DETAILED ACTION
[1] Remarks
I. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
II. This Office Action is in response to the RCE filed on 06/29/2026.
III. Claims 1-5 and 7-21 are pending and have been examined, where claims 1-5 and 7-14 is/are found rejected and claims 15-21 are withdraw from consideration.
IV. Inventor and/or assignee search were performed and determined no double patenting rejection(s) is/are necessary.
V. Patent eligibility (updated in 2019) shown by the following: Claims 1-14 pass patent eligibility test because there is/are no limitation or a combination of limitations amounting to an abstract idea. Also, the following limitation or the combinations of the limitations:
“determining a georeferenced parcel image for a property parcel associated with a set of location descriptions, wherein the georeferenced parcel image is determined by filtering a remote 2D image using a 2D parcel mask to isolate pixels defining a boundary of the property parcel from the remote 2D image” effects a transformation or a reduction of a particular article to a different state or thing / adds a specific limitation(s) other than what is well-understood, routine and conventional in the field, or adding unconventional steps that confine the claim to a particular useful application and providing improvements to the technical field of parcel size determination, which recite additional elements that integrate the judicial exception into a practical application and amounting significant more.
[2] Response to Arguments
The arguments presented by the applicant have been considered and are found unconvincing.
The applicant stated:
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The examiner disagrees. The amendment filed does not overcomes the current prior art rejection. The remote sensing image shown in figure 8 is a two-dimensional image.
McLaughlin (US 20120321129) discloses determining a georeferenced parcel image for a property parcel associated with a set of location descriptions, wherein the georeferenced parcel image is determined by filtering a remote 2D image using a 2D parcel mask to isolate pixels defining a boundary of the property parcel from the remote 2D image (see paragraphs 42 and 43, FIG. 8 illustrates the sample area following application of a land parcel boundary data mask, as described above, to remove clutter, the red polygons in FIG. 8 illustrate areas remaining following the application of the land parcel boundary data mask, data for these areas remain in the building units data set, a slope filter is applied to the data representative of potential building unit rooftops to remove tree clutter, the slope filter is based on the differences in the slopes of rooftops and trees, figure 8 showing masks and boundaries of each property, also see figure 8 below):
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The arguments presented by the applicant is unconvincing.
[3] Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
Use of the word “means” (or “step for”) in a claim with functional language creates a rebuttable presumption that the claim element is to be treated in accordance with 35 U.S.C. 112(f) (pre-AIA 35 U.S.C. 112, sixth paragraph). The presumption that 35 U.S.C. 112(f) (pre-AIA 35 U.S.C. 112, sixth paragraph) is invoked is rebutted when the function is recited with sufficient structure, material, or acts within the claim itself to entirely perform the recited function. Absence of the word “means” (or “step for”) in a claim creates a rebuttable presumption that the claim element is not to be treated in accordance with 35 U.S.C. 112(f) (pre-AIA 35 U.S.C. 112, sixth paragraph). The presumption that 35 U.S.C. 112(f) (pre-AIA 35 U.S.C. 112, sixth paragraph) is not invoked is rebutted when the claim element recites function but fails to recite sufficiently definite structure, material or acts to perform that function.
Claim elements in this application that use the word “means” (or “step for”) are presumed to invoke 35 U.S.C. 112(f) except as otherwise indicated in an Office action. Similarly, claim elements that do not use the word “means” (or “step for”) are presumed not to invoke 35 U.S.C. 112(f) except as otherwise indicated in an Office action.
Claim(s) 1-5 and 7-21 do not require 35 U.S.C. 112(f) or pre-AIA U.S.C. 112 6th paragraph interpretation because they are method claims and / or they are CRM claims.
Upon examination of the specification and claims, the examiner has determined, under the best understanding of the scope of the claim(s), rejection(s) under 35 U.S.C. 112(a)/(b) is not necessitated because of the following reasons: sufficient support are provided in the written description / drawings of the invention.
[4] Grounds of Rejection
Claim Rejections - 35 USC § 103
1. 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.
2. Claims 1, 3-5, and 7-13 is/are rejected under 35 U.S.C. 103 as being unpatentable over Ananthakrishnan (US 20170091578) in view of Krumm (US 20100023259) and McLaughlin (US 20120321129).
Regarding claim 1, Ananthakrishnan discloses a method, comprising:
determining a georeferenced parcel image for a property parcel associated with a set of location descriptions (see paragraph 49, in 200 a location information is received, a user provides a location of a residence, site, commercial building, or other location that needs to be assessed for a solar installation, see figure 2, 200);
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wherein the georeferenced parcel image is determined by filtering a remote image using a parcel mask to isolate pixels associated with the property parcel from the remote image (FIGS. 10A and 10B are example images illustrating a point cloud generated by an embodiment of a system for determining a viable area, where the images of FIGS. 10A and 10B are generated by viable solar area determination system 104 of FIG. 1, where FIG. 10A shows an example point cloud for a residential location with three-dimensional information extracted and displayed as a projected view, roof area 1000, where the extraction of the three dimensional residential location is read as the filtering process and the light areas are read as the portions where the image is isolated from the rest of the image, see paragraph 114);
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determining a set of image features, each associated with a built structure class, within the georeferenced parcel image (see paragraph 49, automated feature extraction and identification technology takes high-resolution geospatial data for large geographic areas, parses the data into features, e.g., defined in X, Y, Z coordinates and by various qualities of the image and objects, such as spectral qualities);
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for each image feature in the set of image features, determining a location of interest within the image feature (see figure 2, 210, paragraph 64, 210, viable areas are determined, where an unobstructed roof plane is identified by isolating the corners of the roof and then determining the points that are outlined by the corners that lie within a plane, where the corners are the image feature in a set of image features); and
storing an association between the locations of interest and the set of location descriptions (see paragraph 48, points classified as structure are then grouped as being associated with planes in the event that they neighbor each other and have the same orientation, points assigned to other classifications are grouped by such criteria as: material composition, geometric proximity, and similarity to stored generic object primitives that could include trees, bushes, vent pipes, rooftop heating and air conditioning equipment, parking lot layouts, etc.).
Ananthakrishnan is silent in disclosing determining an association between the locations of interest and the set of location descriptions. Krumm discloses determining an association between the locations of interest and the set of location descriptions (see figure 8, 804 and 806, a description for the POI can be identified based upon the analysis of the map annotation data gathered, annotations from users can be filtered, analyzed, and collected in order to identify n-grams for each user-defined location):
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It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to include determining an association between locations of interest and location descriptions is crucial in urban planning, geographic information systems (GIS), and even targeted advertising, where it helps in understanding the rich tapestry of characteristics, relationships, and meanings associated with a place.
Ananthakrishnan and Krumm are silent in disclosing determining a georeferenced parcel image for a property parcel associated with a set of location descriptions, wherein the georeferenced parcel image is determined by filtering a remote 2D image using a 2D parcel mask to isolate pixels defining a boundary of the property parcel from the remote 2D image.
McLaughlin discloses determining a georeferenced parcel image for a property parcel associated with a set of location descriptions, wherein the georeferenced parcel image is determined by filtering a remote 2D image using a 2D parcel mask to isolate pixels defining a boundary of the property parcel from the remote 2D image (see paragraphs 42 and 43, FIG. 8 illustrates the sample area following application of a land parcel boundary data mask, as described above, to remove clutter, the red polygons in FIG. 8 illustrate areas remaining following the application of the land parcel boundary data mask, data for these areas remain in the building units data set, a slope filter is applied to the data representative of potential building unit rooftops to remove tree clutter, the slope filter is based on the differences in neighboring pixel intensities of rooftops and trees, figure 8 showing masks and boundaries of each property, also see figure 8 below):
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It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to include using a 2D parcel mask to isolate pixels defining a boundary of the property parcel from the remote image in order to overcomes the restrictions of manual drawing and fully-automated pixel-level analysis by focusing only on the relevant boundary areas defined by map.
Regarding claim 3, Ananthakrishnan discloses the method of Claim 1, wherein the georeferenced parcel image is a segment of a remote image (see figure 10A above, the image above is taken remotely from the parcel property).
Regarding claim 4, Ananthakrishnan discloses the method of Claim 3, further comprising determining the georeferenced parcel image by aligning a georeferenced property parcel with the remote image, based on the respective georeferences (paragraph 119, Set of panels 1508 and set of panels 1510 are shown superimposed on roof of residential structure, FIG. 15B shows an example active area with different levels of solar irradiance as determined for square tiles of the active area and panel layout).
Regarding claim 5, Ananthakrishnan discloses the method of Claim 3, wherein the remote image comprises a plurality of parcels, each associated with a set of location descriptions, wherein the method is repeated for each parcel of the plurality (see paragraph 23, where the metadata comprises digital information assigned to an extracted data point, for example, X,Y,Z coordinates, pixel size, ground resolution, infrared data, etc.).
Regarding claim 7, Ananthakrishnan discloses the method of Claim 1, wherein the georeferenced parcel image is determined based on a parcel boundary associated with the property parcel, wherein the parcel boundary is determined from the georeferenced parcel image using a machine learning algorithm (see figure 6, 600, structure corners is part of the parcel boundary, also see paragraph 77, a process for classifying points and extracting features. In some embodiments, machine learning is used to generate classifications and extracted features):
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Regarding claim 8, Ananthakrishnan discloses the method of Claim 1, wherein the set of location descriptions is associated with a parcel identifier for the property parcel (see paragraphs 36 and 37, features extraction with associated x, y, z coordinates from the 3D point cloud; and feature assignment to individual parcels/sites including their relative positions in 3D space).
Regarding claim 9, Ananthakrishnan discloses the method of Claim 1, wherein the set of location descriptions comprise multiple location descriptions (see paragraph 48, using overlapping aerial photos to determine 3-dimensional coordinates associated with objects located at the input location, where the multiple aerial photos include), wherein storing the association comprises storing an association between a single location of interest and each location description in the set (see paragraph 48, points classified as structure are then grouped as being associated with planes in the event that they neighbor each other and have the same orientation, points assigned to other classifications are grouped by such criteria as: material composition, geometric proximity, and similarity to stored generic object primitives that could include trees, bushes, vent pipes, rooftop heating and air conditioning equipment, parking lot layouts, etc.).
Regarding claim 10, Ananthakrishnan discloses the method of Claim 1, further comprising selecting a primary image feature from the set based on the associated built structure class (see paragraph 25, input as latitude and longitude, selected graphically from a user input screen, input as part of a batch file of multiple addresses of interest); wherein the set of location descriptions is associated with the location of interest for the primary image feature (see paragraph 36, features extraction with associated x, y, z coordinates from the 3D point cloud).
Regarding claim 11, Ananthakrishnan discloses the method of Claim 1, wherein each of the set of location descriptions comprises an address (see paragraph 25, the address of their geographic site, which could be input as a postal address, input as latitude and longitude, selected graphically from a user input screen); and wherein each location of interest comprises geographic coordinates (see paragraph 25, selected graphically from a user input screen, input as part of a batch file of multiple addresses of interest).
Regarding claim 12, Ananthakrishnan discloses the method of Claim 1, further comprising, for each image feature, determining the built structure class associated with the image feature, wherein the built structure class is retrieved from a database (see paragraph 98, (1) from various and diverse sources, such as third-party and proprietary databases, or (2) extracted from the feature data, are overlaid onto the feature set, such site-related information includes property owner, address, size of mounting plane).
Regarding claim 13, Ananthakrishnan discloses the method of Claim 1, further comprising determining a count of the image features and storing the count in association with the property parcel (see paragraph 119, Set of panels 1508 and set of panels 1510 are shown superimposed on roof of residential structure, see figure 15A illustration below):
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3. Claims 2 is/are rejected under 35 U.S.C. 103 as being unpatentable over Ananthakrishnan (US 20170091578) in view of Krumm (US 20100023259), McLaughlin (US 20120321129) and Lewis (US 20180089833).
Regarding claim 2, Ananthakrishnan, Krumm, and McLaughlin disclose all the limitations of claim 1, but is silent in disclosing the method of Claim 1, wherein each image feature is segmented from the georeferenced parcel image using instance-based segmentation. Lewis discloses the method of Claim 1, wherein each image feature is segmented from the georeferenced parcel image using instance-based segmentation (see paragraph 35, networks can be utilized that perform instance segmentation instead of merely semantic segmentation).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to include using instance-based segmentation on georeferenced parcel images provides more precise object extraction and allows for the accurate identification and differentiation of individual parcels, enabling land classification, target detection, and environmental monitoring.
4. Claims 14 is/are rejected under 35 U.S.C. 103 as being unpatentable over Ananthakrishnan (US 20170091578) in view of Krumm (US 20100023259), McLaughlin (US 20120321129) and Revell (US 20180012060).
Regarding claim 14, Ananthakrishnan, Krumm, and McLaughlin discloses all the limitations of claim 1, but is silent in disclosing the method of Claim 1, wherein the location of interest comprises a geometric centroid of the image feature. Revell discloses the method of Claim 1, wherein the location of interest comprises a geometric centroid of the image feature (see paragraph 5, determining the geometric representation of the image segment may comprise determining a centroid of the image segment and, using the determined centroid, determining the geometric representation).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to include a geometric centroid of the image feature because
the centroid can be used to represent the location of an object or feature within an image, where the centroid offers a simple and efficient way to characterize the spatial distribution of an object or feature improving object recognition.
CONTACT INFORMATION
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ALEX LIEW (duty station is located in New York City) whose telephone number is (571)272-8623 (FAX 571-273-8623), cell (917)763-1192 or email alexa.liew@uspto.gov. Please note the examiner cannot reply through email unless an internet communication authorization is provided by the applicant. The examiner can be reached anytime.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, MISTRY ONEAL R, can be reached on (313)446-4912. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see http://pair-direct.uspto.gov. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/ALEX KOK S LIEW/Primary Examiner, Art Unit 2674 Telephone: 571-272-8623
Date: 7/25/26
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