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 . This action is made non-final.
Claims 21-40 are pending. Claims 21, 30, and 36 are independent. Claims 1-20 and 41-47 are canceled.
Claim Rejections - 35 USC § 103
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 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 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 21, 22, 24, 25, 27, 29-31, 33, 34, 36, 38, and 39 are rejected under 35 U.S.C. 103 as being unpatentable over Nerayoff et al. (US 2016/0078759 A1), in view of Adams et al. (US 2012/0226390 A1).
Regarding claim 21, Nerayoff teaches a method, comprising:
receiving, by a computing system (FIG. 1, [0028], and [0031-0041]: computing system includes at least server system 140), one or more aerial images of an environment from an unmanned aerial vehicle ([0041]: “At least one unmanned aerial vehicle 700 may be wirelessly connected to the network 110. The unmanned aerial vehicle 700 may include a camera that can be used in place of or in conjunction with one or both of the identification camera 120 and destination camera 125.”; FIG. 3A and [0061-0062]: one or more images are obtained and processed from destination camera 125, which as supported in [0041], may be a camera of unmanned aerial vehicle 700);
generating, by the computing system, a geo-referenced digital surface model of the environment based on the one or more aerial images ([0041]: “At least one unmanned aerial vehicle 700 may be wirelessly connected to the network 110. The unmanned aerial vehicle 700 may include a camera that can be used in place of or in conjunction with one or both of the identification camera 120 and destination camera 125.”; FIG. 3A and [0061-0062]: a digital surface model of an environment is generated using at least image 126 from the unmanned aerial vehicle 700. One or more mobile assets, including at least 320a-c and 320e-I, are located using at least image 126. The digital surface model includes specified destination locations 310a-310i, 320a-c and 320e-i, and destination location 340. The environment corresponds to a portion of an urban street; See FIG. 2B and [0047] for another example of a digital surface model);
receiving, by the computing system, data provided by one or more mobile assets located in the environment, the data indicating respective geo-spatial locations of the one or more mobile assets and information indicative of idle or non-moving states of the one or more mobile assets (FIG. 1 and [0084-0090], [0227-0229]: data indicating parked/idle mobile assets and their respective geo-spatial locations is received from and provided by one or more mobile assets via identification and destination cameras and sensors of the mobile assets. For example, vehicles/mobile assets each have an in-vehicle GPS that sense that the idle/parked status of the respective vehicle, the status then being reported to server system 140. The server system 140 also interpolates the identities of the parked/idle vehicles);
identifying, by the computing system, one or more structures within the environment as potential causes of the idle or non-moving states by comparing the respective geo-spatial locations of the one or more mobile assets with the geo-referenced digital surface model (FIG. 3A and [0061-0062]: one or more structures here include at least destination locations 310a-c and 310e-i, which are potential causes of the one or more mobile assets 320a-c and 320e-i being idle based on a comparison of the geo-spatial locations of these mobile assets and the digital surface model. In other words, the comparison identifies when destination locations are being or not being used by vehicles. As a further example, [0061] discloses “If a vehicle is determined to have made use of destination location 340 by remaining stationary for a period of time, the vehicle will be considered in violation”);
Nerayoff does not explicitly teach configuring, by the computing system, a user interface to display a cluster representation of the idle or non-moving states, the cluster representation including a graphical object representing an aggregated geographic area wherein:
responsive to a change in a user-selected map zoom level, the cluster representation is subdivided into multiple sub-clusters corresponding to smaller geographic areas; and
the user interface presents a time-segmented visualization of the idle or non-moving states; and
causing, by the computing system, display of the user interface.
Adams teaches
configuring, by the computing system, a user interface to display a cluster representation of the idle or non-moving states, the cluster representation including a graphical object representing an aggregated geographic area wherein:
responsive to a change in a user-selected map zoom level, the cluster representation is subdivided into multiple sub-clusters corresponding to smaller geographic areas; and
the user interface presents a time-segmented visualization of the idle or non-moving states; and
causing, by the computing system, display of the user interface (FIG. 1 and [0019-0024] and FIG. 3 and [0031-0033]: data is received from and provided by one or more mobile assets, the data provided via in-vehicle devices 105A-N of the mobile assets, the data indicating idleness and respective geo-spatial locations; FIG. 3 and [0031-0033]: vehicle management user interface 300 highlights one or more areas corresponding to the one or more structures, such as roads or streets, where one or more mobile assets are idle. For example, symbols 302 include “blue idle signs to indicate a vehicle that is idling”, as supported in [0031]. Note that selection of a symbol 302 produces a popup box 310 which shows the addresses of current locations, including roads or streets, of idling vehicles. Vehicle management user interface 300, which identifies one or more structures, such as roads, within the environment as potential causes of the one or more mobile assets being idle, is outputted to a display of a user device, such as a management device 135 described in FIG. 1 and [0020]. For example, symbols 302 include “blue idle signs to indicate a vehicle that is idling”, as supported in [0031]; FIG. 4 and [0033], [0040-0048]: see time segmentation).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the highlighting as disclosed in Nerayoff by incorporating the teachings of Adams and include configuring, by the computing system, a user interface to display a cluster representation of the idle or non-moving states, the cluster representation including a graphical object representing an aggregated geographic area wherein: responsive to a change in a user-selected map zoom level, the cluster representation is subdivided into multiple sub-clusters corresponding to smaller geographic areas; and the user interface presents a time-segmented visualization of the idle or non-moving states; and causing, by the computing system, display of the user interface. Doing so would allow a user, like a manager, to visually monitor the status of vehicles and be alerted when vehicles are idle, likely indicating lowered productivity to prompt correction for efficient fleet management to save at least time (like travel time), money (like costs of operation from fuel, vehicle wear, etc.), resources (like fuel), and so on. Furthermore, the user would be able to visualize the areas corresponding to the structures to more quickly understand where the potential source of idling is so as to more effectively assess fleet management. Visual confirmation allows idling vehicles to less likely be attributed to wrong locations, further improving the utility of the digital map and, thus, fleet management accuracy. In addition, a visual display of the user interface would allow a user, like a manager, to visually monitor the status of vehicles and be alerted when vehicles are idle, likely indicating lowered productivity to prompt correction for efficient fleet management to save at least time (like travel time) and/or money (like fuel).
Regarding claim 22, Nerayoff in view of Adams teaches the method of claim 21. Although Nerayoff teaches a display of a user device (display 512 of computer system 500 of FIG. 5 and [0256]), Nerayoff does not explicitly teach outputting, to a display of a user device, a graphical user interface highlighting the one or more areas corresponding to the one or more structures identified as potential causes of the idleness of the one or more mobile assets.
Adams further teaches outputting, to a display of a user device, the user interface highlighting the one or more areas corresponding to the one or more structures identified as potential causes of idleness of the the one or more mobile assets (FIG. 3 and [0031-0033]: vehicle management user interface 300, which identifies and highlights one or more structures, such as roads, within the environment as potential causes of the one or more mobile assets being idle, is outputted to a display of a user device, such as a management device 135 described in FIG. 1 and [0020]. For example, symbols 302 include “blue idle signs to indicate a vehicle that is idling”, as supported in [0031].).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the display of Nerayoff by incorporating the teachings of Adams and include outputting, to a display of a user device, a graphical user interface highlighting the one or more areas corresponding to the one or more structures identified as potential. Doing so would allow a user, like a manager, to visually monitor the status of vehicles and be alerted when vehicles are idle, likely indicating lowered productivity to prompt correction for efficient fleet management to save at least time (like travel time) and/or money (like fuel).
Regarding claim 24, Nerayoff in view of Adams teaches the method of claim 21. Nerayoff further teaches wherein the one or more structures are located in a portion of the environment (FIG. 3A and [0061]: the one or more structures/destination locations are in a portion of the environment/urban street), and further comprising:
performing an automated analysis process to predict the portion of the environment from the one or more images captured by the unmanned aerial vehicle ([0272], FIG. 3A and [0061]: for example, the unmanned aerial vehicle has captured a previous image and, by performing an automated analysis process, predicts a future location of a vehicle, like vehicle 330, this future location corresponding to a portion of urban street like a portion seen in FIG. 3A).
Regarding claim 25, Nerayoff in view of Adams teaches the method of claim 21. Nerayoff further teaches wherein the one or more structures are in a first portion of the environment (FIG. 3A and [0061]: the one or more structures/destination locations are in a first portion of the environment/urban street), and further comprising:
determining, by the computing system, a second portion of the environment that includes one or more features in common with the first portion of the environment (FIG. 3B and [0063]: see this second portion of the urban street that includes one or more features in common with the first portion seen in FIG. 3A; [0006-0009] and [0065-0067]: as a vehicle moves across the field of view of the camera, there is an overlap between an image captured at the first instance and the second instance where the camera is at a different location. This overlap at the second instance capturing a second portion of the environment indicates one or more features in common with the first portion of the environment; See FIG. 4 and its corresponding paragraphs for supplemental details regarding capturing overlaps between first and second portions of an environment).
Regarding claim 27, Nerayoff teaches the method of claim 21. Nerayoff does not explicitly teach wherein the one or more mobile assets are associated with a cluster representation that represents a temporal-based idle amount for at least one of the one or more mobile assets.
Adams teaches wherein the one or more mobile assets are associated with a cluster representation that represents a temporal-based idle amount for at least one of the one or more mobile assets (FIG. 3 and [0031-0032]: one or more mobile assets are associated with a cluster representation/cluster 304 that represents a temporal-based idle amount for at least one of the one or more mobile assets. For example, the user selects cluster 304, causing popup box 310 to be displayed, showing the temporal-based idle amount for at least one of the one or more mobile assets.).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Nerayoff by incorporating the teachings of Adams and include wherein the one or more mobile assets are associated with a cluster representation that represents a temporal-based idle amount for at least one of the one or more mobile assets. Doing so would allow a user, like a manager, to visually monitor the status of vehicles and be alerted when vehicles are idle, likely indicating lowered productivity to prompt correction for efficient fleet management to save at least time (like travel time) and/or money (like fuel).
Regarding claim 29, Nerayoff teaches the method of claim 21. Nerayoff does not explicitly teach outputting, to a display of a user device, a graphical user interface depicting the environment and the idleness of the one or more mobile assets within the environment.
Adams teaches outputting, to a display of a user device, a graphical user interface depicting the environment and the idleness of the one or more mobile assets within the environment (FIG. 3 and [0031-0032]: one or more mobile assets in the environment are associated with a cluster representation/cluster 304 that represents a temporal-based idle amount for at least one of the one or more mobile assets. For example, the user selects cluster 304, causing popup box 310 to be displayed, showing the temporal-based idle amount for at least one of the one or more mobile assets.).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Nerayoff by incorporating the teachings of Adams and include outputting, to a display of a user device, a graphical user interface depicting the environment and idleness in the environment. Doing so would allow a user, like a manager, to visually monitor the status of vehicles and be alerted when vehicles are idle, likely indicating lowered productivity to prompt correction for efficient fleet management to save at least time (like travel time) and/or money (like fuel).
Regarding claim 30, Nerayoff teaches a system (Nerayoff, computer system 500 of FIG. 5 and [0255]), comprising:
a memory (Nerayoff, main memory 506 of FIG. 5 and [0255]); and
a processor (Nerayoff, processor 504 of FIG. 5 and [0255]) configured to execute instructions stored in the memory to:
receiving aerial images of an environment from an unmanned aerial vehicle ([0041]: “At least one unmanned aerial vehicle 700 may be wirelessly connected to the network 110. The unmanned aerial vehicle 700 may include a camera that can be used in place of or in conjunction with one or both of the identification camera 120 and destination camera 125.”; FIG. 3A and [0061-0062]: one or more images are obtained and processed from destination camera 125, which as supported in [0041], may be a camera of unmanned aerial vehicle 700);
([0041]: “At least one unmanned aerial vehicle 700 may be wirelessly connected to the network 110. The unmanned aerial vehicle 700 may include a camera that can be used in place of or in conjunction with one or both of the identification camera 120 and destination camera 125.”; FIG. 3A and [0061-0062]: a digital surface model of an environment is generated using at least image 126 from the unmanned aerial vehicle 700. One or more mobile assets, including at least 320a-c and 320e-I, are located using at least image 126. The digital surface model includes specified destination locations 310a-310i, 320a-c and 320e-i, and destination location 340. The environment corresponds to a portion of an urban street; See FIG. 2B and [0047] for another example of a digital surface model);
receive data from one or more mobile assets located in the environment, indicating idleness of the one or more mobile assets and respective geo-spatial locations of the one or more mobile assets (FIG. 1 and [0084-0090], [0227-0229]: data indicating parked/idle mobile assets and their respective geo-spatial locations is received from and provided by one or more mobile assets via identification and destination cameras and sensors of the mobile assets. For example, vehicles/mobile assets each have an in-vehicle GPS that sense that the idle/parked status of the respective vehicle, the status then being reported to server system 140. The server system 140 also interpolates the identities of the parked/idle vehicles);
identify one or more structures within the environment as causes of the idleness (FIG. 3A and [0061-0062]: one or more structures here include at least destination locations 310a-c and 310e-i, which are potential causes of the one or more mobile assets 320a-c and 320e-i being idle based on a comparison of the geo-spatial locations of these mobile assets and the digital surface model. In other words, the comparison identifies when destination locations are being or not being used by vehicles. As a further example, [0061] discloses “If a vehicle is determined to have made use of destination location 340 by remaining stationary for a period of time, the vehicle will be considered in violation”);
(FIG. 3A and [0061-0062]: one or more structures here include at least destination locations 310a-c and 310e-I are highlighted as they are specified to server system 140);
Nerayoff does not explicitly teach a display; geo-rectifying or ortho-rectifying the images to generate a geo-referenced digital surface model; configure a user interface to highlight one or more areas corresponding to the one or more structures, and, responsive to a change in a user-selected map zoom level, subdividing an aggregated idleness cluster into sub-clusters at a finger geographic resolution, and updating the highlighted areas to reflect the sub-clusters, wherein the user interface further employs a color-coded and time-segmented visualization of idleness and the highlighted structures; and cause the display to visually present the user interface.
Adams teaches
a display (FIG. 3 and [0031-0033]: vehicle management user interface 300, which identifies one or more structures, such as roads, within the environment as potential causes of the one or more mobile assets being idle, is outputted to a display of a user device, such as a management device 135 described in FIG. 1 and [0020]. For example, symbols 302 include “blue idle signs to indicate a vehicle that is idling”, as supported in [0031]);
geo-rectifying or ortho-rectifying the images and generating a geo-referenced digital surface model of the environment based on the rectified images (FIG. 1, [0024], and [0044]: computing system corresponds to vehicle management system 110. Mapping module 115/geo-rectification software generates a digital surface model of the environment based on geo-rectified images. The one or more images are geo-rectified according to a geographic information system (GIS), as commonly understood among those of ordinary skill in the art);
receive data from one or more mobile assets located in the environment indicating idleness of the one or more mobile assets and respective geo-spatial locations of the one or more mobile assets (FIG. 1 and [0019-0024] and FIG. 3 and [0031-0033]: data is received from and provided by one or more mobile assets, the data provided via in-vehicle devices 105A-N of the mobile assets, the data indicating idleness and respective geo-spatial locations);
configure a user interface to highlight one or more areas corresponding to the one or more structures (FIG. 3 and [0031-0033]: vehicle management user interface 300 highlights one or more areas corresponding to the one or more structures, such as roads or streets, where one or more mobile assets are idle. For example, symbols 302 include “blue idle signs to indicate a vehicle that is idling”, as supported in [0031]. Note that selection of a symbol 302 produces a popup box 310 which shows the addresses of current locations, including roads or streets, of idling vehicles) and, responsive to a change in a user-selected map zoom level, subdividing an aggregated idleness cluster into sub-clusters at a finger geographic resolution, and updating the highlighted areas to reflect the sub-clusters, wherein the user interface further employs a color-coded and time-segmented visualization of idleness and the highlighted structures (FIGS. 3-4 and [0039-0048]: a user-selected map zoom level is changed as seen in the transition from FIG. 3 to FIG. 4. A cluster is subdivided into sub-clusters and areas, such as roads or streets, are highlighted to reflect the sub-clusters. There is a color-coded and time-segmented visualization representing idleness and the highlighted structures); and
cause the display to visually present the user interface (FIG. 3 and [0031-0033]: vehicle management user interface 300, which identifies one or more structures, such as roads, within the environment as potential causes of the one or more mobile assets being idle, is outputted to a display of a user device, such as a management device 135 described in FIG. 1 and [0020]. For example, symbols 302 include “blue idle signs to indicate a vehicle that is idling”, as supported in [0031]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Nerayoff by incorporating the teachings of Adams and include a display; geo-rectifying or ortho-rectifying the images to generate a geo-referenced digital surface model; configure a user interface to highlight one or more areas corresponding to the one or more structures, and, responsive to a change in a user-selected map zoom level, subdividing an aggregated idleness cluster into sub-clusters at a finger geographic resolution, and updating the highlighted areas to reflect the sub-clusters, wherein the user interface further employs a color-coded and time-segmented visualization of idleness and the highlighted structures; and cause the display to visually present the user interface. Doing so would allow a user, like a manager, to visually monitor the status of vehicles and be alerted when vehicles are idle, likely indicating lowered productivity to prompt correction for efficient fleet management to save at least time (like travel time), money (like costs of operation from fuel, vehicle wear, etc.), resources (like fuel), and so on. Furthermore, the user would be able to visualize the areas corresponding to the structures to more quickly understand where the potential source of idling is so as to more effectively assess fleet management. Moreover, using geo-rectification software would allow the system to more precisely determine the geo-location of vehicles. In this way, idling vehicles are less likely to be attributed to wrong locations, further improving the utility of the digital map and, thus, fleet management accuracy. In addition, a visual display of the user interface would allow a user, like a manager, to visually monitor the status of vehicles and be alerted when vehicles are idle, likely indicating lowered productivity to prompt correction for efficient fleet management to save at least time (like travel time) and/or money (like fuel). Moreover, allowing the user to change a zoom level allows the user to view more relevant and detailed data of sub-clusters representing a specific portion of data, reducing clutter on the user interface for easier data analysis. Finally, having a color-coded and time-segmented visualization of idleness and the highlighted structures organize different categories of data so that the user can more easily comprehend data.
Regarding claim 31, Nerayoff in view of Adams teaches the system of claim 30. Although Nerayoff teaches a display of a user device (display 512 of computer system 500 of FIG. 5 and [0256]), Nerayoff does not explicitly teach outputting, to a display of a user device, the user interface the one or more structures.
Adams further teaches outputting, to a display of a user device, the user interface identifying the one or more structures (FIG. 3 and [0031-0033]: vehicle management user interface 300, which identifies and highlights one or more structures, such as roads, within the environment as potential causes of the one or more mobile assets being idle, is outputted to a display of a user device, such as a management device 135 described in FIG. 1 and [0020]. For example, symbols 302 include “blue idle signs to indicate a vehicle that is idling”, as supported in [0031].).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the display of Nerayoff by incorporating the teachings of Adams and include outputting, to a display of a user device, the user interface the one or more structures. Doing so would allow a user, like a manager, to visually monitor the status of vehicles and be alerted when vehicles are idle, likely indicating lowered productivity to prompt correction for efficient fleet management to save at least time (like travel time) and/or money (like fuel).
Regarding claim 33, Nerayoff in view of Adams teaches the system of claim 30. Nerayoff further teaches wherein the one or more structures are in a portion of the environment (FIG. 3A and [0061]: the one or more structures/destination locations are in a portion of the environment/urban street), and wherein the processor is further configured to execute instructions stored in the memory to:
predict the portion of the environment from the one or more images captured by the unmanned aerial vehicle ([0272], FIG. 3A and [0061]: for example, the unmanned aerial vehicle has captured a previous image and, by performing an automated analysis process, predicts a future location of a vehicle, like vehicle 330, this future location corresponding to a portion of urban street like a portion seen in FIG. 3A).
Regarding claim 34, Nerayoff in view of Adams teaches the system of claim 30. Nerayoff further teaches wherein the one or more structures are in a first portion of the environment (FIG. 3A and [0061]: the one or more structures/destination locations are in a first portion of the environment/urban street), and wherein the processor is further configured to execute instructions stored in the memory to:
determine a second portion of the environment that includes one or more features in common with the first portion of the environment (FIG. 3B and [0063]: see this second portion of the urban street that includes one or more features in common with the first portion seen in FIG. 3A; [0006-0009] and [0065-0067]: as a vehicle moves across the field of view of the camera, there is an overlap between an image captured at the first instance and the second instance where the camera is at a different location. This overlap at the second instance capturing a second portion of the environment indicates one or more features in common with the first portion of the environment; See FIG. 4 and its corresponding paragraphs for supplemental details regarding capturing overlaps between first and second portions of an environment).
Regarding claims 36, 38, and 39, the claims recite a non-transitory computer readable medium storing instructions operable to cause one or more processors (Nerayoff, FIG. 5 and [0258-0260]) to perform operations comprising operations with corresponding limitations to the system of claims 30, 33, and 34, respectively, and are therefore rejected on the same premises.
Claims 23, 32, and 37 are rejected under 35 U.S.C. 103 as being unpatentable over Nerayoff et al. (US 20160078759 A1), in view of Adams et al. (US 2012/0226390 A1), and in view of Mizuta (US 2017/0161410 A1).
Regarding claim 23, Nerayoff in view of Adams teaches the method of claim 21. Nerayoff in view of Adams does not explicitly teach determining a change to the one or more structures to reduce idleness at the respective geo-spatial locations.
Mizuta teaches determining, by the computing system, a change to at least one of the one or more structures to reduce idleness at the respective geo-spatial locations of the one or more mobile assets ([0057], [0078-0080]: [0080]: for example, a change may be to construct a new road to reduce idleness, or reduce traffic congestion and/or increase traffic flow, at the respective geo-spatial locations. Other examples of change include, expanding the amount of lanes, providing an additional roadway connected to the intersection, installing a roundabout at the intersection).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Nerayoff in view of Adams by incorporating the teachings of Mizuta and include determining a change to the one or more structures to reduce idleness at the respective geo-spatial locations. Doing so would offer solutions that would promote more efficient travel among mobile assets by changing structures at certain geo-spatial locations that may impede the flow of traffic.
Regarding claim 32, Nerayoff in view of Adams teaches the system of claim 30. Nerayoff in view of Adams does not explicitly teach indicating a change to the one or more structures to reduce idleness.
Mizuta teaches indicating a change to the one or more structures to reduce idleness ([0057], [0078-0080]: [0080]: for example, an indicated change may relate to construction of a new road to reduce idleness, or reduce traffic congestion and/or increase traffic flow. Other examples of change include, expanding the amount of lanes, providing an additional roadway connected to the intersection, installing a roundabout at the intersection).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Nerayoff in view of Adams by incorporating the teachings of Mizuta and include indicating a change to the one or more structures to reduce idleness. Doing so would offer solutions that would promote more efficient travel among mobile assets by changing structures that may impede the flow of traffic.
Regarding claim 37, Nerayoff in view of Adams teaches the non-transitory computer readable medium storing instructions of claim 36. Nerayoff in view of Adams does not explicitly teach outputting, to a display of a user device, a graphical user interface indicating a suggestion to modify the one or more structures to address the potential causes of idleness.
Mizuta teaches outputting, to a display of a user device, a graphical user interface indicating a suggestion to modify the one or more structures to address the potential causes of idleness (FIG. 1, [0036], [0057], [0078-0080]: [0080]: for example, a change may be to construct a new road to reduce idleness, or reduce traffic congestion and/or increase traffic flow. Other examples of change include, expanding the amount of lanes, providing an additional roadway connected to the intersection, installing a roundabout at the intersection).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Nerayoff in view of Adams by incorporating the teachings of Mizuta and include eoutputting, to a display of a user device, a graphical user interface indicating a suggestion to modify the one or more structures to address the potential causes of idleness. Doing so would offer solutions displayable to the user that would promote more efficient travel among mobile assets by changing structures that may impede the flow of traffic.
Claims 26, 35, and 40 are rejected under 35 U.S.C. 103 as being unpatentable over Nerayoff et al. (US 20160078759 A1), in view of Adams et al. (US 2012/0226390 A1), and in view of Aziz et al. (US 2017/0352082 A1).
Regarding claim 26, Nerayoff in view of Adams teaches the method of claim 21. Nerayoff further teaches wherein the one or more structures are in a first portion of the environment (FIG. 3A and [0061]: the one or more structures/destination locations are in a first portion of the environment/urban street).
Nerayoff in view of Adams does not explicitly teach determining that the one or more mobile assets will idle more in the first portion of the environment than in a second portion of the environment.
Aziz teaches determining, by the computing system, that the one or more mobile assets will idle more in the first portion of the environment than in a second portion of the environment ([0135-0136]: the system determines that the one or more mobile assets will idle more in a first portion of the environment than a second portion of the environment. For example, the system can calculate that a normally traveled route/first portion of environment has a higher percentage of idling time than alternative routes, including a second portion of the environment.).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Nerayoff in view of Admas by incorporating the teachings of Aziz and include determining that the one or more mobile assets will idle more in the first portion of the environment than in a second portion of the environment. Doing so would allow the system to indicate to the user a more effective route that minimizes idling time to save fuel for the one or more mobile assets.
Regarding claim 35, Nerayoff in view of Adams teaches the system of claim 30. Nerayoff further teaches wherein the one or more structures are in a first portion of the environment (FIG. 3A and [0061]: the one or more structures/destination locations are in a first portion of the environment/urban street).
Nerayoff in view of Adams does not explicitly teach determine that the one or more mobile assets will idle more in the first portion of the environment than in a second portion of the environment.
Aziz teaches determine that the one or more mobile assets will idle more in the first portion of the environment than in a second portion of the environment ([0135-0136]: the system determines that the one or more mobile assets will idle more in a first portion of the environment than a second portion of the environment. For example, the system can calculate that a normally traveled route/first portion of environment has a higher percentage of idling time than alternative routes, including a second portion of the environment.).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Nerayoff in view of Adams by incorporating the teachings of Aziz and include determine that the one or more mobile assets will idle more in the first portion of the environment than in a second portion of the environment. Doing so would allow the system to indicate to the user a more effective route that minimizes idling time to save fuel for the one or more mobile assets.
Regarding claims 40, the claim recites a non-transitory computer readable medium storing instructions performing operations comprising operations with corresponding limitations to the system of claim 35 and is therefore rejected on the same premise.
Claim 28 are rejected under 35 U.S.C. 103 as being unpatentable over Nerayoff et al. (US 20160078759 A1), in view of Adams et al. (US 2012/0226390 A1), and in view of Ashjaee et al. (US 2015/0234055 A1).
Regarding claim 28, Nerayoff in view of Adams teaches the method of claim 21. Nerayoff further teaches navigating, by the computing system, the unmanned aerial vehicle to capture the one or more images ([0011]: the unmanned aerial vehicle is navigated according to a first path or a second path to capture one or more images).
Nerayoff in view of Adams does not explicitly teach using a photogrammetry process to associate the respective geo-spatial locations to one or more points about the one or more images.
Ashjaee teaches navigating, by the computing system, the unmanned aerial vehicle to capture the one or more images (FIG. 1 and [0021-0022], FIG. 3 and [0038]: an unmanned aerial vehicle is navigated along a path to capture the one or more images); and using, by the computing system, a photogrammetry process to associate the respective geo-spatial locations to one or more points about the one or more images ([0004-0005], [0021], [0033], FIG. 3, [0038], and [0054]: photogrammetry is used to associate the respective geo-spatial locations to one or more points about the one or more images).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Nerayoff in view of Adams by incorporating the teachings of Ashjaee and include using a photogrammetry process to associate the respective geo-spatial locations to one or more points about the one or more images. Doing so would effectively capture the location associated with the images to produce an accurate record with a geo-reference so that the user may more easily reference the images and ensure that the images belong to the correct location.
Response to Arguments
The claim amendments have rendered Applicant’s arguments regarding double patenting and 35 U.S.C. 101 moot. However, Applicant's arguments filed 10/20/2025 regarding the 112(a) rejections and the prior art rejection under 103 of the claims have been fully considered but they are not persuasive.
In Remarks, Applicant argues:
Regarding independent claims 30 and 36, Nerayoff does not teach using a digital surface model.
The Examiner respectfully disagrees.
Regarding point (a), Applicant has performed an improper piecemeal analysis regarding a feature which was rejected under the combination of Nerayoff in view of Adams, not Nerayoff alone. In response to applicant's arguments against the references individually, one cannot show nonobviousness by attacking references individually where the rejections are based on combinations of references. See In re Keller, 642 F.2d 413, 208 USPQ 871 (CCPA 1981); In re Merck & Co., 800 F.2d 1091, 231 USPQ 375 (Fed. Cir. 1986). Applicant is advised to review the mapping a rationale for these claims.
Conclusion
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/KENNY NGUYEN/Primary Examiner, Art Unit 2171
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