DETAILED ACTION
Claims 1-2, 5, and 7-11 are presented for examination.
This office action is in response to submission of application on 04-NOVEMBER-2025.
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 .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 28-NOVEMBER-2022 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Response to Amendment
The amendment filed 04-NOVEMBER-2025 in response to the non-final office action mailed 04-AUGUST-2025 has been entered. Claims 1-2, 5, and 7-11 remain pending in the application.
With regards to the non-final office action’s rejection under 101, the amendments to the claims have overcome the original rejection with regards to the claims being directed towards an abstract idea, in particular with regards to the amendment specifying that the superimposing of the post-repair deterioration level on the map improves the visual clarity of the output, providing an improvement to the technology.
With regards to the non-final office action’s rejection under 102, the amendment to the claims have overcome the original rejection. However, upon a new search for the amended limitations, a new 103 rejection over Maston in view of new art Yamasaki has been written.
Regarding the amendments to claim 1:
Maston discloses acquire a repair plan including repair location, repair timing, and repair method; identify, based on the repair plan, repair locations where repair will be completed before a specific prediction time point:
Maston teaches that the maintenance data (the repair plan) may furthermore describe both the area of the treatment (e.g., the specific road) as well as the method of treatment (e.g., salted to deal with ice or snow). (Paragraph 55). Finally, a route may be chosen through the roads that prioritizes recently treated roads (Paragraph 55) which demonstrates that the data also include repair time. This would also mean that during Maston routing process wherein routes are selected that have been recently maintained (Paragraph 55), the routing would identify, based on the repair plans, specific road (i.e., locations) wherein repair has been completed wherein the routing time acts as the specific prediction time point.
Maston discloses calculate a post-repair deterioration level of the repair locations at the specific prediction time point using a post-repair deterioration prediction model that reflects effects of the repair method and the repair location specified in the repair plan:
Maston teaches the prediction (i.e., the calculation) of current road conditions, which would include the deterioration level of the repair locations at the specific prediction time point (Paragraph 40) wherein the prediction may reflect the effects of changed in the road status for the repair location specified in the repair plan, including the repair method (such a road treatment) (Paragraph 55).
However, Maston does not teach the final amendment of claim 1. For this amendment, new art Yamasaki is introduced.
Yamasaki discloses superimpose the post-repair deterioration level of the map in a visually distinguishable display mode from a pre-repair deterioration level:
Yamasaki is analogous art to the present application as it is reasonably pertinent the problem that the applicant is solving of further visual clarity when distinguishing between two states in a display.
Yamasaki teaches a nail printing apparatus with display unit that superimposes marks on the nail images that differentiate between nails that already printed versus nails that are yet to be printed (Paragraph 86). The nail image would actual as the map upon which the mark is superimposed, wherein the mark is representative of a pre-printing or post-printing in a visually distinguishable manner (Paragraph 86).
Previously, Maston has taught a post-repair deterioration level. By applying the teachings of Yamasaki to the deterioration prediction system, it would enable the creation of a system that could superimpose the post-repair deterioration level of the map in a visually distinguishable display mode from a pre-repair deterioration level, as Yamasaki above demonstrates the visually distinct display mode for a second, later state. The advantages of this improvement are described below.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the present application to implement a system that utilized the teachings of Maston and the teachings of Yamasaki. This would have provided the advantage of visual clarity between states (Yamasaki, Paragraph 86).
Regarding newly added claim 11, in light of the new art the arguments are moot.
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 1-2, 5, and 7-11 are rejected under 35 U.S.C. 103 as being unpatentable over Maston (Pub. No. US 20140067265 A1, filed August 28th 2012, hereinafter Maston) in view of Yamasaki (Pub. No. US 20130083098 A1, filed September 13th 2012, hereinafter Yamasaki).
Regarding claim 1:
Claim 1 recites:
A deterioration prediction system comprising: at least one memory configured to store instructions; and at least one processor configured to execute the instructions to: predict a deterioration level of the road at prediction time points according to road inspection data and the prediction time points, the road inspection data obtained by inspecting a road and the prediction time points indicating future time points; acquire a repair plan including repair location, repair timing, and repair method; identify, based on the repair plan, repair locations where repair will be completed before a specific prediction time point; calculate a post-repair deterioration level of the repair locations at the specific prediction time point using a post-repair deterioration prediction model that reflects effects of the repair method and the repair location specified in the repair plan; superimpose the deterioration level on a map for each of the prediction time points in a display mode according to the deterioration level; and superimpose the post-repair deterioration level of the map in a visually distinguishable display mode from a pre-repair deterioration level.
Maston discloses a deterioration prediction system comprising: at least one memory configured to store instructions; and at least one processor configured to execute the instructions:
Maston teaches a computer which explicitly includes both a processing unit and system memory (Paragraph 87). Furthermore, memory configured to store instructions and a processor configured to execute instructions would be inherent to the computer itself.
Maston discloses predict a deterioration level of the road at prediction time points according to road inspection data and the prediction time points:
Maston teaches a prediction of current road conditions based on new or historical data (Paragraph 40). This would be a prediction of a deterioration level as the road condition would describe the deterioration of the road. Furthermore, the historical data would be road inspection data, as road inspection data describes data gathered from observation of the road.
Furthermore, Maston describes a system that may also determine the time of the road conditions (Paragraph 40) which would be the prediction time points.
Maston discloses the road inspection data obtained by inspecting a road and the prediction time points indicating future time points:
Maston teaches a sensor that is used to measure road conditions (Paragraph 32) which would be an example of inspecting the road to create road inspection data.
Furthermore, the prediction system of Maston may also estimate future road conditions (Paragraph 84) which would consist of future time points.
Maston discloses acquire a repair plan including repair location, repair timing, and repair method; identify, based on the repair plan, repair locations where repair will be completed before a specific prediction time point:
Maston teaches that the maintenance data (the repair plan) may furthermore describe both the area of the treatment (e.g., the specific road) as well as the method of treatment (e.g., salted to deal with ice or snow). (Paragraph 55). Finally, a route may be chosen through the roads that prioritizes recently treated roads (Paragraph 55) which demonstrates that the data also include repair time. This would also mean that during Maston routing process wherein routes are selected that have been recently maintained (Paragraph 55), the routing would identify, based on the repair plans, specific road (i.e., locations) wherein repair has been completed wherein the routing time acts as the specific prediction time point.
Maston discloses calculate a post-repair deterioration level of the repair locations at the specific prediction time point using a post-repair deterioration prediction model that reflects effects of the repair method and the repair location specified in the repair plan:
Maston teaches the prediction (i.e., the calculation) of current road conditions, which would include the deterioration level of the repair locations at the specific prediction time point (Paragraph 40) wherein the prediction may reflect the effects of changed in the road status for the repair location specified in the repair plan, including the repair method (such a road treatment) (Paragraph 55).
Maston discloses superimpose the deterioration level on a map for each of the prediction time points in a display mode according to the deterioration level
Maston teaches displaying a map with symbols added to it reflecting the road conditions, e.g., the deterioration level. Furthermore, the information that is displayed on the map may additionally include time data (Paragraph 48) which would be analogous to each of the prediction time points. Displaying the map with symbols would be an example of superimposing data on the map.
Yamasaki discloses superimpose the post-repair deterioration level of the map in a visually distinguishable display mode from a pre-repair deterioration level:
Yamasaki is analogous art to the present application as it is reasonably pertinent the problem that the applicant is solving of further visual clarity when distinguishing between two states in a display.
Yamasaki teaches a nail printing apparatus with display unit that superimposes marks on the nail images that differentiate between nails that already printed versus nails that are yet to be printed (Paragraph 86). The nail image would actual as the map upon which the mark is superimposed, wherein the mark is representative of a pre-printing or post-printing in a visually distinguishable manner (Paragraph 86).
Previously, Maston has taught a post-repair deterioration level. By applying the teachings of Yamasaki to the deterioration prediction system, it would enable the creation of a system that could superimpose the post-repair deterioration level of the map in a visually distinguishable display mode from a pre-repair deterioration level, as Yamasaki above demonstrates the visually distinct display mode for a second, later state. The advantages of this improvement are described below.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the present application to implement a system that utilized the teachings of Maston and the teachings of Yamasaki. This would have provided the advantage of visual clarity between states (Yamasaki, Paragraph 86).
Regarding claim 2, which depends upon claim 1:
Claim 2 recites:
The deterioration prediction system according to claim 1, wherein the at least one processor is further configured to execute the instructions to: predict a change in a deterioration type on the road at the prediction time point, and superimpose the predicted change in the deterioration type on the map
Maston in view of Yamasaki discloses claim 1 upon which claim 2 depends. Furthermore, Maston discloses the limitation of claim 2:
Maston teaches that the map with superimposed symbols may use different symbols to indicate changing conditions, wherein the change is predicted through monitoring of the road. For example, if known flooding is not reconfirmed after several hours of the flood symbol being present, another ‘high water likely’ symbol may be shown to predict lingering effects of the flood (Paragraph 50). This possible high water symbol would be an example of a predicted changed in the deterioration type as it shows that active flooding is no longer believed to be present. Furthermore, the more general changing of symbols for changed conditions demonstrates predicting a change in deterioration type on the road.
Regarding claim 5, which depends upon claim 1:
Claim 5 recites:
The deterioration prediction system according to claim 1, wherein the at least one processor is further configured to execute the instructions to: superimpose an area to be repaired on the road at the prediction time point on the map based on the repair plan
Maston in view of Yamasaki discloses claim 1 upon which claim 5 depends. Furthermore, regarding the limitation of claim 5:
Maston teaches that a symbol of a plow can be superimposed on an area of the map to indicate that maintenance of the road is taking place but not yet repaired (i.e., a plow is present) (Paragraph 72). This would be superimposing an area to be repaired on the road at the prediction time point on the map based on the repair plan as the plowing of the road would be the repair plan and the prediction time point would be the current state of the road.
Regarding claim 7, which depends upon claim 1:
Claim 7 recites:
The deterioration prediction system according to claim 1, wherein the at least one processor is further configured to execute the instructions to: predict the deterioration level of the road at the prediction time point based on a plurality of the repair plans acquired, and display the deterioration level in a display mode according to the deterioration level of the road at the prediction time point for each of the repair plans
Maston in view of Yamasaki discloses claim 1 upon which claim 7 depends. Furthermore, Maston discloses wherein the at least one processor is further configured to execute the instructions to: predict the deterioration level of the road at the prediction time point based on a plurality of the repair plans acquired:
Maston teaches that the effects of different types of road maintenance (i.e., repair plans) have different effects on road conditions (Paragraph 58), which indicates a prediction of the deterioration level of the road at the prediction time point based on the plurality of maintenances performed.
Regarding the limitation display the deterioration level in a display mode according to the deterioration level of the road at the prediction time point for each of the repair plans:
Maston teaches that the historical effects of maintenance, which would be each of the repair plans, can be used to determine prioritization of future repairs based on the predicted deterioration level (or severity of road condition) (Paragraph 58). Furthermore, this information is provided visually using the previous superimposed map system showing when and where maintenance was performed (Paragraph 56).
Regarding claim 8, which depends upon claim 1:
Claim 8 recites:
The deterioration prediction system according to claim 1, wherein the at least one processor is further configured to execute the instructions to: generate a deterioration prediction model that predicts deterioration of the road based on the road inspection data, and predict the deterioration level of the road at the prediction time point based on the generated deterioration prediction model
Maston in view of Yamasaki discloses claim 1 upon which claim 8 depends. Furthermore, regarding the limitation of claim 8:
Maston teaches that routes through the road system based on predictive technologies’ predictions of road deterioration can be automatically created for the prediction time point (i.e., when the request for a route is sent) (Paragraph 60). The automatic creation of route and use of predictive technologies demonstrates the use of a deterioration prediction model that predicts deterioration of the road, wherein the prediction may be based on road condition history (Paragraph 60) i.e. road inspection data.
Claim 9 recites a method that parallels the system of claim 1. Therefore, the analysis discussed above with respect to claim 1 also applies to claim 9. Accordingly, claim 9 is rejected based on substantially similar rationale as set forth above with respect to claim 1.
Claim 10 recites a non-transitory storage medium that parallels the system of claim 1. Therefore, the analysis discussed above with respect to claim 1 also applies to claim 10. Accordingly, claim 10 is rejected based on substantially similar rationale as set forth above with respect to claim 1.
Regarding claim 11, which depends upon claim 1:
Claim 11 recites:
The deterioration prediction system according to claim 1, wherein the visually distinguishable display mode includes displaying symbols representing the post-repair deterioration level with broken lines.
Maston in view of Yamasaki discloses claim 1 upon which claim 11 depends. Furthermore, regarding the limitation of claim 11:
Yamasaki teaches a visually distinguishable display mode including symbols such as colored circles or lines representing the various state a nail in the printing apparatus may be under (Paragraph 86). Among these markings is a broken line that represents a specific state of the printing.
Previously, Maston has taught a post-repair deterioration level. By applying the teachings of Yamasaki to the deterioration prediction system, it would enable the creation of a system that could distinguish the display mode of post-repair deterioration level with broken lines. The advantages of this improvement are described below.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the present application to implement a system that utilized the teachings of Maston and the teachings of Yamasaki. This would have provided the advantage of visual clarity between states (Yamasaki, Paragraph 86).
Response to Arguments
Applicant’s arguments filed 04-NOVEMBER-2025 have been fully considered, but the examiner believes that not all are fully persuasive.
Regarding the applicant’s remarks on the non-final office action’s 102 rejection of the claims, the applicant argues that Maston does not teach the amended limitations of these claims. As such, the applicant argues that all claims dependent on the above would additionally not be anticipated under 102. The examiner agrees that the prior art of the original office action does not teach all of the amended limitations. However, upon a new search of the prior art for the amended limitations, the examiner has written a new rejection under 103 to address these limitations and respectfully requests applicant’s consideration of the following:
Regarding the amendments to claim 1:
Maston discloses acquire a repair plan including repair location, repair timing, and repair method; identify, based on the repair plan, repair locations where repair will be completed before a specific prediction time point:
Maston teaches that the maintenance data (the repair plan) may furthermore describe both the area of the treatment (e.g., the specific road) as well as the method of treatment (e.g., salted to deal with ice or snow). (Paragraph 55). Finally, a route may be chosen through the roads that prioritizes recently treated roads (Paragraph 55) which demonstrates that the data also include repair time. This would also mean that during Maston routing process wherein routes are selected that have been recently maintained (Paragraph 55), the routing would identify, based on the repair plans, specific road (i.e., locations) wherein repair has been completed wherein the routing time acts as the specific prediction time point.
Maston discloses calculate a post-repair deterioration level of the repair locations at the specific prediction time point using a post-repair deterioration prediction model that reflects effects of the repair method and the repair location specified in the repair plan:
Maston teaches the prediction (i.e., the calculation) of current road conditions, which would include the deterioration level of the repair locations at the specific prediction time point (Paragraph 40) wherein the prediction may reflect the effects of changed in the road status for the repair location specified in the repair plan, including the repair method (such a road treatment) (Paragraph 55).
However, Maston does not teach the final amendment of claim 1. For this amendment, new art Yamasaki is introduced.
Yamasaki discloses superimpose the post-repair deterioration level of the map in a visually distinguishable display mode from a pre-repair deterioration level:
Yamasaki is analogous art to the present application as it is reasonably pertinent the problem that the applicant is solving of further visual clarity when distinguishing between two states in a display.
Yamasaki teaches a nail printing apparatus with display unit that superimposes marks on the nail images that differentiate between nails that already printed versus nails that are yet to be printed (Paragraph 86). The nail image would actual as the map upon which the mark is superimposed, wherein the mark is representative of a pre-printing or post-printing in a visually distinguishable manner (Paragraph 86).
Previously, Maston has taught a post-repair deterioration level. By applying the teachings of Yamasaki to the deterioration prediction system, it would enable the creation of a system that could superimpose the post-repair deterioration level of the map in a visually distinguishable display mode from a pre-repair deterioration level, as Yamasaki above demonstrates the visually distinct display mode for a second, later state. The advantages of this improvement are described below.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the present application to implement a system that utilized the teachings of Maston and the teachings of Yamasaki. This would have provided the advantage of visual clarity between states (Yamasaki, Paragraph 86).
Regarding newly added claim 11, this claim is addressed in full by Maston in view of Yamasaki in the 103 rejection above.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/A.J.M./Examiner, Art Unit 2142
/Mariela Reyes/Supervisory Patent Examiner, Art Unit 2142