 may receive the first booking data from the transportation service provider associated with the plurality of vehicles 102a-102d. Hinduja [p.8 lines 20-23], and thus, Hinduja teaches transportation matching application.
Hinduja [p.8 lines 9-20] teaches booking one or more passenger for rides. Database server 106 may receive real-time booking data of the plurality of vehicles 102a-102d., Hinduja [Figure 1A]. Hinduja teaches database server 106, and thus, Hinduja teaches transportation matching.
generating, utilizing a notification model, a notification for a transportation application of a client device based on the vehicle service features from the plurality of service management computing devices and the transportation matching features for the plurality of provider computing devices;
Hinduja [abstract] teaches the method includes training a prediction model based on the plurality of features and the corresponding feature values.
Hinduja [p.3 lines 19-24] teaches a prediction model based on the plurality of features and the corresponding plurality of feature values. The server is further configured to determine a maintenance criterion for a target vehicle based on the trained prediction model and a target dataset associated with the target vehicle. Hinduja teaches a prediction model, and thus, Hinduja teaches a notification model.
and providing the notification for display via a graphical user interface of the transportation application on the client device, wherein the notification comprises at least one of: a vehicle management notification, a transportation recommendation, or a transportation match notification indicating a transportation match with a provider computing device.
Hinduja [p. 33 lines 22-26] teaches the processing circuitry 206 may be further configured to communicate the scheduled maintenance ticket to the driver device 218 of the target vehicle 216. Hinduja [Figure 2B item 218], Hinduja [p. 33 lines 22-26].
Within claim 1, Hinduja discloses booking and a vehicle communication with a transportation database server, and thus, vehicle management notification, a transportation recommendation, or a transportation match notification indicating a transportation match with a provider computing device. Claim 1 a "Markush" claim recites a list of alternatively useable members. In re Harnisch, 631 F.2d 716, 719-20, 206 USPQ 300, 303 (CCPA 1980); Ex parte Markush, 1925 Dec. Comm'r Pat. 126, 127 (1924). The listing of specified alternatives within a Markush claim is referred to as a Markush group or a Markush grouping. Abbott Labs v. Baxter Pharmaceutical Products, Inc., 334 F.3d 1274, 1280-81, 67 USPQ2d 1191, 1196 (Fed. Cir. 2003) (citing to several sources that describe Markush groups)- See MPEP 706.03.
Regarding Claim 2,
The computer-implemented method of claim 1, wherein generating, utilizing the notification model, the notification further comprises utilizing a machine learning model to generate the notification based on the vehicle service features and the transportation matching features.
Similar to claim 1. Hinduja [p.3 lines 19-24] teaches a prediction model based on the plurality of features and the corresponding plurality of feature values. The server is further configured to determine a maintenance criterion for a target vehicle based on the trained prediction model and a target dataset associated with the target vehicle. Hinduja teaches a prediction model, and thus, Hinduja teaches a notification model. Hinduja [p.3 lines 19-24], [abstract].
Regarding Claim 4,
The computer-implemented method of claim 1, further comprising: determining, the vehicle service features by determining at least one of vehicle maintenance patterns, vehicle maintenance costs, vehicle repair down-times, service vehicle types, vehicle accident information, or vehicle service station availability.
Hinduja [abstract] teaches a method for dynamic maintenance scheduling includes receiving, by a server, first maintenance data, first vehicle data, first booking data, and a plurality of maintenance plans associated with a plurality of vehicles., Hinduja [abstract],
Hinduja [p.3 lines 16-19] discloses the server is further configured to determine a plurality of features and a corresponding plurality of feature values for each of the plurality of vehicles based on the first maintenance data, the first vehicle data, the first booking data, and the plurality of maintenance plans. The server is further configured to train a prediction model based on the plurality of features and the corresponding plurality of feature values.
(Hinduja teaches first maintenance data, the first vehicle data, the first booking data, and the plurality of maintenance plans.); (The labels maintenance patterns, vehicle maintenance costs, vehicle repair down-times, service vehicle types, vehicle accident information, or vehicle service station availability are merely names and labels indicating a particular function and do not alter the structure or function of the claimed invention, accordingly these limitations (names and labels) do not patentability distinguish the claims from the cited prior art.)
Within claim 4, Hinduja discloses first maintenance data, the first vehicle data, the first booking data, and the plurality of maintenance plans, and thus, disclose at least one of vehicle maintenance patterns, vehicle maintenance costs, vehicle repair down-times, service vehicle types, vehicle accident information, or vehicle service station availability. Claim 4 a "Markush" claim recites a list of alternatively useable members. In re Harnisch, 631 F.2d 716, 719-20, 206 USPQ 300, 303 (CCPA 1980); Ex parte Markush, 1925 Dec. Comm'r Pat. 126, 127 (1924). The listing of specified alternatives within a Markush claim is referred to as a Markush group or a Markush grouping. Abbott Labs v. Baxter Pharmaceutical Products, Inc., 334 F.3d 1274, 1280-81, 67 USPQ2d 1191, 1196 (Fed. Cir. 2003) (citing to several sources that describe Markush groups)- See MPEP 706.03.
Regarding Claim 5,
The computer-implemented method of claim 1, wherein monitoring a plurality of provider computing devices to determine transportation matching features further comprises monitoring at least one of transportation matching vehicle telematics data, transportation matching driver ratings, transportation matching vehicle types transportation matching driving route patterns, number of transportation matching provider devices for a geographic region, number of transportation matching requester devices for a geographic region, or provider transportation matching schedules.
Hinduja [p. 9 line 15-16] discloses the vehicle data of the plurality of vehicles 102a-102d may be indicative of information pertaining a region of operation of each vehicle 102a-102 and [p.10 lines 23-26] the database server 106 may receive the vehicle data from a corresponding driver device, the telematics device., Hinduja [p. 9 line 15-16], [p.10 lines 23-26].
Hinduja [p. 17 line 5-24] teaches the count of non-scheduled maintenance sessions of the vehicle may be further indicative of an additional cost that is being borne by the transportation service provider due to poor health and additional downtime of the vehicle. In one example, the vehicle 102a may be two years old and may have undergone 6 scheduled maintenance sessions in the two years of use. However as per the maintenance data or records of the vehicle 102a, the vehicle 102a has undergone 10 maintenance sessions., Hinduja [p. 17 lines 5-24], [p.20 lines 12-15].
Within claim 5, Hinduja discloses a region of operation and receive the vehicle data from a corresponding driver device, the telematics device, count of repairs, and thus, discloses geographic region of operation and matching vehicle telematics data, and provider transportation matching schedules. Claim 5 a "Markush" claim recites a list of alternatively useable members. In re Harnisch, 631 F.2d 716, 719-20, 206 USPQ 300, 303 (CCPA 1980); Ex parte Markush, 1925 Dec. Comm'r Pat. 126, 127 (1924). The listing of specified alternatives within a Markush claim is referred to as a Markush group or a Markush grouping. Abbott Labs v. Baxter Pharmaceutical Products, Inc., 334 F.3d 1274, 1280-81, 67 USPQ2d 1191, 1196 (Fed. Cir. 2003) (citing to several sources that describe Markush groups)- See MPEP 706.03
Regarding Claim 7,
The computer-implemented method of claim 1, wherein generating the notification comprises generating the transportation recommendation by selecting between a personal vehicle corresponding to the client device or a set of transportation matching vehicles based on the vehicle service features from the plurality of service management computing devices and the transportation matching features for the plurality of provider computing devices.
Similar to claim 1. Hinduja [p. 17 line 5-24], [p.8 lines 10-23], [Figure 1A ], [Figure 2A] teaches booking transportation service.
Within claim 7, Hinduja discloses booking and a vehicle communication with a transportation database server, and thus, discloses a set of transportation matching vehicles based on the vehicle service features from the plurality of service management computing devices and the transportation matching features for the plurality of provider computing devices. Claim 7 a "Markush" claim recites a list of alternatively useable members. In re Harnisch, 631 F.2d 716, 719-20, 206 USPQ 300, 303 (CCPA 1980); Ex parte Markush, 1925 Dec. Comm'r Pat. 126, 127 (1924). The listing of specified alternatives within a Markush claim is referred to as a Markush group or a Markush grouping. Abbott Labs v. Baxter Pharmaceutical Products, Inc., 334 F.3d 1274, 1280-81, 67 USPQ2d 1191, 1196 (Fed. Cir. 2003) (citing to several sources that describe Markush groups)- See MPEP 706.03.
Regarding Claim 9,
A system comprising: at least one processor; and a non-transitory computer readable storage medium comprising instructions that, when executed by the at least one processor, cause the system to: monitor, vehicle service features from a plurality of service management computing devices, wherein the vehicle service features are based on vehicle data captured by the plurality of service management computing devices; monitor a plurality of provider computing devices, via a transportation matching application, to determine transportation matching features for the plurality of provider computing devices; generate, utilizing a notification model, a notification for a transportation application of a client device based on the vehicle service features from the plurality of service management computing devices and the transportation matching features for the plurality of provider computing devices; and provide the notification for display via a graphical user interface of the transportation application on the client device, wherein the notification comprises at least one of: a vehicle management notification, a transportation recommendation, or a transportation match notification indicating a transportation match with a provider computing device.
Similar to Claim 1.
Hinduja [abstract] , [p.3 lines 16-24] , [p.4 lines 9-20] , [p.8 lines 8-30], [p. 5 lines 6-10], [Figure 1A], [Figure 2A]., Hinduja [p. 33 lines 22-26], [Figure 2B item 218].
Within claim 9, Hinduja discloses booking and a vehicle communication with a transportation database server, and thus, vehicle management notification, a transportation recommendation, or a transportation match notification indicating a transportation match with a provider computing device. Claim 9 a "Markush" claim recites a list of alternatively useable members. In re Harnisch, 631 F.2d 716, 719-20, 206 USPQ 300, 303 (CCPA 1980); Ex parte Markush, 1925 Dec. Comm'r Pat. 126, 127 (1924). The listing of specified alternatives within a Markush claim is referred to as a Markush group or a Markush grouping. Abbott Labs v. Baxter Pharmaceutical Products, Inc., 334 F.3d 1274, 1280-81, 67 USPQ2d 1191, 1196 (Fed. Cir. 2003) (citing to several sources that describe Markush groups)- See MPEP 706.03.
Regarding Claim 10,
The system of claim 9, further comprises instructions that, when executed by the at least one processor, cause the system to: utilize a machine learning model to generate the notification based on the vehicle service features and the transportation matching features.
Similar to claim 10. Hinduja [p.3 lines 19-24], [abstract].
Regarding Claim 12,
The system of claim 9, further comprising instructions that, when executed by the at least one processor, cause the system to determine, the vehicle service features by determining at least one of vehicle maintenance patterns, vehicle maintenance costs, vehicle repair down-times, determining, vehicle service features further comprises determining at least one of service vehicle types, vehicle accident information, or vehicle service station availability.
Hinduja [abstract], [p.3 lines 16-19].
(Hinduja teaches first maintenance data, the first vehicle data, the first booking data, and the plurality of maintenance plans.); (The labels maintenance patterns, vehicle maintenance costs, vehicle repair down-times, service vehicle types, vehicle accident information, or vehicle service station availability are merely names and labels indicating a particular function and do not alter the structure or function of the claimed invention, accordingly these limitations (names and labels) do not patentability distinguish the claims from the cited prior art.)
Within claim 4, Hinduja discloses first maintenance data, the first vehicle data, the first booking data, and the plurality of maintenance plans, and thus, disclose at least one of vehicle maintenance patterns, vehicle maintenance costs, vehicle repair down-times, service vehicle types, vehicle accident information, or vehicle service station availability. Claim 4 a "Markush" claim recites a list of alternatively useable members. In re Harnisch, 631 F.2d 716, 719-20, 206 USPQ 300, 303 (CCPA 1980); Ex parte Markush, 1925 Dec. Comm'r Pat. 126, 127 (1924). The listing of specified alternatives within a Markush claim is referred to as a Markush group or a Markush grouping. Abbott Labs v. Baxter Pharmaceutical Products, Inc., 334 F.3d 1274, 1280-81, 67 USPQ2d 1191, 1196 (Fed. Cir. 2003) (citing to several sources that describe Markush groups)- See MPEP 706.03.
Regarding Claim 13,
The system of claim 9, further comprising instructions that, when executed by the at least one processor, cause the system to monitor a plurality of provider computing devices to determine transportation matching features further comprises monitoring at least one of transportation matching vehicle telematics data, transportation matching driver ratings, transportation matching vehicle types transportation matching driving route patterns, number of transportation matching provider devices for a geographic region, number of transportation matching requester devices for a geographic region, or provider transportation matching schedules.
Hinduja [p. 9 line 15-16], [p.10 lines 23-26], [p. 17 lines 5-24], [p.20 lines 12-15].
Within claim 13, Hinduja discloses a region of operation and receive the vehicle data from a corresponding driver device, the telematics device, count of repairs, and thus, discloses geographic region of operation and matching vehicle telematics data, and provider transportation matching schedules. Claim 13, a "Markush" claim recites a list of alternatively useable members. In re Harnisch, 631 F.2d 716, 719-20, 206 USPQ 300, 303 (CCPA 1980); Ex parte Markush, 1925 Dec. Comm'r Pat. 126, 127 (1924). The listing of specified alternatives within a Markush claim is referred to as a Markush group or a Markush grouping. Abbott Labs v. Baxter Pharmaceutical Products, Inc., 334 F.3d 1274, 1280-81, 67 USPQ2d 1191, 1196 (Fed. Cir. 2003) (citing to several sources that describe Markush groups)- See MPEP 706.03
Regarding Claim 16,
A non-transitory computer readable storage medium comprising instructions that, when executed by at least one processor, cause the at least one processor to: monitor, vehicle service features from a plurality of service management computing devices, wherein the vehicle service features are based on vehicle data captured by the plurality of service management computing devices; monitor a plurality of provider computing devices, via a transportation matching application, to determine transportation matching features for the plurality of provider computing devices; generate, utilizing a notification recommendation model, a notification for a transportation application of a client device based on the vehicle service features from the plurality of service management computing devices and the transportation matching features for the plurality of provider computing devices; and provide the notification for display via a graphical user interface of the transportation application on the client device, wherein the notification comprises at least one of: a vehicle management notification, a transportation recommendation, or a transportation match notification indicating a transportation match with a provider computing device.
Similar to Claim 1.
Hinduja [abstract] , [p.3 lines 16-24] , [p.4 lines 9-20] , [p.8 lines 8-30], [p. 5 lines 6-10], [Figure 1A], [Figure 2A]., Hinduja [p. 33 lines 22-26], [Figure 2B item 218].
Within claim 16, Hinduja discloses booking and a vehicle communication with a transportation database server, and thus, vehicle management notification, a transportation recommendation, or a transportation match notification indicating a transportation match with a provider computing device. Claim 16, a "Markush" claim recites a list of alternatively useable members. In re Harnisch, 631 F.2d 716, 719-20, 206 USPQ 300, 303 (CCPA 1980); Ex parte Markush, 1925 Dec. Comm'r Pat. 126, 127 (1924). The listing of specified alternatives within a Markush claim is referred to as a Markush group or a Markush grouping. Abbott Labs v. Baxter Pharmaceutical Products, Inc., 334 F.3d 1274, 1280-81, 67 USPQ2d 1191, 1196 (Fed. Cir. 2003) (citing to several sources that describe Markush groups)- See MPEP 706.03.
Regarding Claim 20,
The non-transitory computer readable storage medium of claim 16, further comprising instructions that, when executed by the at least one processor, cause the at least one processor to monitor at least one of transportation matching vehicle telematics data, transportation matching driver ratings, transportation matching vehicle types transportation matching driving route patterns, number of transportation matching provider devices for a geographic region, number of transportation matching requester devices for a geographic region, or provider transportation matching schedules.
Similar to claim 5. Hinduja [p. 9 line 15-16], [p.10 lines 23-26], [p. 17 lines 5-24], [p.20 lines 12-15].
Within claim 20, Hinduja discloses a region of operation and receive the vehicle data from a corresponding driver device, the telematics device, count of repairs, and thus, discloses geographic region of operation and matching vehicle telematics data, and provider transportation matching schedules. Claim 20, a "Markush" claim recites a list of alternatively useable members. In re Harnisch, 631 F.2d 716, 719-20, 206 USPQ 300, 303 (CCPA 1980); Ex parte Markush, 1925 Dec. Comm'r Pat. 126, 127 (1924). The listing of specified alternatives within a Markush claim is referred to as a Markush group or a Markush grouping. Abbott Labs v. Baxter Pharmaceutical Products, Inc., 334 F.3d 1274, 1280-81, 67 USPQ2d 1191, 1196 (Fed. Cir. 2003) (citing to several sources that describe Markush groups)- See MPEP 706.03
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 text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
The factual inquiries 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) 3, 6, 8, 11, 14, 15, 18, and 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Hinduja (WO 2022/0,911,120 A1) in view of McClintic (US 2016/0,078,695 A1).
Regarding Claim 3,
The computer-implemented method of claim 1, further comprising: monitoring a plurality of requester computing devices to determine the transportation matching features by determining a number of requester computing devices at a particular time;
monitoring the vehicle service features by determining vehicle service station availability at the particular time;
and generating the notification by generating the vehicle management notification based on the number of requester computing devices and the vehicle service station availability at the particular time.
Hinduja [p.20 lines 23-28] disclose features 212 may further include a count of dormant days of a vehicle, a count of active days of a vehicle, and a deviation in a count of active days between consecutive scheduled maintenance sessions of a vehicle. In such an embodiment, the plurality of feature values 214 may include the count of dormant days of each vehicle 102a and 102b, the count of active days of each vehicle 102a and 102b, the deviation in the count of active days between consecutive scheduled maintenance sessions of each vehicle 102a and 102b.
Although Hinduja matches vehicle for bookings and counts downtown of vehicles, Hinjuda does not explicitly teach:
determining vehicle service station availability at the particular time … the vehicle service station availability….
McClintic teaches:
determining vehicle service station availability at the particular time … the vehicle service station availability….
McClintic [009] planning of maintenance activities may include the selection of an optimal time and/or location for performing the work, with consideration given to trends in the operating data, the availability of necessary repair resources., McClintic [009], [045], [096].
McClintic [093] discloses the data center or service personnel may evaluate the most logical repair location in terms of various criteria, such as train proximity, parts, repair equipment availability, manpower availability, etc. The service recommendation automatically triggers the creation of an electronic work order.
Hinduja teaches a prediction model that may learn occurring scheduled and non-scheduled maintained. McClintic relate to indicating a repair to perform on an asset based on historic data related to a repair on the asset and/or sensor data associated with the asset. It would have been obvious to combine before the effective filing date, a count of times the vehicle undergoes scheduled maintenance in a fixed time-period, as taught by Hinduja, with service recommendations, and availability of shops, as taught by McClintic, to higher utilization levels in a given asset., Hinduja [034].
Regarding Claim 6,
The computer-implemented method of claim 1, wherein: determining the transportation matching features comprises determining a provider transportation matching schedule corresponding with a provider computing device; determining vehicle service features comprises …; and generating the notification comprises generating the vehicle management notification based on the provider transportation ….
Hinduja [p.20 lines 3-10] discloses learning repair downtime of a vehicle refers to a time-interval for which the vehicle has been out of service due to repair and maintenance actions. The repair downtime may be indicative of one of occurrence of one or more major or minor performance issues associated with the vehicle and a time spent on repair and maintenance of the vehicle for correcting those performance issues. For example, the vehicle 102a may have been put to use on March 30, 2012. Further, on March 30, 2013, the vehicle 102a is brought to the maintenance center 108 for maintenance and repair. The vehicle 102a is again put to use on April 30, 2013. Thus, the repair downtime of the vehicle 102a is one month.
Although Hinduja matches vehicle for bookings and counts downtown of vehicles, Hinjuda does not explicitly teach:
determining vehicle service station availability at the particular time … the vehicle service station availability….
McClintic teaches:
determining vehicle service station availability at the particular time … the vehicle service station availability….
McClintic [009] planning of maintenance activities and the availability of necessary repair resources., McClintic [009], [045], [096], [093].
Hinduja teaches a prediction model that may learn occurring scheduled and non-scheduled maintained. McClintic relate to indicating a repair to perform on an asset based on historic data related to a repair on the asset and/or sensor data associated with the asset. It would have been obvious to combine before the effective filing date, a count of times the vehicle undergoes scheduled maintenance in a fixed time-period, as taught by Hinduja, with service recommendations, and availability of shops, as taught by McClintic, to higher utilization levels in a given asset., Hinduja [034].
Regarding Claim 8,
The computer-implemented method of claim 1, wherein generating the notification comprises generating the transportation match notification by selecting a provider computing device from a pool of provider computing devices based on the vehicle service features from the plurality of service management computing devices and the transportation matching features for the plurality of provider computing devices.
Hinduja [Figure 4 and the associated text] disclose FIG. 4 is a flowchart 400 that illustrates a method for dynamic maintenance scheduling of a vehicle, in accordance with an exemplary embodiment of the disclosure.
McClintic further teaches:
selecting a provider computing device from a pool of provider ….
McClintic [008] discloses systems and methods are described herein for effectively integrating the diverse elements involved in the management of remote assets, e.g., a fleet of mobile assets.
Hinduja teaches a prediction model that may learn occurring scheduled and non-scheduled maintained. McClintic relate to indicating a repair to perform on an asset based on historic data related to a repair on the asset and/or sensor data associated with the asset. It would have been obvious to combine before the effective filing date, a count of times the vehicle undergoes scheduled maintenance in a fixed time-period, as taught by Hinduja, with service recommendations, and availability of shops, as taught by McClintic, to higher utilization levels in a given asset., Hinduja [034].
Regarding, Claim 11,
The system of claim 9, further comprising instructions that, when executed by the at least one processor, cause the system to: monitor a plurality of requester computing devices to determine the transportation matching features by determining a number of requester computing devices at a particular time; monitor the vehicle service features by determining vehicle service station availability at the particular time; and generate the notification by generating the vehicle management notification based on the number of requester computing devices and the vehicle service station availability at the particular time.
Hinduja [p.20 lines 23-28], McClintic [009], [045], [093], [096].
Hinduja teaches a prediction model that may learn occurring scheduled and non-scheduled maintained. McClintic relate to indicating a repair to perform on an asset based on historic data related to a repair on the asset and/or sensor data associated with the asset. It would have been obvious to combine before the effective filing date, a count of times the vehicle undergoes scheduled maintenance in a fixed time-period, as taught by Hinduja, with service recommendations, and availability of shops, as taught by McClintic, to higher utilization levels in a given asset., Hinduja [034].
Regarding Claim 14,
The system of claim 11, further comprising instructions that, when executed by the at least one processor, cause the system to: determine a provider transportation matching schedule corresponding with a provider computing device; determine vehicle station availability; and generate the vehicle management notification based on the provider transportation matching schedule and the vehicle service station availability.
Similar to claim 6. Hinduja [p.20 lines 3-10], McClintic [009], [045], [096], [093].
Hinduja teaches a prediction model that may learn occurring scheduled and non-scheduled maintained. McClintic relate to indicating a repair to perform on an asset based on historic data related to a repair on the asset and/or sensor data associated with the asset. It would have been obvious to combine before the effective filing date, a count of times the vehicle undergoes scheduled maintenance in a fixed time-period, as taught by Hinduja, with service recommendations, and availability of shops, as taught by McClintic, to higher utilization levels in a given asset., Hinduja [034].
Regarding Claim 15,
The system of claim 11, further comprising instructions that, when executed by the at least one processor, cause the system to generate the transportation recommendation by selecting between a personal vehicle corresponding to the client device or a set of transportation matching vehicles based on the vehicle service features from the plurality of service management computing devices and the transportation matching features for the plurality of provider computing devices.
Similar to claim 1 and claim 7. Hinduja [p. 17 line 5-24], [p.8 lines 10-23], [Figure 1A ], [Figure 2A].
Within claim 7, Hinduja discloses booking and a vehicle communication with a transportation database server, and thus, discloses a set of transportation matching vehicles based on the vehicle service features from the plurality of service management computing devices and the transportation matching features for the plurality of provider computing devices. Claim 7 a "Markush" claim recites a list of alternatively useable members. In re Harnisch, 631 F.2d 716, 719-20, 206 USPQ 300, 303 (CCPA 1980); Ex parte Markush, 1925 Dec. Comm'r Pat. 126, 127 (1924). The listing of specified alternatives within a Markush claim is referred to as a Markush group or a Markush grouping. Abbott Labs v. Baxter Pharmaceutical Products, Inc., 334 F.3d 1274, 1280-81, 67 USPQ2d 1191, 1196 (Fed. Cir. 2003) (citing to several sources that describe Markush groups)- See MPEP 706.03.
Regarding Claim 18,
The non-transitory computer readable storage medium of claim 16, further comprising instructions that, when executed by the at least one processor, cause the at least one processor to: monitor a plurality of requester computing devices to determine the transportation matching features by determining a number of requester computing devices at a particular time; monitor the vehicle service features by determining vehicle service station availability at the particular time; and generate the notification by generating the vehicle management notification based on the number of requester computing devices and the vehicle service station availability at the particular time.
Hinduja [p.20 lines 23-28]. McClintic [009], [045], [093], [096].
Hinduja teaches a prediction model that may learn occurring scheduled and non-scheduled maintained. McClintic relate to indicating a repair to perform on an asset based on historic data related to a repair on the asset and/or sensor data associated with the asset. It would have been obvious to combine before the effective filing date, a count of times the vehicle undergoes scheduled maintenance in a fixed time-period, as taught by Hinduja, with service recommendations, and availability of shops, as taught by McClintic, to higher utilization levels in a given asset., Hinduja [034].
Regarding Claim 19,
The non-transitory computer readable storage medium of claim 16, further comprising instructions that, when executed by the at least one processor, cause the at least one processor to determine, the vehicle service features by determining at least one of vehicle maintenance patterns, vehicle maintenance costs, vehicle repair down-times, determining, vehicle service features further comprises determining at least one of service vehicle types, vehicle accident information, or vehicle service station availability.
Similar to claim 4. Hinduja [abstract], [p.3 lines 16-19]. McClintic [009], [045], [093], [096].
Hinduja teaches a prediction model that may learn occurring scheduled and non-scheduled maintained. McClintic relate to indicating a repair to perform on an asset based on historic data related to a repair on the asset and/or sensor data associated with the asset. It would have been obvious to combine before the effective filing date, a count of times the vehicle undergoes scheduled maintenance in a fixed time-period, as taught by Hinduja, with service recommendations, and availability of shops, as taught by McClintic, to higher utilization levels in a given asset., Hinduja [034].
(Hinduja teaches first maintenance data, the first vehicle data, the first booking data, and the plurality of maintenance plans.); (The labels maintenance patterns, vehicle maintenance costs, vehicle repair down-times, service vehicle types, vehicle accident information, or vehicle service station availability are merely names and labels indicating a particular function and do not alter the structure or function of the claimed invention, accordingly these limitations (names and labels) do not patentability distinguish the claims from the cited prior art.)
Within claim 19, Hinduja discloses first maintenance data, the first vehicle data, the first booking data, and the plurality of maintenance plans, and thus, disclose at least one of vehicle maintenance patterns, vehicle maintenance costs, vehicle repair down-times, service vehicle types, vehicle accident information, or vehicle service station availability. Claim 4 a "Markush" claim recites a list of alternatively useable members. In re Harnisch, 631 F.2d 716, 719-20, 206 USPQ 300, 303 (CCPA 1980); Ex parte Markush, 1925 Dec. Comm'r Pat. 126, 127 (1924). The listing of specified alternatives within a Markush claim is referred to as a Markush group or a Markush grouping. Abbott Labs v. Baxter Pharmaceutical Products, Inc., 334 F.3d 1274, 1280-81, 67 USPQ2d 1191, 1196 (Fed. Cir. 2003) (citing to several sources that describe Markush groups)- See MPEP 706.03.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Wang (2019, Vehicle Fleet Maintenance Scheduling Optimization by Multi-objective Evolutionary Algorithms).
Any inquiry concerning this communication or earlier communications from the examiner should be directed to THEA LABOGIN whose telephone number is (571)272-9149. The examiner can normally be reached Monday -Friday, 8am-5pm.
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, Patricia Munson can be reached at 571-270- 5396. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/THEA LABOGIN/Examiner, Art Unit 3624
Prosecution Insights