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 .
Claims 1-20 have been presented for examination.
Claims 1-20 are rejected.
Claim Objections
Claims 1, 5 and 15 are objected to because of the following informalities:
claim 1 line 10 recites “point could” which should read “point cloud”.
Claims 5 and 15 have similar issues. Appropriate correction is required.
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 1-20 are provisionally rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-23 of copending Application No. 17/994,912 (reference application). Although the claims at issue are not identical, they are not patentably distinct from each other.
Claims 1-20 are provisionally rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-20 of copending Application No. 18/071,207 (reference application). Although the claims at issue are not identical, they are not patentably distinct from each other.
This is a provisional nonstatutory double patenting rejection because the patentably indistinct claims have not in fact been patented.
Claims 1-20 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-20 of U.S. Patent No. 12353803. Although the claims at issue are not identical, they are not patentably distinct from each other.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1–20 are rejected under 35 U.S.C. § 101 because the claimed invention is directed to a judicial exception to patent-eligible subject matter, specifically a mental process, and the claims do not include additional elements that amount to significantly more than the judicial exception.
Step 1: Statutory Category
The claims are directed to a system and method for modeling obstructions to sunlight at a site, which fall within the statutory categories of process and machine.
Step 2A, Prong One: Judicial Exception (Abstract Idea – Mental Process)
Claim 1 recites steps that can be performed in the human mind or with the aid of pen and paper, such as the following bolded limitations:
A system to model obstructions to sunlight, comprising: a network interface to couple to one or more client computing devices over a communication network; memory to store one or more of point cloud data and computer-readable instructions that when executed by a processor cause the system to perform operations; and one or more processors to execute the computer-readable instructions to cause the system to perform operations to:
access point cloud data for a site; identify one or more surfaces of interest at the site from the point could data; model the point cloud data to generate a site representation of the site that includes the one or more surfaces of interest and one or more objects at the site that are around the one or more surfaces of interest; simulate a path of the sun with respect to the site representation to identify areas of the one or more surfaces of interest that are shaded from the sun; mask surface of interest points of the point cloud; and determine a shade metric at each point of each of the one or more surfaces of interest.
The examiner submits that the bolded steps under their broadest reasonable interpretation fall within the “mental processes” grouping of abstract ideas in that it recites a concept performed in the human mind as an observation, judgement, evaluation, or opinion. For example, under the broadest reasonable interpretation of the claim in light of the specification, a person can receive or access data about a site (e.g., visualizing a property), identify surfaces of interest (e.g., mentally recognizing roof areas), model the site and surrounding objects (e.g., sketching or imagining the site layout), simulate the path of the sun to determine shaded areas (e.g., mentally tracing sun angles and shadows throughout the day/year), determine where shade will fall and calculate a “shade metric” (e.g., estimating how much sunlight a surface receives) and generate a proposal or visual representation (e.g., drawing or describing a suggested installation).
These steps, as recited in the claim, are abstract ideas because they can be performed as mental processes, either in the human mind or with pen and paper, without a particular improvement to computer technology or another technical field.
Step 2A, Prong Two: Integration Into a Practical Application
The underlined limitations above of claim 1 do not recite any additional elements that integrate the abstract idea into a practical application. The recited “network interface,” “memory,” and “processor” are generic computer components performing their basic functions of receiving, storing, and processing data. The claim does not specify a particular improvement to the functioning of a computer or another technology, nor do they recite any unconventional technical solution.
Thus, taken alone, the additional elements do not integrate the abstract idea into a practical application. Further, looking at the additional limitation(s) as an ordered combination or as a whole, the limitation(s) add nothing that is not already present when looking at the elements taken individually. For instance, there is no indication that the additional elements, when considered as a whole, reflect an improvement in the functioning of a computer or an improvement to another technology or technical field, apply or use the above-noted judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition, implement/use the above-noted judicial exception with a particular machine or manufacture that is integral to the claim, effect a transformation or reduction of a particular article to a different state or thing, or apply or use the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is not more than a drafting effort designed to monopolize the exception (MPEP § 2106.05). Accordingly, the additional limitation(s) do/does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
Step 2B: Significantly More
Claim 1 not include additional elements that amount to significantly more than the abstract idea itself. The use of generic computer components to perform data processing, modeling, and simulation does not transform the abstract idea into patent-eligible subject matter. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. Hence, the claim is not patent eligible.
Independent claim 11 is similar in scope as in claim 1 and is rejected using the same rationale.
Dependent claim(s) 2-10, 12-20 do not recite any further limitations that cause the claims to be directed towards statutory subject matter. Claim 2/12: Further specify obtaining sun positions for phases throughout the year, filtering to daytime, and simulating shade for multiple days. Claim 3/13: Further specify casting rays between sun positions and points, recording intersections, applying insolation values, and calculating irradiance percentages. Claim 4/14: Add identifying objects at the site that are obstructions, based on the shade metric. Claim 5/15: Add that identifying surfaces of interest includes modeling point cloud data to generate a 3D model of an object of interest. Claims 6/16: Specify the object of interest is a structure at the site. Claims 7/17: Specify the surfaces are roof surfaces of a structure. Claims 8/18: Specify the site is a location of a potential solar electrical generation system. Claims 9/19: Add generating a visual representation of the object and obstructions that indicates the shade metric. Claims 10/20: Specify the visual representation is a digital interactive proposal.
These limitations further define the steps by which sun path and shading are modeled. However, the steps (obtaining sun positions, filtering, ray casting, applying values, calculating percentages) are high-level and could be performed conceptually by a human or with pen and paper, using known mathematical or geometric methods. The claims do not require a specific improvement in computer technology or unconventional use of computing resources. While 3D modeling can be computationally intensive, the claim does not require a specific improvement to 3D modeling technology or a particular algorithm. The step is still a generic implementation of modeling, which could be performed conceptually or with conventional tools. Generating a visual or interactive proposal is the presentation of information, which is itself an abstract idea. The claims do not recite a specific technical improvement to the way information is displayed or interacted with. The use of generic computing components to display data does not add “significantly more.” Each of the further limitations expound upon the mental process and do not recite additional elements integrating the mental process into a practical application or additional elements that are not well-understood, routine or conventional (See MPEP § 2106.05). Therefore, dependent claims 2-10, 12-20 are similarly rejected as being directed towards non-statutory subject matter.
Accordingly, claims 1–20 are directed to a mental process, which is a judicial exception to patent-eligible subject matter, and do not recite additional elements that amount to significantly more than the exception. Therefore, the claims are not patent-eligible under 35 U.S.C. § 101.
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over Loveland et al. (USPGPUB No. US 20200293773 A1; hereinafter Loveland) in view of Stevens et al. (USPGPUB No. US 20210272358 A1; hereinafter Stevens).
Regarding claim 1, Loveland teaches a system to model obstructions to sunlight, comprising: a network interface to couple to one or more client computing devices over a communication network ([0096], “For example, the network may connect some of the modules located on the UAV with others connected remotely through the network.”); memory to store one or more of point cloud data and computer-readable instructions that when executed by a processor cause the system to perform operations ([0095]“a network interface”; [0101] “communication networks”); and one or more processors to execute the computer-readable instructions to cause the system to perform operations to:
access point cloud data for a site; ([0100] “The estimator module may use historical data to estimate cloudy, rainy, and/or snowy lengths of time that occlude solar exposure.”; [0052] teaches “a site”)
identify one or more surfaces of interest at the site from the point cloud data; ([0033]; [0137] “… the ray-path modeling subsystem 1694 may identify and conceptually divide the roof surfaces into a plurality of polygons. Each polygon may be approximated as a planar surface, the normal to which represents the ideal angle from which to receive solar radiation.”)
model the point cloud data to generate a site representation of the site that includes the one or more surfaces of interest and one or more objects at the site that are around the one or more surfaces of interest; ([0136] “The ray-path modeling subsystem 1694 may utilize captured images to generate a three-dimensional model that includes the structure, obstacles on the structure, and/or obstacles proximate the structure.”)
simulate a path of the sun with respect to the site representation ([0088] “Again, the ray-path modeling may include ray paths between locations on the roof of the structure and the modeled location of the sun that are reflected off of the neighboring structure.”) to identify areas of the one or more surfaces of interest that are shaded from the sun; ([0089] “Alternatively, as a user digitally places solar panels on a displayed model of the roof, the system may show the user how many kilowatts will be generated per hour, day, week, month, year, lifetime, etc. For example, a 300-watt solar panel in one location on the roof may be expected to collect 100 watts early in the morning, 300 watts in the afternoon, and be shaded in the later afternoon and evening.”)
determine a shade metric at each point of each of the one or more surfaces of interest. ([0042] “the thousands of points on the surface of the roof may be identified, and the solar irradiance ray path tracing to various modeled locations of the sun at various time increments during a time period may be mapped”; [0148] “the graphical user interface generation subsystem 1692 may use the data from the ray-path modeling subsystem 1694 to display a heatmap that uses various shades of gray or different colors (e.g., black body temperature modeling) to illustrate the relative impact or effect of various obstacles and obstructions.”)
Although Loveland discloses that “Again, blocked ray paths correspond to shadows. For example, a relatively large chimney may cast very little or no shadow (i.e., block relatively few ray paths) on a rooftop when the sun is directly overhead.” See [0039]
Loveland does not appear to expressly teach:
mask surface of interest points of the point cloud;
However Stevens teaches mask surface of interest points of the point cloud; (Stevens, [0063] “Roof face segmentation module 1203 uses a neural network to generate a mask for each roof face using instance segmentation”)
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the instant application to have combined the (3D) building model estimation of Loveland to include the masking features of Stevens; which would provide with high accuracy the usable area of a 3D roof top model for purposes of designing and simulating a virtual solar energy system that can output performance data that can be used to design an actual solar energy system that achieves the user's target energy savings goal and other user goals as disclosed in Stevens [0006].
Regarding claim 2, Loveland in combination with Stevens teaches the system of claim 1, Loveland further teaches wherein simulating the path of the sun with respect to the site representation comprises: obtaining sun positions for a plurality of points in time that is representative of phases throughout the year given a geolocation of the site; filtering the sun positions to daytime sun positions; filtering further to sun positions for multiple days of a year; and representing the sun positions for each of the multiple days of the year to simulate shade on the one or more surfaces of interest. (Loveland [0036]; [0038] [0043])
Regarding claim 3, Loveland in combination with Stevens teaches the system of claim 1, Stevens further teaches wherein determining a shade metric at each point of each of the one or more surfaces of interest comprises: casting a ray between the sun positions and each surface of interest point in the point cloud checking for any intersections with the site representation; recording, for each given surface of interest point, intersections with the site representation of the ray cast from a given sun position to the given surface of interest point; applying an insolation value to the surface of interest points without intersections; and summing insolation values for each given point and dividing by a total possible irradiance for the given point producing a percentage of total irradiance at the given point.(Stevens, [0078])
Regarding claim 4, Loveland in combination with Stevens teaches the system of claim 1, Loveland further teaches wherein the one or more processors are further to execute the computer-readable instructions to cause the system to perform operations to identify the objects at the site that are obstructions (Loveland [0007] “FIG. 4 illustrates an example of a UAV performing a 360-degree panoramic scan of a region proximate the structure to identify actual and/or forecasted obstructions.”), based on the shade metric at each point of each of the one or more surfaces of interest. (Loveland [0036] “The three-dimensional model includes other objects in the space that may obstruct a ray path between the modeled location of the sun and a polygon on the roof, depending on the modeled location of the sun for a given day and time. The system may model the ray path between each polygon on the roof surface and the modeled location of the sun at different times of the day and for different days each week.”; Also see [0043])
Regarding claim 5, Loveland in combination with Stevens teaches the system of claim 1, Loveland further teaches wherein identifying the one or more surfaces of interest at the site from the point could data comprises modeling the point cloud data to generate a three dimensional model of an object of interest that includes the one or more surfaces of interest. (Loveland [0136] “The ray-path modeling subsystem 1694 may utilize captured images to generate a three-dimensional model that includes the structure, obstacles on the structure, and/or obstacles proximate the structure.”)
Regarding claim 6, Loveland in combination with Stevens teaches the system of claim 1, Loveland further teaches wherein the one or more surfaces pertain to an object of interest at the site and the object of interest is a structure at the site. (Loveland [0036] “The three-dimensional model includes other objects in the space that may obstruct a ray path between the modeled location of the sun and a polygon on the roof, depending on the modeled location of the sun for a given day and time.”)
Regarding claim 7, Loveland in combination with Stevens teaches the system of claim 1, Loveland further teaches wherein the one or more surfaces are roof surfaces of a structure at the site. (Loveland [0033]; [0137] “… the ray-path modeling subsystem 1694 may identify and conceptually divide the roof surfaces into a plurality of polygons. Each polygon may be approximated as a planar surface, the normal to which represents the ideal angle from which to receive solar radiation.”)
Regarding claim 8, Loveland in combination with Stevens teaches the system of claim 1, Loveland further teaches wherein the site is a location of a potential solar electrical generation system. (Loveland [0053] “Any solar panel installation site may benefit from the systems and methods described. For example, the systems described in this application may be applied with some adaptation or modification to an empty field, a skyscraper, a house, an apartment complex, a commercial building or factory, and/or any other solar panel installation site.”)
Regarding claim 9, Loveland in combination with Stevens teaches the system of claim 1, Stevens further teaches wherein the one or more processors are further to execute the computer-readable instructions to cause the system to perform operations to generate a visual representation of the object of interest and the obstructions that indicates the shade metric of each point of each of the one or more surfaces of interest. (Stevens [0094] “FIG. 27 illustrates shading by ray tracing against a 3D building model, obstructions and surrounding, according to an embodiment. In an embodiment, shading is determined using ray tracing against a 3D model of the building 2700, rooftop obstructions, and its surroundings. The LIDAR mesh (generated from the earlier spike free triangulation step) is used to model the building's surroundings, which can then cast shadows onto the building. For a given point on the roof or on a solar panel, the system calculates, for every hour of a simulated year, whether the solar panel is in shade. Additionally, the system calculates irradiance by combining weather data with shading information. Based on the angle of the solar panel surface relative to the sun, and based on whether the solar panel is in shade or not, the system calculates, for every hour of the simulated year, an amount of sunlight hitting the solar panel surface in W/m.sup.2.”)
Regarding claim 10, Loveland in combination with Stevens teaches the system of claim 9, Loveland further teaches wherein the visual representation is a digital interactive proposal. (Loveland [0030], “Using the collection of images, a rendering system may generate interactive models of the target structure or another object.”)
Claims 11- 20 are rejected under the same rationale, mutatis mutandis, as claims 1-10, above.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Strader (US 12353803 B2) teaches systems and methods to generate highly accurate solar production models in order to present sophisticated, dynamic and/or interactive solar sales proposals.
Campau (US 11928394 B2) teaches Systems and methods for enabling automated roof planning using a processor.
Stevens (US 11830137 B2) teaches an automated three-dimensional (3D) building model estimation.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ANISS CHAD whose telephone number is (571)270-3832 or email aniss.chad@uspto.gov. The examiner can normally be reached M-F 8:00-4:00pm EST.
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/ANISS CHAD/
Supervisory Patent Examiner
Art Unit 3662