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 19 February 2025 and 03 April 2025. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claims 1, 4-10 and 13-17 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-4 and 7-9 of U.S. Patent No. 12,229,889 B2 in view of Howell (WO 2021134114).
Claim
Current application 19/050,233
Claim
US Patent 12,229,899 B2
1
An agricultural modeling system for processing data for an agricultural geographic area, the agricultural modeling system comprising:
1
An agricultural modeling system for processing data for an agricultural geographic area, the agricultural modeling system comprising:
A scanning platform configured to generate three-dimensional (3D) point cloud data of the agricultural geographic area;
A scanning platform configured to generate three-dimensional (3D) point cloud data of the agricultural geographic area;
A geospatial database configured to store at least one data layer for the agricultural geographic area and having a resolution less than or equal to the 3D point cloud data of the agricultural geographic area; and
A geospatial database configured to store at least one data layer for the agricultural geographic area and having a resolution less than or equal to the 3D point cloud data of the agricultural geographic area; and
A computing resource in communication with the scanning platform, a plurality of client devices, and the geospatial database, the computing resource configured to geographically reference the at least one data layer fused with the 3D point cloud data of the agricultural geographic area, and
A computing resource in communication with the scanning platform, a plurality of client devices, and the geospatial database, the computing resource configured to geographically reference the at least one data layer fused with the 3D point cloud data of the agricultural geographic area;
Generate a multi-layered data model for the geographically referenced at least one data layer fused with the 3D point cloud data of the agricultural geographic area;
A given client device from the plurality of client devices and configured to upload an additional data source;
A given client device from the plurality of client devices and configured to upload an additional data source and a programming code script to the computing resource
The computing resource configured to geographically reference and fuse the additional data source and the 3D point cloud data of the agricultural geographic area, and
The computing resource configured to geographically reference and fuse the additional data source and the 3D point cloud data of the agricultural geographic area, and
Selectively render the multi-layered data model including the additional data source based upon the programming code script, the multi-layered data model being unique to the given client device.
Generate at least one prediction characteristic for the agricultural geographic area.
4
The agricultural modeling system of claim 1
2
The agricultural modeling system of claim 1
Wherein the computing resource is configured to scale each data layer with the 3D point cloud data of the agricultural geographic area.
Wherein the computing resource is configured to scale each data layer with the 3D point cloud data of the agricultural geographic area.
5
The agricultural modeling system of claim 1
3
The agricultural modeling system of claim 1
Wherein the at least one data layer for the agricultural geographic area comprises a plurality of data layers for the agricultural geographic area comprising a climate data source, a soil survey data source, a satellite imagery data source, and a tree phenotyping data source.
Wherein the at least one data layer for the agricultural geographic area comprises a plurality of data layers for the agricultural geographic area comprising a climate data source, a soil survey data source, a satellite imagery data source, and a tree phenotyping data source.
6
The agricultural modeling system of claim 1
4
The agricultural modeling system of claim 1
Wherein the 3D point cloud data comprises a Keyhole Markup Language polygon defining the agricultural geographic area.
Wherein the 3D point cloud data comprises a Keyhole Markup Language polygon defining the agricultural geographic area.
7
The agricultural modeling system of claim 1
7
The agricultural modeling system of claim 1
Wherein the computing resource is configured to generate a different multi-layered data model for each client device using a respective different at least one data layer.
Wherein the computing resource is configured to generate a different multi-layered data model for each client device using a respective different at least one data layer.
8
The agricultural modeling system of claim 1
8
The agricultural modeling system of claim 1
Wherein the given client device comprises a notebook client device; and
Wherein the given client device comprises a notebook client device; and
Wherein the at least one data layer is associated with at least one notebook workflow.
Wherein the at least one data layer is associated with at least one notebook workflow.
9
The agricultural modeling system of claim 1
9
The agricultural modeling system of claim 1
Wherein the scanning platform comprises at least one of an airborne platform and a ground platform.
Wherein the scanning platform comprises at least one or an airborne platform and a ground platform.
Regarding current claim 1, claim 1 of US 12,229,899 B2 teaches all of the limitations of current claim 1 except for the following which are taught by Howell:
Generate a multi-layered data model for the geographically referenced at least one data layer fused with the 3D point cloud data of the agricultural geographic area (Paragraph 42, An AgTwin in preferred embodiments operates by providing a visualization layer (defined by a 3D model, for example a photomosaic defined by photogrammetry methods, a digital terrain model, or the like), which facilitates visual review of the region and a control layer (for example defined by a shape file or the like) which covers substantially the same region as the visualization later and allows identification of locations of user interactions with the model in the context of user interface control operations (for example selection of an asset or field). Additional visualization layers are able to be defined by using a point cloud, digital surface model and/or digital terrain model, and assigning colour values to points/pixels based on a defined algorithm which assigns an information value to each pixel (for example an elevation, upstream flow metric, slope gradient, or the like) thereby to enable delivery of information overlays (optionally with controllable variable transparency));
Generate at least one prediction characteristic for the agricultural geographic area (Paragraph 70, For example, in one embodiment image processing techniques (for example based on colour composition and/or Al-based image classification) is used thereby to perform an automated prediction of vegetation and/or soil characteristics).
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the teachings of Howell in the same field of 3D modeling of agricultural land and generate a multi-layered model for the data layer fused with the 3D point cloud data and generate at least one prediction characteristic for the agricultural area. Doing so would have allowed the user to interactively overlay additional information on the visualization that the user may find to be useful (Howell, [0042]).
Current claims 10 and 17 correspond to current claim 1 and are therefore rejected for the same reasons as used above.
Current claim 13 corresponds to current claim 4 and is therefore rejected for the same reasons as used above.
Current claim 14 corresponds to current claim 5 and is therefore rejected for the same reasons as used above.
Current claim 15 corresponds to current claim 6 and is therefore rejected for the same reasons as used above.
Current claim 16 corresponds to current claim 7 and is therefore rejected for the same reasons as used above.
Claims 1, 5-9 and 14-17 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-3 and 6-8 of U.S. Patent No. 11,880,938 B1 in view of Howell (WO 2021134114).
Claim
Current application 19/050,233
Claim
US Patent 11,880,938 B1
1
An agricultural modeling system for processing data for an agricultural geographic area, the agricultural modeling system comprising:
1
An agricultural modeling system for processing data for an agricultural geographic area, the agricultural modeling system comprising:
A scanning platform configured to generate three-dimensional (3D) point cloud data of the agricultural geographic area;
A mobile ranging platform configured to generate three-dimensional (3D) point cloud data of the agricultural geographic area;
A plurality of client devices, the plurality of client devices being arranged in subsets;
A geospatial database configured to store at least one data layer for the agricultural geographic area and having a resolution less than or equal to the 3D point cloud data of the agricultural geographic area; and
A geospatial database configured to store at least one data layer for the agricultural geographic area and having a resolution less than or equal to the 3D point cloud data of the agricultural geographic area; and
A computing resource in communication with the scanning platform, a plurality of client devices, and the geospatial database, the computing resource configured to geographically reference the at least one data layer fused with the 3D point cloud data of the agricultural geographic area, and
A server computing resource in communication with said mobile ranging platform, said plurality of client devices, and said geospatial database, said computing resource configured to geographically reference the at least one data layer fused with the 3D point cloud data of the agricultural geographic area;
Generate a multi-layered data model for the geographically referenced at least one data layer fused with the 3D point cloud data of the agricultural geographic area;
Generate a multi-layered data model for the geographically referenced at least one data layer fused with the 3D point cloud data of the agricultural geographic area.
A given client device from the plurality of client devices and configured to upload an additional data source;
A given client device from a given subset of client devices and configured to upload an additional data source to said server computing resource
The computing resource configured to geographically reference and fuse the additional data source and the 3D point cloud data of the agricultural geographic area, and
Said computing resource configured to geographically reference and fuse the additional data source and the 3D point cloud data of the agricultural geographic area, and
Selectively render the multi-layered data model including the additional data source, the multi-layered data model being unique to the given client device, and share the multi-layered data model including the additional data source with the given subset of client devices while isolating the multi-layered data model including the additional data source from other subsets of client devices.
Generate at least one prediction characteristic for the agricultural geographic area.
5
The agricultural modeling system of claim 1
2
The agricultural modeling system of claim 1
Wherein the at least one data layer for the agricultural geographic area comprises a plurality of data layers for the agricultural geographic area comprising a climate data source, a soil survey data source, a satellite imagery data source, and a tree phenotyping data source.
Wherein the at least one data layer for the agricultural geographic area comprises a plurality of data layers for the agricultural geographic area comprising a climate data source, a soil survey data source, a satellite imagery data source, and a tree phenotyping data source.
6
The agricultural modeling system of claim 1
3
The agricultural modeling system of claim 1
Wherein the 3D point cloud data comprises a Keyhole Markup Language polygon defining the agricultural geographic area.
Wherein the 3D point cloud data comprises a Keyhole Markup Language polygon defining the agricultural geographic area.
7
The agricultural modeling system of claim 1
6
The agricultural modeling system of claim 1
Wherein the computing resource is configured to generate a different multi-layered data model for each client device using a respective different at least one data layer.
Wherein the computing resource is configured to generate a different multi-layered data model for each client device using a respective different at least one data layer.
8
The agricultural modeling system of claim 1
7
The agricultural modeling system of claim 1
Wherein the given client device comprises a notebook client device; and
Wherein the given client device comprises a notebook client device; and
Wherein the at least one data layer is associated with at least one notebook workflow.
Wherein the at least one data layer is associated with at least one notebook workflow.
9
The agricultural modeling system of claim 1
8
The agricultural modeling system of claim 1
Wherein the scanning platform comprises at least one of an airborne platform and a ground platform.
Wherein the scanning platform comprises at least one or an airborne platform and a ground platform.
Regarding current claim 1, claim 1 of US 11,880,938 B1 teaches all of the limitations of current claim 1 except for the following which are taught by Howell:
Generate at least one prediction characteristic for the agricultural geographic area (Paragraph 70, For example, in one embodiment image processing techniques (for example based on colour composition and/or Al-based image classification) is used thereby to perform an automated prediction of vegetation and/or soil characteristics).
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the teachings of Howell in the same field of 3D modeling of agricultural land and generate at least one prediction characteristic for the agricultural area. Doing so would have allowed the user to interactively overlay additional information on the visualization that the user may find to be useful (Howell, [0042]).
Additionally, it would have been obvious for a person of ordinary skill in the art to substitute a mobile ranging platform for a scanning platform to perform the method of current claim 1. Doing so would have allowed for scanning using any platform regardless of mobility.
Current claims 10 and 17 correspond to current claim 1 and are therefore rejected for the same reasons as used above.
Current claim 14 corresponds to current claim 5 and is therefore rejected for the same reasons as used above.
Current claim 15 corresponds to current claim 6 and is therefore rejected for the same reasons as used above.
Current claim 16 corresponds to current claim 7 and is therefore rejected for the same reasons as used above.
Claims 1, 4-10 and 13-17 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-2, 4 and 7-9 of U.S. Patent No. 11,468,632 B2 in view of Howell (WO 2021134114).
Claim
Current application 19/050,233
Claim
US Patent 12,229,899 B2
1
An agricultural modeling system for processing data for an agricultural geographic area, the agricultural modeling system comprising:
1
An agricultural modeling system for processing data for an agricultural geographic area, the agricultural modeling system comprising:
A scanning platform configured to generate three-dimensional (3D) point cloud data of the agricultural geographic area;
A mobile light detection and ranging (LiDAR) platform configured to generate three-dimensional (3D) point cloud data of the agricultural geographic area;
A plurality of client devices;
A geospatial database configured to store at least one data layer for the agricultural geographic area and having a resolution less than or equal to the 3D point cloud data of the agricultural geographic area; and
A geospatial database configured to store at least one data layer for the agricultural geographic area and having a resolution less than or equal to the 3D point cloud data of the agricultural geographic area; and
A computing resource in communication with the scanning platform, a plurality of client devices, and the geospatial database, the computing resource configured to geographically reference the at least one data layer fused with the 3D point cloud data of the agricultural geographic area, and
A server computing resource in communication with said mobile LiDAR platform, said plurality of client devices, and said geospatial database, said server computing resource configured to scale each data layer with the 3D point cloud data of the agricultural geographic area, geographically reference the at least one data layer fused with the 3D point cloud data of the agricultural geographic area;
Generate a multi-layered data model for the geographically referenced at least one data layer fused with the 3D point cloud data of the agricultural geographic area;
Generate a multi-layered data model for the geographically referenced at least one data layer fused with the 3D point cloud data of the agricultural geographic area for providing interactive analysis and visualization of agricultural information alongside collaborators with LiDAR-based high resolution 3D plant model;
A given client device from the plurality of client devices and configured to upload an additional data source;
A given client device from said plurality of client devices configured to upload an additional data source to said server computing resource
The computing resource configured to geographically reference and fuse the additional data source and the 3D point cloud data of the agricultural geographic area, and
Said server computing resource configured to geographically reference and fuse the additional data source and the 3D point cloud data of the agricultural geographic area, and
Selectively render the multi-layered data model including the additional data source, the multi-layered data model being unique to the given client device.
Generate at least one prediction characteristic for the agricultural geographic area.
4
The agricultural modeling system of claim 1
1
Wherein the computing resource is configured to scale each data layer with the 3D point cloud data of the agricultural geographic area.
Said server computing resource configured to scale each data layer with the 3D point cloud data of the agricultural geographic area
5
The agricultural modeling system of claim 1
2
The agricultural modeling system of claim 1
Wherein the at least one data layer for the agricultural geographic area comprises a plurality of data layers for the agricultural geographic area comprising a climate data source, a soil survey data source, a satellite imagery data source, and a tree phenotyping data source.
Wherein the at least one data layer for the agricultural geographic area comprises a plurality of data layers for the agricultural geographic area comprising a climate data source, a soil survey data source, a satellite imagery data source, and a tree phenotyping data source.
6
The agricultural modeling system of claim 1
4
The agricultural modeling system of claim 1
Wherein the 3D point cloud data comprises a Keyhole Markup Language polygon defining the agricultural geographic area.
Wherein the 3D point cloud data comprises a Keyhole Markup Language polygon defining the agricultural geographic area.
7
The agricultural modeling system of claim 1
7
The agricultural modeling system of claim 1
Wherein the computing resource is configured to generate a different multi-layered data model for each client device using a respective different at least one data layer.
Wherein the computing resource is configured to generate a different multi-layered data model for each client device using a respective different at least one data layer.
8
The agricultural modeling system of claim 1
8
The agricultural modeling system of claim 1
Wherein the given client device comprises a notebook client device; and
Wherein the given client device comprises a notebook client device; and
Wherein the at least one data layer is associated with at least one notebook workflow.
Wherein the at least one data layer is associated with at least one notebook workflow.
9
The agricultural modeling system of claim 1
9
The agricultural modeling system of claim 1
Wherein the scanning platform comprises at least one of an airborne platform and a ground platform.
Wherein the scanning platform comprises at least one or an airborne platform and a ground platform.
Regarding current claim 1, claim 1 of US 11,468,632 B2 teaches all of the limitations of current claim 1 except for the following which are taught by Howell:
Generate at least one prediction characteristic for the agricultural geographic area (Paragraph 70, For example, in one embodiment image processing techniques (for example based on colour composition and/or Al-based image classification) is used thereby to perform an automated prediction of vegetation and/or soil characteristics).
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the teachings of Howell in the same field of 3D modeling of agricultural land and generate at least one prediction characteristic for the agricultural area. Doing so would have allowed the user to interactively overlay additional information on the visualization that the user may find to be useful (Howell, [0042]).
Additionally, it would have been obvious for a person of ordinary skill in the art to substitute a mobile LiDAR platform for a scanning platform to perform the method of current claim 1. Doing so would have allowed for scanning using any platform regardless of mobility or type.
Current claims 10 and 17 correspond to current claim 1 and are therefore rejected for the same reasons as used above.
Current claim 13 corresponds to current claim 4 and is therefore rejected for the same reasons as used above.
Current claim 14 corresponds to current claim 5 and is therefore rejected for the same reasons as used above.
Current claim 15 corresponds to current claim 6 and is therefore rejected for the same reasons as used above.
Current claim 16 corresponds to current claim 7 and is therefore rejected for the same reasons as used above.
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, 7, 9-10 and 16-17 are rejected under 35 U.S.C. 103 as being unpatentable over Gurzoni (US 20200019777) in view of Howell (WO 2021134114) and further in view of Jeppesen (“Open geospatial infrastructure for data management and analytics in interdisciplinary research”).
Regarding claim 1, Gurzoni teaches an agricultural modeling system for processing data for an agricultural geographic area, the agricultural modeling system comprising:
A scanning platform configured to generate three-dimensional (3D) point cloud data of the agricultural geographic area (Paragraph 9, collecting, with the inspection system, area data comprising laser-scan data (e.g., LiDAR scan data, stereoscopic cameras, etc.); Paragraph 68, The pre-processing of the laser scan data 120 may generate the PP laser scan data 186 as a point cloud);
Store at least one data layer for the agricultural geographic area (Figure 1, Map 114; Figure 3, Storage Devices 168) and having a resolution less than or equal to the 3D point cloud data of the agricultural geographic area (Paragraph 192, The point cloud reconstruction may be assembled from captured LiDAR scans);
Plurality of client devices (Paragraph 34, The datacenter 108 may provide the processing and analysis for a number of different users (i.e., clients) of the system);
The computing resource configured to geographically reference and fuse the additional data source and the 3D point cloud data of the agricultural geographic area (Paragraph 98, The datacenter 108 combines the processed and segmented image data and the 3D point cloud data to generate a 3D model of each plant 422. The datacenter 108 combines the geo-reference data 124, the 3D model of each plant, and the analysis results 126 to generate a 3D map 114 of the plant area 424. The dashboard 110 displays the 3D map 114 and the analysis results 126 to the user 426);
Generate at least one prediction characteristic for the agricultural geographic area (Paragraph 84, In some embodiments, the dashboard 110 may receive the various outputs (e.g., fused 3D image data, segmented images and associated ID, geo-reference data, environment data, disease estimates and identification, maturity estimation, etc.) from the datacenter 108 to be displayed in various formats (e.g., charts, graphs, lists, etc.) on a graphical user interface of the dashboard 110).
While Gurzoni fails to disclose the following, Howell teaches:
A geospatial database (Paragraph 44, The AgTwin interface provided by system 100 utilizes 3D mapping and imaging data maintained in a database 130. This includes data provided by one or more 3D mapping/imaging data generation systems 120);
Having a resolution less than or equal to the 3D point cloud data of the agricultural geographic area (Paragraph 50, localized high-resolution 3D models (for example via LiDAR scanning); Paragraph 55, Section iv, specific areas of crops are scanned at close range using LiDAR equipment; Paragraph 15, render the three-dimensional object with a secondary overlay generated based on any one or more of: (i) lower-resolution satellite imagery);
A computing resource in communication with the scanning platform (Figure 1, "Data Center" (server) is in communication with the "Transport Device" that collects "Laser Scan Data 120" (LiDAR data)), a plurality of client devices (Taught by Gurzoni), and the geospatial database (Paragraph 44, The AgTwin interface provided by system 100 utilises 3D mapping and imaging data maintained in a database 130. This includes data provided by one or more 3D mapping/imaging data generation systems 120), the computing resource configured to geographically reference the at least one data layer fused with the 3D point cloud data of the agricultural geographic area (Taught by Gurzoni);
Generate a multi-layered data model for the geographically referenced at least one data layer fused with the 3D point cloud data of the agricultural geographic area (Paragraph 42, An AgTwin in preferred embodiments operates by providing a visualization layer (defined by a 3D model, for example a photomosaic defined by photogrammetry methods, a digital terrain model, or the like), which facilitates visual review of the region and a control layer (for example defined by a shape file or the like) which covers substantially the same region as the visualization later and allows identification of locations of user interactions with the model in the context of user interface control operations (for example selection of an asset or field). Additional visualization layers are able to be defined by using a point cloud, digital surface model and/or digital terrain model, and assigning colour values to points/pixels based on a defined algorithm which assigns an information value to each pixel (for example an elevation, upstream flow metric, slope gradient, or the like) thereby to enable delivery of information overlays (optionally with controllable variable transparency));
Howell and Gurzoni are both considered to be analogous to the claimed invention because they are in the same field of 3D modeling of agricultural land. Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have modified Gurzoni to incorporate the teachings of Howell and use a geospatial database, have a scan resolution be less than or equal to the resolution of the point cloud data, use a computing resource in communication with a scanning platform, and generate a multi-layered model for the data layer fused with the 3D point cloud data. Doing so would have allowed for more efficient and more effective means to store large massive amounts of data and allowed the user to interactively overlay additional information on the visualization that the user may find to be useful (Howell, [0042]).
While the combination of Gurzoni and Howell fails to disclose the following, Jeppesen teaches:
A given client device from the plurality of client devices and configured to upload an additional data source (Section 4.1 On the GeoNode web interface, data can be uploaded manually by a user; Section 4.3, GeoNode provides a web interface with a user-based system for up loading, downloading, and visualizing GIS data);
Jeppesen and the combination of Gurzoni and Howell are both considered to be analogous to the claimed invention because they are in the same field of 3D modeling of agricultural land. Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have modified the combination of Gurzoni and Howell to incorporate the teachings of Jeppesen and use a given client device and upload an additional data source. Doing so would have allowed the client devices to send any needed or unique data from their spatial map dataset to the server for processing (Jeppesen, Section 4.1).
Apparatus claim 10 and method claim 17 correspond to system claim 1. Therefore, claims 10 and 17 are rejected for the same reasons as used above.
Regarding claim 7, the combination of Gurzoni, Howell, and Jeppesen teaches the agricultural modeling system of claim 1. While the combination as presented previously fails to disclose the following, Howell further teaches:
Wherein the computing resource is configured to generate a different multi-layered data model for each client device using a respective different at least one data layer (Paragraph 49, to provide a AgTwin interface for a respective client (defined by a client account, which may be accessed via one or more client systems in the form of networked computing devices); Paragraph 50, Activate/deactivate various available information overlays based on operation of an overlay data generation module, for example overlays generated based on: measured attuites of the topography (e.g. colour coding land areas based on slope gradient or altitude); attributes generated based on data from external data/imaging systems 140, which are received via an input module).
Howell and the combination of Gurzoni and Jeppesen are both considered to be analogous to the claimed invention because they are in the same field of 3D modeling of agricultural land. Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have modified the combination of Gurzoni and Jeppesen to incorporate the teachings of Howell and generate different multi-layered data models for each client device using a respective at least one data layer. Doing so would have allowed for more precise customization on their own particular view of the visualization data.
Apparatus claim 16 corresponds to system claim 7. Therefore, claim 16 is rejected for the same reasons as used above.
Regarding claim 9, the combination of Gurzoni, Howell, and Jeppesen teaches the agricultural modeling system of claim 1 wherein the scanning platform comprises at least one of an airborne platform and a ground platform (Gurzoni, Paragraph 36, the transport device 106 may comprise a vehicle such as a tractor or other farm machinery, an all-terrain vehicle (ATV), a four-wheeler, an aerial drone or other aerial device, a robot, or other suitable transport device).
Claims 2, 11 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Gurzoni in view of Howell and further in view of Jeppesen as applied to claims 1, 7, 9-10 and 16-17 above and further in view of Cui (CN 106713342).
Regarding claim 2, the combination of Gurzoni, Howell, and Jeppesen teaches the agricultural model system of claim 1, wherein the at least one prediction characteristic comprises a plurality thereof, the plurality of prediction characteristics comprising a yield characteristic for the agricultural geographic area (Gurzoni, Paragraph 84, As a result, properties may be presented to the user via the dashboard 110 including growth stage, estimated crop yield), a crop fertility characteristic for the agricultural geographic area (Gurzoni, Paragraph 84, the dashboard 110 may receive the various outputs (e.g., fused 3D image data, segmented images and associated ID, geo-reference data, environment data, disease estimates and identification, maturity estimation, etc.)).
While the combination fails to disclose the following, Cui teaches:
An irrigation characteristic for the agricultural geographic data (Page 2, Paragraph 5, for real-time prediction of irrigation and really realizes the timely and proper water for floor plan).
Cui and the combination of Gurzoni, Howell, and Jeppesen are both considered to be analogous to the claimed invention because they are in the same field of 3D modeling of agricultural land. Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have modified the combination of Gurzoni, Howell, and Jeppesen to incorporate the teachings of Cui and predict an irrigation characteristic for an agricultural geographic area. Doing so would have allowed for determining which crops will thrive in that particular area.
Apparatus claim 11 and method claim 18 correspond to system claim 2. Therefore, claims 11 and 18 are rejected for the same reasons as used above.
Claims 3, 12 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Gurzoni in view of Howell and further in view of Jeppesen as applied to claims 1, 7, 9-10 and 16-17 above and further in view of McPeek (US 20170016870).
Regarding claim 3, the combination of Gurzoni, Howell, and Jeppesen teaches the agricultural model system of claim 1. While the combination fails to disclose the following McPeek teaches:
Wherein the computing resource is configured to generate the at least one prediction characteristic for the agricultural geographic area using a model operating based upon at least a combination of processed plant data and actual yield (Paragraph 26, A grower may then associate yield measurements with other information measured by each plant. This allows growers to compare predicted yields for each plant to actual harvest data for verification).
McPeek and the combination of Gurzoni, Howell, and Jeppesen are both considered to be analogous to the claimed invention because they are in the same field of 3D modeling of agricultural land. Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have modified the combination of Gurzoni, Howell, and Jeppesen to incorporate the teachings of McPeek and generate the prediction characteristic using a combination of processed plant data and actual yield. Doing so would have allowed for alerting growers to underperforming assets (McPeek, Paragraph 26).
Apparatus claim 12 and method claim 19 correspond to system claim 3. Therefore, claims 12 and 19 are rejected for the same reasons as used above.
Claims 4, 13 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Gurzoni in view of Howell and further in view of Jeppesen as applied to claims 1, 7, 9-10 and 16-17 above and further in view of Xu (US 20190096086).
Regarding claim 3, the combination of Gurzoni, Howell, and Jeppesen teaches the agricultural model system of claim 1. While the combination fails to disclose the following Xu teaches:
Wherein the computing resource is configured to scale each data layer with the 3D point cloud data of the agricultural geographic area (Paragraph 48, Thus, at 512, each point in the point cloud may be projected onto an image plane. Once projected, a feature patch may then be extracted around the point at an intermediate layer of the image processing algorithm, and the patch may be resized to a fixed size feature vector using bilinear interpolation).
Xu and the combination of Gurzoni, Howell, and Jeppesen are both considered to be analogous to the claimed invention because they are in the same field of 3D point clouds. Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have modified the combination of Gurzoni, Howell, and Jeppesen to incorporate the teachings of Xu and scale each data layer with the 3D point cloud data. Doing so would have allowed for processing individual layers of point cloud data and customizing the output.
Apparatus claim 13 and method claim 20 correspond to system claim 4. Therefore, claims 13 and 20 are rejected for the same reasons as used above.
Claims 5 and 14 are rejected under 35 U.S.C. 103 as being unpatentable over Gurzoni in view of Howell and further in view of Jeppesen as applied to claims 1, 7, 9-10 and 16-17 above and further in view of Johnson (US 20130174040) and Dungey (“Phenotyping whole forests will help to track genetic performance”).
Regarding claim 5, the combination of Gurzoni, Howell, and Jeppesen teaches the agricultural model system of claim 1. While the combination fails to disclose the following Johnson teaches:
Wherein the at least one data layer for the agricultural geographic area comprises a plurality of data layers for the agricultural geographic area comprising a climate data source (Paragraph 58, Exemplary historical data may include, for example, information related to previously planted crops and climate data), a soil survey data source (Paragraph 58, Exemplary geographic data may include, for example, information related to an area of land (e.g., size, location, etc.), soil attributes (e.g., soil types, texture, organic matter, fertility, etc.) ), a satellite imagery data source (Paragraph 55, Geographic/geologic data 250 may be derived from a variety of sources, such as satellite images).
Johnson and the combination of Gurzoni, Howell, and Jeppesen are both considered to be analogous to the claimed invention because they are in the same field of 3D point clouds. Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have modified the combination of Gurzoni, Howell, and Jeppesen to incorporate the teachings of Johnson and include data layers for climate data, soil data, and satellite imagery. Doing so would have allowed for a user to better visualize the available data and to better plan crop planting (Johnson, Paragraph 6).
While the combination fails to disclose the following, Dungey teaches:
A tree phenotyping data source (Figure 4, “Phenotypic models” is an input to “Site index” layer visualization).
Dungey and the combination of Gurzoni, Howell, Jeppesen, and Johnson are both considered to be analogous to the claimed invention because they are in the same field of 3D point clouds. Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have modified the combination of Gurzoni, Howell, Jeppesen, and Johnson to incorporate the teachings of Dungey and include a tree phenotype data source. Doing so would have improved the genetic traits of the trees being planted (Dungey, Page 861, Paragraph 2).
Apparatus claim 14 corresponds to system claim 4. Therefore, claim 14 is rejected for the same reasons as used above.
Claims 6 and 15 are rejected under 35 U.S.C. 103 as being unpatentable over Gurzoni in view of Howell and further in view of Jeppesen as applied to claims 1, 7, 9-10 and 16-17 above and further in view of Schubert (US 20190129039).
Regarding claim 5, the combination of Gurzoni, Howell, and Jeppesen teaches the agricultural model system of claim 1. While the combination fails to disclose the following Schubert teaches:
Wherein the 3D point cloud data comprises a Keyhole Markup Language polygon defining the agricultural geographic area (Paragraph 121, Convert the text file of boxes to KML for visualization in a 3D map).
Schubert and the combination of Gurzoni, Howell, and Jeppesen are both considered to be analogous to the claimed invention because they are in the same field of 3D point clouds. Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have modified the combination of Gurzoni, Howell, and Jeppesen to incorporate the teachings of Schubert and use a Keyhole Markup Language polygon to define the geographic area. Doing so would have allowed for storing the map data into an open data standard format that is compatible with many geographic visualization programs.
Apparatus claim 15 corresponds to system claim 6. Therefore, claim 15 is rejected for the same reasons as used above.
Claim 8 is rejected under 35 U.S.C. 103 as being unpatentable over Gurzoni in view of Howell and further in view of Jeppesen as applied to claims 1, 7, 9-10 and 16-17 above and further in view of Thomson (US 20200144849).
Regarding claim 8, the combination of Gurzoni, Howell, and Jeppesen teaches the agricultural model system of claim 1. While the combination fails to disclose the following Thomson teaches:
Wherein the given client device comprises a notebook client device (Paragraph 61, client device 1100A is depicted as a laptop/notebook computer); and
Wherein the at least one data layer is associated with at least one notebook workflow (Paragraph 58, the collected data is transmitted to another server or a mapping module on ground that may be configured to perform route mapping).
Thomson and the combination of Gurzoni, Howell, and Jeppesen are both considered to be analogous to the claimed invention because they are in the same field of 3D point clouds. Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have modified the combination of Gurzoni, Howell, and Jeppesen to incorporate the teachings of Thomson associate at least notebook workflow with at least one data layer. Doing so would have allowed for conveniently transporting the computer while maintaining a larger screen than a mobile phone.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SNIGDHA SINHA whose telephone number is (571)272-6618. The examiner can normally be reached Mon-Fri. 12pm-8pm.
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, Jason Chan can be reached at 571-272-3022. 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.
/SNIGDHA SINHA/Examiner, Art Unit 2619
/JASON CHAN/Supervisory Patent Examiner, Art Unit 2619
Prosecution Insights