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 .
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1 – 4 are rejected under 35 U.S.C. § 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Independent claim 1, in part is directed toward a statutory category of invention, the claim appears to be directed toward a judicial exception namely an abstract idea. Claim 1 recites invention directed to
Dividing information associated with a road to be repaired into a plurality of segments, usage of specification information of the road to be repaired and condition score indicating condition of the road to be repaired. After segmenting of the information, mathematical calculation are performed calculate post-repair weighted condition scores for each segment using plurality of multiplying factors for a particular predetermined area of the road, by taking into account a number of points requiring repair of the same type in the same route by a post-repair condition score of the segment, which, pursuant to MPEP 2106.04, is aptly categorized as a method of organizing human activity (i.e. advertising, budgeting). Therefore, under Step 2A, Prong One, the claims recite a judicial exception.
Next, the aforementioned claims recite additional functional elements that are associated with the judicial exception, including: calculation of discrete variables maximizing total sum of values of each segment, wherein the values of each segment obtained by adding value obtained by multiplying the discrete variable taking either 1 or 0 (e.g., Yes/No) by the post-repair weighted condition score and value obtained by multiplying difference of 1 and the discrete variable by the condition score, which, pursuant to MPEP 2106.04, is aptly categorized as a method of organizing human activity (i.e. advertising) , budgeting. Therefore, under Step 2A, Prong One, the claims recite a judicial exception. Therefore, pursuant to MPEP 2106.04, the claimed invention is aptly categorized as a method of organizing human activity (i.e. advertising, budgeting). Therefore, under Step 2A, Prong One, the claims recite a judicial exception.
The aforementioned claims also recite technical elements in their claimed invention. The claimed limitations are recited at a high level of generality, and appear to be nothing more than defining a workflow or algorithm to perform the calculations. 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 2358, 110 USPQ2d at 1983. See also 134 S. Ct. at 2389, 110 USPQ2d at 1984.
Furthermore, looking at the elements individually and in combination, under Step 2A, Prong Two, the claims as a whole do not integrate the judicial exception into a practical application because they fail to: improve the functioning of a computer or a technical field, apply the judicial exception in the treatment or prophylaxis of a disease, apply the judicial exception with a particular machine, effect a transformation or reduction of a particular article to a different state or thing, or apply the judicial exception beyond generally linking the use of the judicial exception to a particular technological environment. Rather, the claims merely use a computer as a tool to perform the abstract idea(s), and/or add insignificant extra-solution activity to the judicial exception, and/or generally link the use of the judicial exception to a particular technological environment (e.g. a generic computer).
Next, under Step 2B, the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements, when considered both individually and as an ordered combination, do not amount to significantly more than the abstract idea. Furthermore, looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. Simply put, as noted above, there is no indication that the combination of elements improves the functioning of a computer (or any other technology), and their collective functions merely provide conventional computer implementation.
Additionally, pursuant to the requirement under Berkheimer, the following citations are provided to demonstrate that the additional elements, identified as extra-solution activity, amount to activities that are well-understood, routine, and conventional. See MPEP 2106.05(d).
Storing and retrieving information in memory. Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93.
Outputting/Presenting data to a user. Mayo, 566 U.S. at 79, 101 USPQ2d at 1968; OIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1092-93 (Fed. Cir. 2015); MPEP 2106.05(g)(3).
Using a machine learning model to determine user segment characteristics for an ad campaign. https://whites.agency/blog/how-to-use-machine-learning-for-customer-segmentation/.
Thus, taken alone and in combination, the additional elements do not amount to significantly more than the above-identified judicial exception (the abstract idea), and are ineligible under 35 USC 101.
Claims 2 – 4 dependent on the aforementioned independent claim 1, and include all the limitations contained therein. These claims do not recite any additional technical elements, and simply disclose additional limitations that further limit the abstract idea with details regarding range and Which variables will be considered for calculating discrete variables; what criteria will be considered for classifying the segments of the road, and what variables will be considered for scheduling repairs. Thus, the dependent claims merely provide additional non-structural (and predominantly non-functional) details that fail to meaningfully limit the claims or the abstract idea(s).
Therefore, claims 1 – 4 are not drawn to eligible subject matter, as they are directed to an abstract idea without significantly more.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1 – 4 are rejected under 35 U.S.C. 103 as being unpatentable over Lu et al. Chinese Patent Application CN-115423245-A hereinafter referred to as Lu in view of Odoki et al. published article “Development of optimal road maintenance fund allocation framework” hereinafter referred to as Odoki.
Regarding claim 1, Lu teaches Road maintenance and management planning support system (Lu teaches system and method for providing a tunnel (e.g., tunnel comprises road) maintenance fund distribution decision method, by utilizing different decision types according to different purposes, providing simple and reasonable tunnel maintenance fund distribution decision scheme [Lu, page 2], comprising:
dividing a road to be repaired into a plurality of segments, usage of specification information of the road to be repaired and condition score indicating condition of the road to be repaired (Lu, According to the current road tunnel maintenance technology specification, respectively building structure of the tunnel, electromechanical structure, other engineering facilities, the component unit is divided, forming the ith tunnel component detail list, detail content at least comprises: the i-th tunnel unique number, the ith tunnel name, component type, component unique number, component mileage or mileage paragraph, component type namely the existing road tunnel maintenance technology specification of tunnel soil structure, electromechanical structure, other engineering facilities) [Lu, page 5],
Lu does not explicitly recite calculation of weighted condition score. However, Lu teaches Lu teaches calculating each tunnel maintenance fund requirement, obtaining maintenance fund budget list of each component of each tunnel; for n tunnel, repeating said steps for each tunnel, then obtaining the total amount BT of maintenance budget requirement of n tunnels, daily maintenance budget Bg, preventative maintenance budget total By, disease repairing and reinforcing budget total Bf, n seat tunnel component detail table, n tunnel technology condition score list table, n tunnel preventative maintenance component budget list table, n tunnel repairing reinforcing component budget list table [Lu, page 6]; Odoki teaches a three-stage allocation structure is proposed as illustrated in Figure 1. The first step in the allocation process involves determination of the roads in maintainable state and defining the input data required. This is then followed by the three-stage allocation structure which consists of the following [Odoki, page 9, allocation structure as proposed in Fig. 1].
Therefore, at the time of filing, it would have been obvious to one of ordinary skill in the art to modify Lu by adopting teachings of Odoki to prioritize allocation of maintenance funds for road repairs and stay withing allocated annual budget.
Lu in view of Odoki teaches system and method further coprising:
calculation of post-repair weighted condition scores [Odoki, page 9, allocation structure as proposed in Fig. 1] for each segment by multiplying a priority obtained based on the specification information and according to a road standard of the road to be repaired, a priority obtained by taking into account a number of segments of same repair type in predetermined area [Lu, page 6], and a priority obtained by taking into account a number of points requiring repair of the same type in the same route by a post-repair condition score of the segment (Lu, the single-factor ordering model according to the tunnel length of the tunnel in the sample, the tunnel daily traffic or technical condition worst priority ordering, then repairing and reinforcing funds for disease, preventative maintenance fund calculation to eliminate, until the actual investment of disease repair reinforcing funds Ffs, The preventive maintenance fund Fys is complete. the comprehensive weight method ordering model adopts tunnel length, traffic, technical condition worst comprehensive weighting calculation for tunnel priority ordering, using the maximum minimum normalization or average normalization to perform priority calculation processing; then repairing and reinforcing funds for disease, the preventative maintenance fund calculation is carried out, until the actual investment of disease repairing and reinforcing demand fund Ffs, the preventive maintenance demand fund Fys is completely ablated.) [Lu, page 8], and,
calculation of discrete variables maximizing total sum of values of each segment, wherein the values of each segment obtained by adding value obtained by multiplying the discrete variable taking either 1 or 0 by the post-repair weighted condition score and value obtained by multiplying difference of 1 and the discrete variable by the condition score (Lu, the tunnel maintenance items and the tunnel maintenance items are corresponding to the investment maintenance cost; the tunnel data classification module is used for determining the property of the tunnel maintenance according to the distribution condition information of the tunnel, and classifying the maintenance cost according to the tunnel maintenance property, so as to determine the maintenance fund requirement type; the tunnel maintenance fund calculation module is used for calculating the tunnel maintenance fund requirement according to the maintenance fund requirement type, obtaining the tunnel sample in n tunnel each maintenance fund requirement; the maintenance fund distribution module is used for distributing tunnel maintenance funds according to proportion of each maintenance fund requirement of n tunnel in the tunnel sample) [Lu, page 7].
Regarding claim 2, as combined and under the same rationale as above, Lu in view of Odoki teaches system and method, wherein the discrete variables are calculated within a range where total repair cost being total sum of cost of each segment becomes equal to or less than the budget upper limit, the cost of each segment is obtained by multiplying repair cost by the discrete variable (Lu, the tunnel maintenance items and the tunnel maintenance items are corresponding to the investment maintenance cost; the tunnel data classification module is used for determining the property of the tunnel maintenance according to the distribution condition information of the tunnel, and classifying the maintenance cost according to the tunnel maintenance property, so as to determine the maintenance fund requirement type; the tunnel maintenance fund calculation module is used for calculating the tunnel maintenance fund requirement according to the maintenance fund requirement type, obtaining the tunnel sample in n tunnel each maintenance fund requirement; the maintenance fund distribution module is used for distributing tunnel maintenance funds according to proportion of each maintenance fund requirement of n tunnel in the tunnel sample) [Lu, page 7].
Regarding claim 3, as combined and under the same rationale as above, Lu in view of Odoki teaches system and method, wherein repair scheduled for the each segment is classified into classes according to the condition score (Odoki, Funds shall be allocated to give the optimum effect in terms of road condition; Factors that influence road maintenance cost) [Odoki, page 4, 7], and, small-scale implementation discrete variables are calculated such that total sum of costs of each segment becomes more than cost allocated to small-scale repair of the total repair cost, the cost of each segment is obtained by multiplying the small-scale implementation discrete variable taking 1 in case where the small-scale repair in the classes is performed and taking 0 in case where the small-scale repair in the classes is not performed, and the discrete variables by the total repair cost (Lu, the tunnel maintenance items and the tunnel maintenance items are corresponding to the investment maintenance cost; the tunnel data classification module is used for determining the property of the tunnel maintenance according to the distribution condition information of the tunnel, and classifying the maintenance cost according to the tunnel maintenance property, so as to determine the maintenance fund requirement type; the tunnel maintenance fund calculation module is used for calculating the tunnel maintenance fund requirement according to the maintenance fund requirement type, obtaining the tunnel sample in n tunnel each maintenance fund requirement; the maintenance fund distribution module is used for distributing tunnel maintenance funds according to proportion of each maintenance fund requirement of n tunnel in the tunnel sample) [Lu, page 7].
Regarding claim 4, as combined and under the same rationale as above, Lu in view of Odoki teaches system and method, wherein repair scheduled for the each segment is classified into classes according to the condition score (Odoki, Funds shall be allocated to give the optimum effect in terms of road condition; Factors that influence road maintenance cost) [Odoki, page 4, 7], and, large-scale implementation discrete variables are calculated such that total sum of cost of each segment becomes more than cost allocated to large-scale repair of the total repair cost, the cost of each segment is obtained by multiplying the large-scale implementation discrete variable taking 1 in case where the large-scale repair in the classes is performed and taking 0 in case where the large-scale repair in the classes is not performed, and the discrete variables by the total repair cost (Lu, the tunnel maintenance items and the tunnel maintenance items are corresponding to the investment maintenance cost; the tunnel data classification module is used for determining the property of the tunnel maintenance according to the distribution condition information of the tunnel, and classifying the maintenance cost according to the tunnel maintenance property, so as to determine the maintenance fund requirement type; the tunnel maintenance fund calculation module is used for calculating the tunnel maintenance fund requirement according to the maintenance fund requirement type, obtaining the tunnel sample in n tunnel each maintenance fund requirement; the maintenance fund distribution module is used for distributing tunnel maintenance funds according to proportion of each maintenance fund requirement of n tunnel in the tunnel sample) [Lu, page 7].
Conclusion
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/NARESH VIG/Primary Examiner, Art Unit 3622
September 17, 2025