DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application is being examined under the pre-AIA first to invent provisions.
Status of Application
This Communication is a Final Office Action in response to the Amendments, Arguments, and Remarks filed on the 22nd day of August, 2025. Currently Claims 1-21 are pending. No claims are allowed.
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 1-21 are rejected under 35 U.S.C. §101 because the claimed invention is directed to judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) with no practical application and without significantly more.
Under MPEP 2106, when considering subject matter eligibility under 35 U.S.C. § 101, it must be determined whether the claim is directed to one of the four statutory categories of invention, i.e., process, machine, manufacture, or composition of matter (step 1). If the claim does fall within one of the statutory categories, it must then be determined whether the claim is directed to a judicial exception (i.e., law of nature, natural phenomenon, and abstract idea) (step 2A prong 1), and if so, it must additionally be determined whether the claim is integrated into a practical application (step 2A prong 2). If an abstract idea is present in the claim without integration into a practical application, any element or combination of elements in the claim must be sufficient to ensure that the claim amounts to significantly more than the abstract idea itself (step 2B).
In the instant case, claims 1-21 are directed to a system, method, and non-transitory computer-readable media. Thus, each of the claims falls within one of the four statutory categories (step 1). However, the claims also fall within the judicial exception of an abstract idea (step 2). While claims 2, 9, and 16, are directed to different categories, the language and scope are substantially the same and have been addressed together below.
Under Step 2A Prong 1, the test is to identify whether the claims are “directed to” a judicial exception. Examiner notes that the claimed invention is directed to an abstract idea in that the instant application is directed to mathematical calculations (see MPEP 2106.04(a)(2)(I), certain methods of organizing human activity specifically commercial interactions and behaviors and managing personal behavior and/or interactions between people (see MPEP 2106.04(a)(2)(II)) and mental processes (see MPEP 2106.04(a)(2)(III).
Examiner notes that claims 1-21 recite a method, system, and apparatus for customizing a real asset, comprising: forming, via one or more computer processors coupled to at least one memory device, a group of digitized parameters representing the real asset; receiving, via a graphical user interface coupled to the one or more computer processors, specified proposed modifications to the real asset; storing, in the at least one memory device, binary digits corresponding to an as- is value of the real asset, binary digits corresponding to an estimate of resources allocated to modify the real asset in accordance with the specified proposed modifications, and an estimated value of the real asset that is to include the specified proposed modifications; computing, based, at least in part, on the estimate of the resources via the one or more computer processors, an amount of a financial resource premium for a proposed agreement between a current owner of the real asset and a first entity that permits [[a]] the first entity to procure the real asset at the as-is value or a specified percentage thereof within a specified period of time and that directs that the financial resource premium be provided by the first entity for the purpose of implementing the specified proposed modifications; and forming a record of materials and/or material specifications based, at least in part, on the specified proposed modifications to the real asset which is directed to concepts that are performed mentally and a product of human mental work. The limitations suggest a process similar to receiving information related to real estate planned improvements and valuations, processing the information and storing the information within the system, and the steps involved human judgments, observations and evaluations that can be practically or reasonably performed in the human mind, the claim recites an abstract idea consistent with the “mental process” grouping set forth in the see MPEP 2106.04(a)(2)(III).
Alternatively, Examiner notes that claims 12-21 recite a method, system, and apparatus for customizing a real asset, comprising: forming, via one or more computer processors coupled to at least one memory device, a group of digitized parameters representing the real asset; receiving, via a graphical user interface coupled to the one or more computer processors, specified proposed modifications to the real asset; storing, in the at least one memory device, binary digits corresponding to an as- is value of the real asset, binary digits corresponding to an estimate of resources allocated to modify the real asset in accordance with the specified proposed modifications, and an estimated value of the real asset that is to include the specified proposed modifications; computing, based, at least in part, on the estimate of the resources via the one or more computer processors, an amount of a financial resource premium for a proposed agreement between a current owner of the real asset and a first entity that permits [[a]] the first entity to procure the real asset at the as-is value or a specified percentage thereof within a specified period of time and that directs that the financial resource premium be provided by the first entity for the purpose of implementing the specified proposed modifications; and forming a record of materials and/or material specifications based, at least in part, on the specified proposed modifications to the real asset, and is similar to the abstract idea identified in MPEP 2106.04(a)(2)(II) in grouping “II” in that the claims recite certain methods of organizing human activity such as real estate transactions. This is merely further embellishments of the abstract idea and does not further limit the claimed invention to render the claims patentable subject matter. The limitations, substantially comprising the body of the claim, recite standard processes found in standard practice in transfer of real estate property for commercial or residential flippers. The purchasers are able to get approval from their respective banks for the purchase of “as-is” properties and associating planned improvement financing to the overall funding agreement. This is common practice in every area of real estate wherein the property is purchased at a price that accounts for the condition of the property, account for potential plans in the granting of funding based on the planned improvements and construction wherein the funding is dispersed based on the completed aspects of the improvements. Because the limitations above closely follow the steps standard in interactions between people and businesses such as real estate transactions such as flipping houses, and the steps of the claims involve organizing human activity, the claim recites an abstract idea consistent with the “organizing human activity” grouping set forth in the see MPEP 2106.04(a)(2)(II).
The conclusion that the claim recites an abstract idea within the groupings of the MPEP 2106.04(a)(2) remains grounded in the broadest reasonable interpretation consistent with the description of the invention in the specification. For example, [App. Spec 5], “a graphical user interface coupled to the one or more computer processors, specified modifications to the real asset”. Accordingly, the Examiner submits claims 1-21, recite an abstract idea based on the language identified in claims 1, 12, and 17, and the abstract ideas previously identified based on that language that remains consistent with the groupings of Step 2A Prong 1 of the MPEP 2106.04(a)(1).
If the claims are directed toward the judicial exception of an abstract idea, it must then be determined under Step 2A Prong 2 whether the judicial exception is integrated into a practical application. Examiner notes that considerations under Step 2A Prong 2 comprise most the consideration previously evaluated in the context of Step 2B. The Examiner submits that the considerations discussed previously determined that the claim does not recite “significantly more” at Step 2B would be evaluated the same under Step 2A Prong 1 and result in the determination that the claim does not integrate the abstract idea into a practical application.
The instant application fails to integrate the judicial exception into a practical application because the instant application merely recites words “apply it” (or an equivalent) with the judicial exception or merely includes instructions to implement an abstract idea. The instant application is directed to a method instructing the reader to implement the identified method of organizing human activity of business and legal interactions such as contractual agreements (i.e., property purchases and funding) on generically claimed computer structure. For instance, the additional elements or combination of elements other than the abstract idea itself include the elements such as “processor”, “memory”, “database”, “smart contract” recited at a high level of generality. These elements do not themselves amount to an improvement to the interface or computer, to a technology or another technical field. This is consistent with Applicant’s disclosure which states that the computing device is “processor 520 may fetch executable instructions from memory and proceed to execute the fetched instructions. Memory 522 may also comprise a memory controller for accessing device readable-medium 540 that may carry and/or make accessible digital content, which may include code, and/or instructions, for example, executable by processor 520 and/or some other device, such as a controller, as one example, capable of executing computer instructions, for example. Under direction of processor 520, a non-transitory memory, such as memory cells storing physical states (e.g., memory states), comprising, for example, a program of executable computer instructions, may be executed by processor 520 and able to generate signals to be communicated via a network, for example, as previously described. Generated signals may also be stored in memory, also previously suggested”. (App. Spec. 66).
Accordingly, the claimed “system” read in light of the specification employs any wide range of possible devices comprising a number of components that are “well-known” and included in an indiscriminate “processor”, “memory”, “database”, “smart contract” (e.g., processing device, modules). Thus, the claimed structure amounts to appending generic computer elements to abstract idea comprising the body of the claim. The computing elements are only involved at a general, high level, and do not have the particular role within any of the functions but to be an computer-implemented method using a generically claimed “processor” and “memory” and even basic, generic recitations that imply use of the computer such as storing information via servers would add little if anything to the abstract idea.
Similarly, reciting the abstract idea as software functions used to program a generic computer is not significant or meaningful: generic computers are programmed with software to perform various functions every day. A programmed generic computer is not a particular machine and by itself does not amount to an inventive concept because, as discussed in MPEP 2106.05(a), adding the words “apply it” (or an equivalent) with the judicial exception, or more instructions to implement an abstract idea on a computer, as discussed in Alice, 134 S. Ct. at 2360, 110 USPQ2d at 1984 (see MPEP § 2106.05(f)), is not enough to integrate the exception into a practical application. Further, it is not relevant that a human may perform a task differently from a computer. It is necessarily true that a human might apply an abstract idea in a different manner from a computer. What matters is the application, “stating an abstract idea while adding the words ‘apply it with a computer’” will not render an abstract idea non-abstract. Tranxition v. Lenovo, Nos. 2015-1907, -1941, -1958 (Fed. Cir. Nov. 16, 2016), slip op. at 7-8.
Here, the instructions entirely comprise the abstract idea, leaving little if any aspects of the claim for further consideration under Step 2A Prong 2. In short, the role of the generic computing elements recited in claims 1-21, is the same as the role of the computer in the claims considered by the Supreme Court in Alice, and the claim as whole amounts merely to an instruction to apply the abstract idea on the generic computerised system. Therefore, the claims have failed to integrate a practical application (2106.04(d)). Under the MPEP 2106.05, this supports the conclusion that the claim is directed to an abstract idea, and the analysis proceeds to Step 2B.
While many considerations in Step 2A need not be reevaluated in Step 2B because the outcome will be the same. Here, on the basis of the additional elements other than the abstract idea, considered individually and in combination as discussed above, the Examiner respectfully submits that the claims 1-21, does not contain any additional elements that individually or as an ordered combination amount to an inventive concept and the claims are ineligible.
With respect to the dependent claims do not recite anything that is found to render the abstract idea as being transformed into a patent eligible invention. The dependent claims are merely reciting further embellishments of the abstract idea and do not claim anything that amounts to significantly more than the abstract idea itself.
Claims 2-11, 13-16, and 18-21 are directed to further embellishments of the abstract idea in that they are directed to aspects of the domain registration process and ownership validation of domain names which is the central theme of the abstract idea identified above, as well as being directed to data processing and transmission which the courts have recognized as insignificant extra-solution activities (see at least M.P.E.P. 2106.05(g)). Data transmission is one of the most basic and fundamental uses there are for a generic computing device is not sufficient to amount to significantly more. The examiner takes the position that simply appending the judicial exception with such a well understood step of data transmission is not going to amount to significantly more than the abstract idea.
Therefore, since there are no limitations in the claim that transform the abstract idea into a patent eligible application such that the claim amounts to significantly more than the abstract idea itself, the claims are rejected under 35 U.S.C. § 101 as being directed to non-statutory subject matter. See MPEP 2106.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
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.
Claim(s) 1, 3-17, and 19-21 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent Application Publication No. 20230011777 to Brown et al. (hereinafter Brown) in view of U.S. Patent Application Publication No. 20210012443 to Davison in view of U.S. Patent Application Publication No. 20180053269 to Heatherly et al. (hereinafter Heatherly).
Referring to Claim 1, Brown teaches a method for customizing a real asset, Claim 12 recites a system, and Claim 17 reciting an article comprising: a non-transitory storage medium having computer-readable instructions encoded thereon, which, when executed by a processor coupled to a memory device (see at least Brown: ¶ 58-59, 84, 95, and 99), are operable to comprising:
one or more computer processors coupled to at least one memory device to form a group of digitized parameters to represent a real asset (see at least Brown: ¶ 60 “The database 400 can be a SQL database, NoSQL database, and/or any other suitable database. The database 400 can be queried to retrieve the measurements, condition scores, attributes, parcel data, auxiliary data, and/or any other suitable information used to perform the method. The query can include geographic coordinates, an address, and/or any other property identifier (e.g., used to identify a parcel and/or group of parcels)”; see also Brown: ¶ 29 “A measurement preferably records a parameter of a property (e.g., the property of interest), but can additionally or alternatively record a parameter the surrounding geographic region, adjacent properties, and/or other features. The parameter can be: the visual appearance (e.g., wherein the measurement depicts the property or surrounding geographic region), a geometry (e.g., depth), a chemical composition, audio, and/or any other parameter”; see also Brown: ¶ 30-31, 33-36, “Property attributes can include: structural attributes (e.g., for a primary structure, accessory structure, neighboring structure, etc.), location (e.g., parcel centroid, structure centroid, roof centroid, etc.), property type (e.g., single family, lease, vacant land, multifamily, duplex, etc.), property component parameters (e.g., area, enclosure, presence, structure type, count, material, construction type, area condition, spacing, etc.; for pools, porches, decks, patios, fencing, etc.), storage (e.g., presence of a garage, carport, etc.), permanent or semi-permanent improvements (e.g., solar panel presence, count, type, arrangement, and/or other solar panel parameters; HVAC presence, count, footprint, type, location, and/or other parameters; etc.), temporary improvement parameters (e.g., presence, area, location, etc. of trampolines, playsets, etc.), pavement parameters (e.g., paved area, percent illuminated, etc.), foundation elevation, terrain parameters (e.g., parcel slope, surrounding terrain information, etc.), and/or any other attribute that remains substantially static after built structure construction.”; see also Brown: ¶ 44, 50, 53, 72, and 122);
(claim 12) a graphical user interface, coupled to the one or more computer processors, to permit a user to specify one or more modifications to the real asset (see at least Brown: ¶ 28 “a property component or set or segment thereof, and/or otherwise defined. For example, the property can include both the underlying land and improvements (e.g., built structures, fixtures, etc.) affixed to the land, only include the underlying land, or only include a subset of the improvements (e.g., only the primary building). Property components can include: built structures (e.g., primary structure, accessory structure, deck, pool, etc.); subcomponents of the built structures (e.g., roof, siding, framing, flooring, living space, bedrooms, bathrooms, garages, foundation, HVAC systems, solar panels, slides, diving board, etc.); permanent improvements (e.g., pavement, statutes, fences, etc.); temporary improvements or objects”; see also Brown: ¶ 34-35 “Property attributes can include: structural attributes (e.g., for a primary structure, accessory structure, neighboring structure, etc.), location (e.g., parcel centroid, structure centroid, roof centroid, etc.), property type (e.g., single family, lease, vacant land, multifamily, duplex, etc.), property component parameters (e.g., area, enclosure, presence, structure type, count, material, construction type, area condition, spacing, etc.; for pools, porches, decks, patios, fencing, etc.), storage (e.g., presence of a garage, carport, etc.), permanent or semi-permanent improvements (e.g., solar panel presence, count, type, arrangement, and/or other solar panel parameters; HVAC presence, count, footprint, type, location, and/or other parameters; etc.), temporary improvement parameters”), wherein the at least one memory device is to store binary digits corresponding to (see at least Brown: ¶ 60 “The database 400 can be a SQL database, NoSQL database, and/or any other suitable database. The database 400 can be queried to retrieve the measurements, condition scores, attributes, parcel data, auxiliary data, and/or any other suitable information used to perform the method. The query can include geographic coordinates, an address, and/or any other property identifier (e.g., used to identify a parcel and/or group of parcels)”; see also Brown: ¶ 30 “The condition score can be discrete, continuous, binary, multiclass, numerical, categorical, and/or otherwise structured. The condition score can be a label, or not be a label. The condition score can be a multi-class label (e.g., severe, poor, fair, good, excellent, etc.), a binary label (e.g., good or poor corresponding to 1 or 0), a value (e.g., 0-5, 0-10, 0-100, etc.; an integer value, a decimal value, etc.), and/or any other suitable score.”; see also Brown: ¶ 38 “Attribute values can be discrete, continuous, binary, multiclass, and/or otherwise structured.”; see also Brown: ¶ 45, 51, 73, 77-79: binary use):
forming, via one or more computer processors coupled to at least one memory device, a group of digitized parameters representing the real asset (see at least Brown: ¶ 60 “The database 400 can be a SQL database, NoSQL database, and/or any other suitable database. The database 400 can be queried to retrieve the measurements, condition scores, attributes, parcel data, auxiliary data, and/or any other suitable information used to perform the method. The query can include geographic coordinates, an address, and/or any other property identifier (e.g., used to identify a parcel and/or group of parcels)”; see also Brown: ¶ 29 “A measurement preferably records a parameter of a property (e.g., the property of interest), but can additionally or alternatively record a parameter the surrounding geographic region, adjacent properties, and/or other features. The parameter can be: the visual appearance (e.g., wherein the measurement depicts the property or surrounding geographic region), a geometry (e.g., depth), a chemical composition, audio, and/or any other parameter”; see also Brown: ¶ 30-31, 33-36, “Property attributes can include: structural attributes (e.g., for a primary structure, accessory structure, neighboring structure, etc.), location (e.g., parcel centroid, structure centroid, roof centroid, etc.), property type (e.g., single family, lease, vacant land, multifamily, duplex, etc.), property component parameters (e.g., area, enclosure, presence, structure type, count, material, construction type, area condition, spacing, etc.; for pools, porches, decks, patios, fencing, etc.), storage (e.g., presence of a garage, carport, etc.), permanent or semi-permanent improvements (e.g., solar panel presence, count, type, arrangement, and/or other solar panel parameters; HVAC presence, count, footprint, type, location, and/or other parameters; etc.), temporary improvement parameters (e.g., presence, area, location, etc. of trampolines, playsets, etc.), pavement parameters (e.g., paved area, percent illuminated, etc.), foundation elevation, terrain parameters (e.g., parcel slope, surrounding terrain information, etc.), and/or any other attribute that remains substantially static after built structure construction.”; see also Brown: ¶ 44, 50, 53, 72, and 122; see also Brown: ¶ 30 “The condition score can be discrete, continuous, binary, multiclass, numerical, categorical, and/or otherwise structured. The condition score can be a label, or not be a label. The condition score can be a multi-class label (e.g., severe, poor, fair, good, excellent, etc.), a binary label (e.g., good or poor corresponding to 1 or 0), a value (e.g., 0-5, 0-10, 0-100, etc.; an integer value, a decimal value, etc.), and/or any other suitable score.”; see also Brown: ¶ 38 “Attribute values can be discrete, continuous, binary, multiclass, and/or otherwise structured.”; see also Brown: ¶ 45, 51, 73, 77-79: binary use);
receiving, via a graphical user interface coupled to the one or more computer processors, specified proposed modifications to the real asset (see at least Brown: ¶ 60 “The database 400 can be a SQL database, NoSQL database, and/or any other suitable database. The database 400 can be queried to retrieve the measurements, condition scores, attributes, parcel data, auxiliary data, and/or any other suitable information used to perform the method. The query can include geographic coordinates, an address, and/or any other property identifier (e.g., used to identify a parcel and/or group of parcels)”; see also Brown: ¶ 29 “A measurement preferably records a parameter of a property (e.g., the property of interest), but can additionally or alternatively record a parameter the surrounding geographic region, adjacent properties, and/or other features. The parameter can be: the visual appearance (e.g., wherein the measurement depicts the property or surrounding geographic region), a geometry (e.g., depth), a chemical composition, audio, and/or any other parameter”; see also Brown: ¶ 30-31, 33-36, “Property attributes can include: structural attributes (e.g., for a primary structure, accessory structure, neighboring structure, etc.), location (e.g., parcel centroid, structure centroid, roof centroid, etc.), property type (e.g., single family, lease, vacant land, multifamily, duplex, etc.), property component parameters (e.g., area, enclosure, presence, structure type, count, material, construction type, area condition, spacing, etc.; for pools, porches, decks, patios, fencing, etc.), storage (e.g., presence of a garage, carport, etc.), permanent or semi-permanent improvements (e.g., solar panel presence, count, type, arrangement, and/or other solar panel parameters; HVAC presence, count, footprint, type, location, and/or other parameters; etc.), temporary improvement parameters (e.g., presence, area, location, etc. of trampolines, playsets, etc.), pavement parameters (e.g., paved area, percent illuminated, etc.), foundation elevation, terrain parameters (e.g., parcel slope, surrounding terrain information, etc.), and/or any other attribute that remains substantially static after built structure construction.”; see also Brown: ¶ 44, 50, 53, 72, and 122; see also Brown: ¶ 30 “The condition score can be discrete, continuous, binary, multiclass, numerical, categorical, and/or otherwise structured. The condition score can be a label, or not be a label. The condition score can be a multi-class label (e.g., severe, poor, fair, good, excellent, etc.), a binary label (e.g., good or poor corresponding to 1 or 0), a value (e.g., 0-5, 0-10, 0-100, etc.; an integer value, a decimal value, etc.), and/or any other suitable score.”; see also Brown: ¶ 38 “Attribute values can be discrete, continuous, binary, multiclass, and/or otherwise structured.”; see also Brown: ¶ 45, 51, 73, 77-79: binary use);
Brown fails to state that the system receives a specified proposed modifications to a real asset.
However, Davison, which talks about a system and method for on-line management of real estate purchase, renovation and sale transactions via a blockchain, teaches it is known for the system to receive submitted offers and requests that have modifications (see at least Davison: ¶ 21 “lender accesses borrower financial position and payment history, property details and valuation, and project scope and ARV. At step 324, the lender records a loan offer, including draw schedule. At step 326, the borrower reviews the loan offer and accepts, declines, or requests modification.”; see also Davison: ¶ 21 “the borrower uploads financial documents required by lender (e.g., tax return, bank statements, existing loan docs). At step 312, the lender or third party(ies) verify and/or supplement borrower information and records results. At step 314, the borrower records property details and valuation. Optionally, as shown in step 316, the system calculates and records property valuation. At step 318, the borrower records project scope and draw schedule (either system default or proposed alternative)”).
Therefore, it would have been obvious to one of ordinary skill in the art at the time of filing to apply the known technique of on-line management of real estate purchase, renovation and sale transactions wherein financing is procured in consideration of future planned improvements (as disclosed by Davison) to the known method and system for managing real estate transactions wherein the system provides an estimate related to a property valuation which incorporates the estimate for repair or modification of a real property asset and an estimated cost (as disclosed by Brown) to manage information used to underwrite a loan for acquisition of real property and planned improvements (see at least Davison: ¶ 20). One of ordinary skill in the art would have been motivated to apply the known technique of on-line management of real estate purchase, renovation and sale transactions wherein financing is procured in consideration of future planned improvements because it would to reduce inspection fees and wait times ¶ 23; to track the flipping process end-to-end from initial purchase of the subject property through financing, renovation and sale to consumers ¶ 2; to allow renovators, lenders, vendors and inspectors to record aspects of the purchase, renovation and sale of the real estate in the blockchain (Abstract); and to manage information used to underwrite a loan for acquisition of real property and planned improvements (see at least Davison: ¶ 20)
Furthermore, it would have been obvious to one of ordinary skill in the art at the time of filing to apply the known technique of on-line management of real estate purchase, renovation and sale transactions wherein financing is procured in consideration of future planned improvements and project scopes (as disclosed by Davison) to the known method and system for managing real estate transactions wherein the system provides an estimate related to a property valuation which incorporates the estimate for repair or modification of a real property asset and an estimated cost (as disclosed by Brown) to manage information used to underwrite a loan for acquisition of real property and planned improvements (see at least Davison: ¶ 20), because the claimed invention is merely applying a known technique to a known method ready for improvement to yield predictable results. See KSR Int’l Co. v. Teleflex Inc., 550 U.S. 398, 406 (2007). In other words, all of the claimed elements were known in the prior art and one skilled in the art could have combined the elements as claimed by known methods with no change in their respective functions, and the combination would have yielded nothing more than predictable results to one of ordinary skill in the art at the time of the invention (i.e., predictable results are obtained by applying the known technique of on-line management of real estate purchase, renovation and sale transactions wherein financing is procured in consideration of future planned improvements to the known method and system for managing real estate transactions wherein the system provides an estimate related to a property valuation which incorporates the estimate for repair or modification of a real property asset and an estimated cost to reduce inspection fees and wait times ¶ 23; track the flipping process end-to-end from initial purchase of the subject property through financing, renovation and sale to consumers ¶ 2; and allow renovators, lenders, vendors and inspectors to record aspects of the purchase, renovation and sale of the real estate in the blockchain (see at least Davison: Abstract)). See also MPEP § 2143(I)(D).
The combination of Brown and Davison teaches:
storing, in the at least one memory device, binary digits corresponding to an as-is value of the real asset (see at least Brown: ¶ 92 “In a sixth variant, S300 can include using a condition scoring model that directly ingests the measurement depicting the property and outputs the condition score. The condition scoring model can optionally ingest a property description vector extracted from a property description (e.g., from a real estate listing service) using an NLP model, keywords identified in the property description (e.g., “turnkey”, “potential”, “as-is”), and/or other attributes extracted from the property description; example shown in FIG. 7 .”; see also Brown: ¶ 30 “The condition score can be discrete, continuous, binary, multiclass, numerical, categorical, and/or otherwise structured. The condition score can be a label, or not be a label. The condition score can be a multi-class label (e.g., severe, poor, fair, good, excellent, etc.), a binary label (e.g., good or poor corresponding to 1 or 0), a value (e.g., 0-5, 0-10, 0-100, etc.; an integer value, a decimal value, etc.), and/or any other suitable score.”; see also Brown: ¶ 38 “Attribute values can be discrete, continuous, binary, multiclass, and/or otherwise structured.”; see also Brown: ¶ 45, 51, 73, 77-79: binary use) binary digits (see also Brown: ¶ 30 “The condition score can be discrete, continuous, binary, multiclass, numerical, categorical, and/or otherwise structured. The condition score can be a label, or not be a label. The condition score can be a multi-class label (e.g., severe, poor, fair, good, excellent, etc.), a binary label (e.g., good or poor corresponding to 1 or 0), a value (e.g., 0-5, 0-10, 0-100, etc.; an integer value, a decimal value, etc.), and/or any other suitable score.”; see also Brown: ¶ 38 “Attribute values can be discrete, continuous, binary, multiclass, and/or otherwise structured.”; see also Brown: ¶ 45, 51, 73, 77-79: binary use) corresponding to an estimate of resources allocated to modify the real asset in accordance with the specified proposed modifications, and an estimated value of the real asset that is to include the specified proposed modifications (further addressed below);
Brown fails to explicitly state:
that the binary digits corresponding to an estimate of resources allocated to modify the real asset in accordance with the specified proposed modifications, and an estimated value of the real asset that is to include the specified proposed modifications
However, Davison, which talks about a method and system and method for on-line management of real estate purchase, renovation and sale transactions via a blockchain, teaches it is known to store and use corresponding information related to real estate properties such as an estimate of resources allocated to modify the real asset in accordance with the specified proposed modifications, and an estimated value of the real asset that is to include the specified proposed modifications (see at least Davison: ¶ 20 “The blockchain may be enabled to manage information used to underwrite a loan for acquisition of real property and planned improvement”; see at least Davison: ¶ 16 “FIG. 1 is a block diagram of exemplary stakeholders in a typical property flip process. The flipper 10 must obtain financing from a lender 20 for property purchase and/or rehab construction work on the subject property.”; see also Davison: ¶ 19 “The user, who may be the flipper, a lender or a third party consultant records the project scope in the system 210. The user, or the system determines as-repaired value (“ARV”) 212. This may be done automatically by the system based on publicly available market data”; see also Davison: ¶ 20-21 “The blockchain may be enabled to calculate the value of property prior to improvement and calculate an ARV based on factors including scope of work and comparable sales… the borrower records property details and valuation. Optionally, as shown in step 316, the system calculates and records property valuation. At step 318, the borrower records project scope and draw schedule (either system default or proposed alternative). Optionally, as shown at step 320, the system calculates and records after repair value (ARV). At step 322, the lender accesses borrower financial position and payment history, property details and valuation, and project scope and ARV.”).
Davison teaches it is known for the system to receive submitted offers and requests that have modifications (see at least Davison: ¶ 21 “lender accesses borrower financial position and payment history, property details and valuation, and project scope and ARV. At step 324, the lender records a loan offer, including draw schedule. At step 326, the borrower reviews the loan offer and accepts, declines, or requests modification.”; see also Davison: ¶ 21 “the borrower uploads financial documents required by lender (e.g., tax return, bank statements, existing loan docs). At step 312, the lender or third party(ies) verify and/or supplement borrower information and records results. At step 314, the borrower records property details and valuation. Optionally, as shown in step 316, the system calculates and records property valuation. At step 318, the borrower records project scope and draw schedule (either system default or proposed alternative)”).
Brown discloses a system which provides an estimate related to a property valuation which incorporates the estimate for repair or modification of a real property asset and an estimated cost (see at least Brown: ¶ 54 “The condition scoring module 200 can be specific to: a use case (e.g., real estate valuation, insurance loss estimation, maintenance/repair cost, etc.”; see also Brown: ¶ 47 “The attribute module 100 can be specific to: a use case (e.g., real estate valuation, insurance loss estimation, maintenance/repair cost, etc.), a measurement type (e.g., 2D measurement, 3D measurement, interior measurement, exterior measurement, etc.),”; see also Brown: ¶ 112 “the weights can be selected based on maintenance or repair cost per property component associated with the attribute.”; see also Brown: ¶ 125 “he condition score can be used with: personal and/or commercial lines insurance (e.g., rating, inspection optimization, etc.), real estate property investing (e.g., identify underpriced properties that can increase in value through renovation and/or repairs, incorporate condition score into a valuation model to establish the offer price, etc.”).
Therefore, it would have been obvious to one of ordinary skill in the art at the time of filing to apply the known technique of on-line management of real estate purchase, renovation and sale transactions wherein financing is procured in consideration of future planned improvements (as disclosed by Davison) to the known method and system for managing real estate transactions wherein the system provides an estimate related to a property valuation which incorporates the estimate for repair or modification of a real property asset and an estimated cost (as disclosed by Brown) to reduce inspection fees and wait times ¶ 23; track the flipping process end-to-end from initial purchase of the subject property through financing, renovation and sale to consumers ¶ 2; and allow renovators, lenders, vendors and inspectors to record aspects of the purchase, renovation and sale of the real estate in the blockchain (see at least Davison: Abstract). One of ordinary skill in the art would have been motivated to apply the known technique of on-line management of real estate purchase, renovation and sale transactions wherein financing is procured in consideration of future planned improvements because it would to reduce inspection fees and wait times ¶ 23; track the flipping process end-to-end from initial purchase of the subject property through financing, renovation and sale to consumers ¶ 2; and allow renovators, lenders, vendors and inspectors to record aspects of the purchase, renovation and sale of the real estate in the blockchain (see at least Davison: Abstract).
Furthermore, it would have been obvious to one of ordinary skill in the art at the time of filing to apply the known technique of on-line management of real estate purchase, renovation and sale transactions wherein financing is procured in consideration of future planned improvements (as disclosed by Davison) to the known method and system for managing real estate transactions wherein the system provides an estimate related to a property valuation which incorporates the estimate for repair or modification of a real property asset and an estimated cost (as disclosed by Brown) to reduce inspection fees and wait times ¶ 23; track the flipping process end-to-end from initial purchase of the subject property through financing, renovation and sale to consumers ¶ 2; and allow renovators, lenders, vendors and inspectors to record aspects of the purchase, renovation and sale of the real estate in the blockchain (see at least Davison: Abstract), because the claimed invention is merely applying a known technique to a known method ready for improvement to yield predictable results. See KSR Int’l Co. v. Teleflex Inc., 550 U.S. 398, 406 (2007). In other words, all of the claimed elements were known in the prior art and one skilled in the art could have combined the elements as claimed by known methods with no change in their respective functions, and the combination would have yielded nothing more than predictable results to one of ordinary skill in the art at the time of the invention (i.e., predictable results are obtained by applying the known technique of on-line management of real estate purchase, renovation and sale transactions wherein financing is procured in consideration of future planned improvements to the known method and system for managing real estate transactions wherein the system provides an estimate related to a property valuation which incorporates the estimate for repair or modification of a real property asset and an estimated cost to reduce inspection fees and wait times ¶ 23; track the flipping process end-to-end from initial purchase of the subject property through financing, renovation and sale to consumers ¶ 2; and allow renovators, lenders, vendors and inspectors to record aspects of the purchase, renovation and sale of the real estate in the blockchain (see at least Davison: Abstract)). See also MPEP § 2143(I)(D).
The combination of Brown and Davison teaches:
computing, based, at least in part, on the estimate of the resources via the one or more computer processors, an amount of a financial resource premium for a proposed agreement that permits a first entity to procure the real asset at the as-is value or a specified percentage thereof within a specified period of time and that directs that the financial resource premium be provided by the first entity for the purpose of implementing the specified proposed modifications (see at least Brown: ¶ 92 “In a sixth variant, S300 can include using a condition scoring model that directly ingests the measurement depicting the property and outputs the condition score. The condition scoring model can optionally ingest a property description vector extracted from a property description (e.g., from a real estate listing service) using an NLP model, keywords identified in the property description (e.g., “turnkey”, “potential”, “as-is”), and/or other attributes extracted from the property description; example shown in FIG. 7 .”; see also Brown: ¶ 30 “The condition score can be discrete, continuous, binary, multiclass, numerical, categorical, and/or otherwise structured. The condition score can be a label, or not be a label. The condition score can be a multi-class label (e.g., severe, poor, fair, good, excellent, etc.), a binary label (e.g., good or poor corresponding to 1 or 0), a value (e.g., 0-5, 0-10, 0-100, etc.; an integer value, a decimal value, etc.), and/or any other suitable score.”; see also Brown: ¶ 38 “Attribute values can be discrete, continuous, binary, multiclass, and/or otherwise structured.”; see also Brown: ¶ 45, 51, 73, 77-79: binary use) binary digits (see also Brown: ¶ 30 “The condition score can be discrete, continuous, binary, multiclass, numerical, categorical, and/or otherwise structured. The condition score can be a label, or not be a label. The condition score can be a multi-class label (e.g., severe, poor, fair, good, excellent, etc.), a binary label (e.g., good or poor corresponding to 1 or 0), a value (e.g., 0-5, 0-10, 0-100, etc.; an integer value, a decimal value, etc.), and/or any other suitable score.”; see also Brown: ¶ 38 “Attribute values can be discrete, continuous, binary, multiclass, and/or otherwise structured.”; see also Brown: ¶ 45, 51, 73, 77-79: binary use; see also Brown: ¶ 125 “The condition score can be used to determine: automated valuation model error, insurance loss ratio (e.g., insurance loss divided by premium), and/or any other value. The condition score can be used with: personal and/or commercial lines insurance (e.g., rating, inspection optimization, etc.), real estate property investing (e.g., identify underpriced properties that can increase in value through renovation and/or repairs, incorporate condition score into a valuation model to establish the offer price, etc.), real estate loan trading (e.g., use condition score to evaluate the quality of a loan pool and adjust bid price accordingly; use condition score to identify acute condition issues that can result in removal of a loan from the pool during due diligence; use condition score as an input into a model that predicts probability of default; etc.), real estate mortgage origination (e.g., GSEs can use the condition score to determine whether they will allow a property inspection waiver; originators of non-agency or agency loans can use the condition score as an input into their underwriting criteria; etc.), real estate valuations (e.g., use condition score as an input to an automated valuation model; use condition score as a supplement to a property-level valuation report; etc.), and/or otherwise used”; see also Brown: ¶ 126 “The property attributes and/or component values can be used to determine: automated valuation model error, automated valuation model accuracy, automated property valuation or price, and/or any other suitable value. The AVM can be: retrieved from a database, determined dynamically, and/or otherwise determined”; see also Brown: ¶ 130 “the attributes can describe property components (e.g., age of vegetation, age of roof of built structure, age of paved surface, price to replace roof, price to replace surface, etc.)”; see at least Brown: ¶ 54 “The condition scoring module 200 can be specific to: a use case (e.g., real estate valuation, insurance loss estimation, maintenance/repair cost, etc.”; see also Brown: ¶ 47 “The attribute module 100 can be specific to: a use case (e.g., real estate valuation, insurance loss estimation, maintenance/repair cost, etc.), a measurement type (e.g., 2D measurement, 3D measurement, interior measurement, exterior measurement, etc.),”; see also Brown: ¶ 112 “the weights can be selected based on maintenance or repair cost per property component associated with the attribute.”; see also Brown: ¶ 125 “he condition score can be used with: personal and/or commercial lines insurance (e.g., rating, inspection optimization, etc.), real estate property investing (e.g., identify underpriced properties that can increase in value through renovation and/or repairs, incorporate condition score into a valuation model to establish the offer price, etc.”).
Examiner notes that the combination of Brown and Davison fails to state between a current owner of the real asset and a first entity;
However, Heatherly, which talks about a method and system for connecting users of a real-estate transaction management platform, teaches that it is known to manage and provide systems to facilitate and manage real estate property transactions between current owners and buyers (see at least Heatherly: ¶ 26 “The real-estate agent/broker in the context of this disclosure may include anyone who furnishes the buyer with the opportunity to purchase/rent the real-estate property. Examples of the real-estate agent/broker may include a current owner of the real-estate property, a representative or agent of the real-estate property”).
Brown discloses the system and method “method can optionally include determining a property analysis based on the condition score and/or a timeseries thereof. Examples of property analyses include: the attribute values, real estate valuations (e.g., estimated based on the condition score and/or one or more attribute values), purchase and/or sale analyses, loan buying and/or selling analyses, timeseries analyses (e.g., property change over time, property change detection, etc.), insurance estimates, claim severity estimates, claim frequency estimates, whether inspectors should be deployed, overall condition estimates, and/or any other suitable property analysis.” (see at least Brown: ¶ 121).
Davison teaches system and method for on-line management of real estate purchase, renovation and sale transactions via a blockchain (see at least Davison: Abstract).
The combination just does not explicitly state that the system is managing a transaction between a current owner and the buyer.
Therefore, it would have been obvious to one of ordinary skill in the art at the time of filing to apply the known technique of facilitating and manage real estate property transactions between current owners and buyers (as disclosed by Heatherly) to the known system and method for on-line management of real estate purchase, renovation and sale transactions (as disclosed by the combination of Brown and Davison) to connect the buyers/real-estate agents/money lenders in a novel and efficient manner, provide an organized chain of professional brokers and lenders, where the potential buyers can select the best deal as per their requirements. One of ordinary skill in the art would have been motivated to apply the known technique of facilitating and manage real estate property transactions between current owners and buyers because it would connect the buyers/real-estate agents/money lenders in a novel and efficient manner, provide an organized chain of professional brokers and lenders, where the potential buyers can select the best deal as per their requirements (see Heatherly ¶ 6).
Furthermore, it would have been obvious to one of ordinary skill in the art at the time of filing to apply the known technique of facilitating and manage real estate property transactions between current owners and buyers (as disclosed by Heatherly) to the known system and method for on-line management of real estate purchase, renovation and sale transactions (as disclosed by the combination of Brown and Davison) to connect the buyers/real-estate agents/money lenders in a novel and efficient manner, provide an organized chain of professional brokers and lenders, where the potential buyers can select the best deal as per their requirements, because the claimed invention is merely applying a known technique to a known method ready for improvement to yield predictable results. See KSR Int’l Co. v. Teleflex Inc., 550 U.S. 398, 406 (2007). In other words, all of the claimed elements were known in the prior art and one skilled in the art could have combined the elements as claimed by known methods with no change in their respective functions, and the combination would have yielded nothing more than predictable results to one of ordinary skill in the art at the time of the invention (i.e., predictable results are obtained by applying the known technique of facilitating and manage real estate property transactions between current owners and buyers to the known system and method for on-line management of real estate purchase, renovation and sale transactions to connect the buyers/real-estate agents/money lenders in a novel and efficient manner, provide an organized chain of professional brokers and lenders, where the potential buyers can select the best deal as per their requirements). See also MPEP § 2143(I)(D).
The combination of Brown, Davison, and Heatherly teaches:
forming a record of materials and/or material specifications based, at least in part, on the specified proposed modifications to the real asset (see at least Brown: ¶ 60 “The database 400 can be a SQL database, NoSQL database, and/or any other suitable database. The database 400 can be queried to retrieve the measurements, condition scores, attributes, parcel data, auxiliary data, and/or any other suitable information used to perform the method. The query can include geographic coordinates, an address, and/or any other property identifier (e.g., used to identify a parcel and/or group of parcels”; see also Brown: ¶ 54 “The condition scoring module 200 can be specific to: a use case (e.g., real estate valuation, insurance loss estimation, maintenance/repair cost, etc.”; see also Brown: ¶ 47 “The attribute module 100 can be specific to: a use case (e.g., real estate valuation, insurance loss estimation, maintenance/repair cost, etc.), a measurement type (e.g., 2D measurement, 3D measurement, interior measurement, exterior measurement, etc.),”; see also Brown: ¶ 112 “the weights can be selected based on maintenance or repair cost per property component associated with the attribute.”; see also Brown: ¶ 125 “he condition score can be used with: personal and/or commercial lines insurance (e.g., rating, inspection optimization, etc.), real estate property investing (e.g., identify underpriced properties that can increase in value through renovation and/or repairs, incorporate condition score into a valuation model to establish the offer price, etc.”; see also Brown: ¶ 33-36 and 77-78: discussing the system storing a record of materials based on the specified modification to the real asset… “property component parameters (e.g., area, enclosure, presence, structure type, count, material, construction type, area condition, spacing, etc.” and “Attributes associated with a property component can include: location (e.g., centroid location), boundary, distance (e.g., to another property component, to a geographic landmark, to wildland, setback distance, etc.), material, type, presence, count, density, geometry parameters (e.g., footprint and/or area, area ratios and/or percentages, complexity, number of facets and/or other elements, slope, height, etc.), condition (e.g., a condition rating), hazard context, geographic context, vegetation context (e.g., based on an area larger than the property), weather context, terrain context, historical construction information, ratios or comparisons therebetween, counts, and/or any other parameter associated with one or more property components…Structural attributes can include: the structure footprint, structure density, count, structure class/type, proximity information and/or setback distance (e.g., relative to a primary structure, relative to another property component, etc.), building height, parcel area, number of bedrooms, number of bathrooms, number of stories, roof parameters (e.g., area, area relative to structure area, geometry/shape, slope, complexity, number of facets, height, material, roof extension, solar panel presence, solar panel area, etc.), framing parameters (e.g., material), flooring (e.g., floor type), historical construction information (e.g., year built, year updated/improved/expanded, etc.), area of living space, ratios or comparisons therebetween, and/or other attribute descriptive of the physical property construction”; see also Davison: ¶ 20 “The blockchain may be enabled to record proof of delivery of material, labor, or other services that improve a property and to record payments for delivery of material, labor, or other services. Proof may include digital scans or photos of delivery documentation, digital recording of acceptance of delivery, or photo or video documentation with embedded location information. The blockchain may be enabled to manage a network of verifiers who review documentation related to delivery of material, labor, or other services that improve a property and to record results for use in authorizing payment. The blockchain system maintains information about verifiers, including performance reviews, for use in manual or automated routing of requests for verification. The blockchain system manages payment of verifiers. The blockchain may be enabled to record evidence of improvements on a property, including photo and video documentation of in progress and completed work. The blockchain system also provides evidence of vendor payment for improvements. The blockchain system also records any applicable warranties for material, labor, or other services that improve a property.”).
Referring to Claim 2, the combination of Brown, Davison, and Heatherly teaches the method of claim 1including computing a fraction of the amount of the financial resource premium provided to the first entity responsive to a second entity procuring the real asset (see at least Davison: ¶ 20 “The blockchain may be enabled to manage information used to underwrite a loan for acquisition of real property and planned improvements. The blockchain may be enabled in a draw schedule for funds disbursement as milestones are achieved, record funds transfers based on achievement of milestones, with optional transfers directly from lender to vendors, record payments made by the borrower, and record the loan payoff”; see also Davison: ¶ 21 “the borrower records project scope and draw schedule (either system default or proposed alternative). Optionally, as shown at step 320, the system calculates and records after repair value (ARV). At step 322, the lender accesses borrower financial position and payment history, property details and valuation, and project scope and ARV. At step 324, the lender records a loan offer, including draw schedule.”; see also Davison: ¶ 22 “At step 426, if draw requirements are met, the system initiates (or executes) and records payment from lender to borrower (or vendor(s), if specified) for draw amount.”; see also Davison: ¶ 25 “the system pays the vendor based on payment terms. At step 626, when a vendor is associated with a draw in a draw schedule and the draw is approved, system initiates (or executes) and records a transfer directly from the lender to the vendor.”).
Therefore, it would have been obvious to one of ordinary skill in the art at the time of filing to apply the known technique of on-line management of real estate purchase, renovation and sale transactions wherein financing is procured in consideration of future planned improvements (as disclosed by Davison) to the known method and system for managing real estate transactions wherein the system provides an estimate related to a property valuation which incorporates the estimate for repair or modification of a real property asset and an estimated cost (as disclosed by Brown) to reduce inspection fees and wait times ¶ 23; track the flipping process end-to-end from initial purchase of the subject property through financing, renovation and sale to consumers ¶ 2; and allow renovators, lenders, vendors and inspectors to record aspects of the purchase, renovation and sale of the real estate in the blockchain (see at least Davison: Abstract). One of ordinary skill in the art would have been motivated to apply the known technique of on-line management of real estate purchase, renovation and sale transactions wherein financing is procured in consideration of future planned improvements because it would to reduce inspection fees and wait times ¶ 23; track the flipping process end-to-end from initial purchase of the subject property through financing, renovation and sale to consumers ¶ 2; and allow renovators, lenders, vendors and inspectors to record aspects of the purchase, renovation and sale of the real estate in the blockchain (see at least Davison: Abstract).
Referring to Claim 3, the combination of Brown, Davison, and Heatherly teaches the method of claim 1, wherein the group of digitized parameters representing the real asset correspond to construction parameters of the real asset (see at least Brown: ¶ 92 “In a sixth variant, S300 can include using a condition scoring model that directly ingests the measurement depicting the property and outputs the condition score. The condition scoring model can optionally ingest a property description vector extracted from a property description (e.g., from a real estate listing service) using an NLP model, keywords identified in the property description (e.g., “turnkey”, “potential”, “as-is”), and/or other attributes extracted from the property description; example shown in FIG. 7 .”; see also Brown: ¶ 30 “The condition score can be discrete, continuous, binary, multiclass, numerical, categorical, and/or otherwise structured. The condition score can be a label, or not be a label. The condition score can be a multi-class label (e.g., severe, poor, fair, good, excellent, etc.), a binary label (e.g., good or poor corresponding to 1 or 0), a value (e.g., 0-5, 0-10, 0-100, etc.; an integer value, a decimal value, etc.), and/or any other suitable score.”; see also Brown: ¶ 38 “Attribute values can be discrete, continuous, binary, multiclass, and/or otherwise structured.”; see also Brown: ¶ 45, 51, 73, 77-79: binary use) binary digits (see also Brown: ¶ 30 “The condition score can be discrete, continuous, binary, multiclass, numerical, categorical, and/or otherwise structured. The condition score can be a label, or not be a label. The condition score can be a multi-class label (e.g., severe, poor, fair, good, excellent, etc.), a binary label (e.g., good or poor corresponding to 1 or 0), a value (e.g., 0-5, 0-10, 0-100, etc.; an integer value, a decimal value, etc.), and/or any other suitable score.”; see also Brown: ¶ 38 “Attribute values can be discrete, continuous, binary, multiclass, and/or otherwise structured.”; see also Brown: ¶ 45, 51, 73, 77-79: binary use; see also Brown: ¶ 125 “The condition score can be used to determine: automated valuation model error, insurance loss ratio (e.g., insurance loss divided by premium), and/or any other value. The condition score can be used with: personal and/or commercial lines insurance (e.g., rating, inspection optimization, etc.), real estate property investing (e.g., identify underpriced properties that can increase in value through renovation and/or repairs, incorporate condition score into a valuation model to establish the offer price, etc.), real estate loan trading (e.g., use condition score to evaluate the quality of a loan pool and adjust bid price accordingly; use condition score to identify acute condition issues that can result in removal of a loan from the pool during due diligence; use condition score as an input into a model that predicts probability of default; etc.), real estate mortgage origination (e.g., GSEs can use the condition score to determine whether they will allow a property inspection waiver; originators of non-agency or agency loans can use the condition score as an input into their underwriting criteria; etc.), real estate valuations (e.g., use condition score as an input to an automated valuation model; use condition score as a supplement to a property-level valuation report; etc.), and/or otherwise used”; see also Brown: ¶ 126 “The property attributes and/or component values can be used to determine: automated valuation model error, automated valuation model accuracy, automated property valuation or price, and/or any other suitable value. The AVM can be: retrieved from a database, determined dynamically, and/or otherwise determined”; see also Brown: ¶ 130 “the attributes can describe property components (e.g., age of vegetation, age of roof of built structure, age of paved surface, price to replace roof, price to replace surface, etc.)”).
Referring to Claim 4, the combination of Brown, Davison, and Heatherly teaches the method of claim 3, wherein the construction parameters of the real asset correspond to at least one of: a floor plan, a type of flooring in one or more sections of the real asset, a roof type, cabinetry parameters, installed appliance parameters, countertop parameters, outside landscaping parameters, kitchen fixture parameters, bathroom fixture parameters, interior wall coloring, and exterior coloring (see at least Brown: ¶ 92 “In a sixth variant, S300 can include using a condition scoring model that directly ingests the measurement depicting the property and outputs the condition score. The condition scoring model can optionally ingest a property description vector extracted from a property description (e.g., from a real estate listing service) using an NLP model, keywords identified in the property description (e.g., “turnkey”, “potential”, “as-is”), and/or other attributes extracted from the property description; example shown in FIG. 7 .”; see also Brown: ¶ 30 “The condition score can be discrete, continuous, binary, multiclass, numerical, categorical, and/or otherwise structured. The condition score can be a label, or not be a label. The condition score can be a multi-class label (e.g., severe, poor, fair, good, excellent, etc.), a binary label (e.g., good or poor corresponding to 1 or 0), a value (e.g., 0-5, 0-10, 0-100, etc.; an integer value, a decimal value, etc.), and/or any other suitable score.”; see also Brown: ¶ 38 “Attribute values can be discrete, continuous, binary, multiclass, and/or otherwise structured.”; see also Brown: ¶ 45, 51, 73, 77-79: binary use) binary digits (see also Brown: ¶ 30 “The condition score can be discrete, continuous, binary, multiclass, numerical, categorical, and/or otherwise structured. The condition score can be a label, or not be a label. The condition score can be a multi-class label (e.g., severe, poor, fair, good, excellent, etc.), a binary label (e.g., good or poor corresponding to 1 or 0), a value (e.g., 0-5, 0-10, 0-100, etc.; an integer value, a decimal value, etc.), and/or any other suitable score.”; see also Brown: ¶ 38 “Attribute values can be discrete, continuous, binary, multiclass, and/or otherwise structured.”; see also Brown: ¶ 45, 51, 73, 77-79: binary use; see also Brown: ¶ 125 “The condition score can be used to determine: automated valuation model error, insurance loss ratio (e.g., insurance loss divided by premium), and/or any other value. The condition score can be used with: personal and/or commercial lines insurance (e.g., rating, inspection optimization, etc.), real estate property investing (e.g., identify underpriced properties that can increase in value through renovation and/or repairs, incorporate condition score into a valuation model to establish the offer price, etc.), real estate loan trading (e.g., use condition score to evaluate the quality of a loan pool and adjust bid price accordingly; use condition score to identify acute condition issues that can result in removal of a loan from the pool during due diligence; use condition score as an input into a model that predicts probability of default; etc.), real estate mortgage origination (e.g., GSEs can use the condition score to determine whether they will allow a property inspection waiver; originators of non-agency or agency loans can use the condition score as an input into their underwriting criteria; etc.), real estate valuations (e.g., use condition score as an input to an automated valuation model; use condition score as a supplement to a property-level valuation report; etc.), and/or otherwise used”; see also Brown: ¶ 126 “The property attributes and/or component values can be used to determine: automated valuation model error, automated valuation model accuracy, automated property valuation or price, and/or any other suitable value. The AVM can be: retrieved from a database, determined dynamically, and/or otherwise determined”; see also Brown: ¶ 130 “the attributes can describe property components (e.g., age of vegetation, age of roof of built structure, age of paved surface, price to replace roof, price to replace surface, etc.)”).
Referring to Claim 5, the combination of Brown, Davison, and Heatherly teaches the method of claim 1, wherein the real asset corresponds to a real estate asset (see at least Brown: ¶ 92 “In a sixth variant, S300 can include using a condition scoring model that directly ingests the measurement depicting the property and outputs the condition score. The condition scoring model can optionally ingest a property description vector extracted from a property description (e.g., from a real estate listing service) using an NLP model, keywords identified in the property description (e.g., “turnkey”, “potential”, “as-is”), and/or other attributes extracted from the property description; example shown in FIG. 7 .”; see also Brown: ¶ 30 “The condition score can be discrete, continuous, binary, multiclass, numerical, categorical, and/or otherwise structured. The condition score can be a label, or not be a label. The condition score can be a multi-class label (e.g., severe, poor, fair, good, excellent, etc.), a binary label (e.g., good or poor corresponding to 1 or 0), a value (e.g., 0-5, 0-10, 0-100, etc.; an integer value, a decimal value, etc.), and/or any other suitable score.”; see also Brown: ¶ 38 “Attribute values can be discrete, continuous, binary, multiclass, and/or otherwise structured.”; see also Brown: ¶ 45, 51, 73, 77-79: binary use) binary digits (see also Brown: ¶ 30 “The condition score can be discrete, continuous, binary, multiclass, numerical, categorical, and/or otherwise structured. The condition score can be a label, or not be a label. The condition score can be a multi-class label (e.g., severe, poor, fair, good, excellent, etc.), a binary label (e.g., good or poor corresponding to 1 or 0), a value (e.g., 0-5, 0-10, 0-100, etc.; an integer value, a decimal value, etc.), and/or any other suitable score.”; see also Brown: ¶ 38 “Attribute values can be discrete, continuous, binary, multiclass, and/or otherwise structured.”; see also Brown: ¶ 45, 51, 73, 77-79: binary use; see also Brown: ¶ 125 “The condition score can be used to determine: automated valuation model error, insurance loss ratio (e.g., insurance loss divided by premium), and/or any other value. The condition score can be used with: personal and/or commercial lines insurance (e.g., rating, inspection optimization, etc.), real estate property investing (e.g., identify underpriced properties that can increase in value through renovation and/or repairs, incorporate condition score into a valuation model to establish the offer price, etc.), real estate loan trading (e.g., use condition score to evaluate the quality of a loan pool and adjust bid price accordingly; use condition score to identify acute condition issues that can result in removal of a loan from the pool during due diligence; use condition score as an input into a model that predicts probability of default; etc.), real estate mortgage origination (e.g., GSEs can use the condition score to determine whether they will allow a property inspection waiver; originators of non-agency or agency loans can use the condition score as an input into their underwriting criteria; etc.), real estate valuations (e.g., use condition score as an input to an automated valuation model; use condition score as a supplement to a property-level valuation report; etc.), and/or otherwise used”; see also Brown: ¶ 126 “The property attributes and/or component values can be used to determine: automated valuation model error, automated valuation model accuracy, automated property valuation or price, and/or any other suitable value. The AVM can be: retrieved from a database, determined dynamically, and/or otherwise determined”; see also Brown: ¶ 130 “the attributes can describe property components (e.g., age of vegetation, age of roof of built structure, age of paved surface, price to replace roof, price to replace surface, etc.)”).
Referring to Claim 6, the combination of Brown, Davison, and Heatherly teaches the method of claim 1, wherein the digitized parameters correspond to one or more computer-aided design files (see at least Brown: ¶ 29 “the visual appearance (e.g., wherein the measurement depicts the property or surrounding geographic region), a geometry (e.g., depth), a chemical composition, audio, and/or any other parameter. The measurement can be: 2D, 3D or geometric, and/or have any other set of dimensions. Examples of measurements can include: images (e.g., 2D images, 3D images, etc.), surface models (e.g., digital surface models (DSM), digital elevation models (DEM), digital terrain models (DTM), etc.), point clouds (e.g., generated from LIDAR, RADAR, stereoscopic imagery, etc.), depth maps, depth images, virtual models (e.g., geometric models, mesh models), audio, video, and/or any other suitable measurement”; see also Brown: ¶ 47 “a measurement type (e.g., 2D measurement, 3D measurement, interior measurement, exterior measurement, etc.)”; see also Brown: ¶ 54 and 66; see also Davison: ¶ 33).
Referring to Claim 7, the combination of Brown, Davison, and Heatherly teaches the method of claim 1, further comprising: transmitting the record of materials and/or material specifications to a contracting entity to modify the real asset in accordance with the specified modifications (see at least Brown: ¶ 60 “The database 400 can be a SQL database, NoSQL database, and/or any other suitable database. The database 400 can be queried to retrieve the measurements, condition scores, attributes, parcel data, auxiliary data, and/or any other suitable information used to perform the method. The query can include geographic coordinates, an address, and/or any other property identifier (e.g., used to identify a parcel and/or group of parcels”; see also Brown: ¶ 54 “The condition scoring module 200 can be specific to: a use case (e.g., real estate valuation, insurance loss estimation, maintenance/repair cost, etc.”; see also Brown: ¶ 47 “The attribute module 100 can be specific to: a use case (e.g., real estate valuation, insurance loss estimation, maintenance/repair cost, etc.), a measurement type (e.g., 2D measurement, 3D measurement, interior measurement, exterior measurement, etc.),”; see also Brown: ¶ 112 “the weights can be selected based on maintenance or repair cost per property component associated with the attribute.”; see also Brown: ¶ 125 “he condition score can be used with: personal and/or commercial lines insurance (e.g., rating, inspection optimization, etc.), real estate property investing (e.g., identify underpriced properties that can increase in value through renovation and/or repairs, incorporate condition score into a valuation model to establish the offer price, etc.”; see also Brown: ¶ 33-36 and 77-78: discussing the system storing a record of materials based on the specified modification to the real asset… “property component parameters (e.g., area, enclosure, presence, structure type, count, material, construction type, area condition, spacing, etc.” and “Attributes associated with a property component can include: location (e.g., centroid location), boundary, distance (e.g., to another property component, to a geographic landmark, to wildland, setback distance, etc.), material, type, presence, count, density, geometry parameters (e.g., footprint and/or area, area ratios and/or percentages, complexity, number of facets and/or other elements, slope, height, etc.), condition (e.g., a condition rating), hazard context, geographic context, vegetation context (e.g., based on an area larger than the property), weather context, terrain context, historical construction information, ratios or comparisons therebetween, counts, and/or any other parameter associated with one or more property components…Structural attributes can include: the structure footprint, structure density, count, structure class/type, proximity information and/or setback distance (e.g., relative to a primary structure, relative to another property component, etc.), building height, parcel area, number of bedrooms, number of bathrooms, number of stories, roof parameters (e.g., area, area relative to structure area, geometry/shape, slope, complexity, number of facets, height, material, roof extension, solar panel presence, solar panel area, etc.), framing parameters (e.g., material), flooring (e.g., floor type), historical construction information (e.g., year built, year updated/improved/expanded, etc.), area of living space, ratios or comparisons therebetween, and/or other attribute descriptive of the physical property construction”; see also Davison: ¶ 20 “The blockchain may be enabled to record proof of delivery of material, labor, or other services that improve a property and to record payments for delivery of material, labor, or other services. Proof may include digital scans or photos of delivery documentation, digital recording of acceptance of delivery, or photo or video documentation with embedded location information. The blockchain may be enabled to manage a network of verifiers who review documentation related to delivery of material, labor, or other services that improve a property and to record results for use in authorizing payment. The blockchain system maintains information about verifiers, including performance reviews, for use in manual or automated routing of requests for verification. The blockchain system manages payment of verifiers. The blockchain may be enabled to record evidence of improvements on a property, including photo and video documentation of in progress and completed work. The blockchain system also provides evidence of vendor payment for improvements. The blockchain system also records any applicable warranties for material, labor, or other services that improve a property.”; see at least Davison: ¶ 20 “The blockchain may be enabled to manage information used to underwrite a loan for acquisition of real property and planned improvement”; see at least Davison: ¶ 16 “FIG. 1 is a block diagram of exemplary stakeholders in a typical property flip process. The flipper 10 must obtain financing from a lender 20 for property purchase and/or rehab construction work on the subject property.”; see also Davison: ¶ 19 “The user, who may be the flipper, a lender or a third party consultant records the project scope in the system 210. The user, or the system determines as-repaired value (“ARV”) 212. This may be done automatically by the system based on publicly available market data”; see also Davison: ¶ 20-21 “The blockchain may be enabled to calculate the value of property prior to improvement and calculate an ARV based on factors including scope of work and comparable sales… the borrower records property details and valuation. Optionally, as shown in step 316, the system calculates and records property valuation. At step 318, the borrower records project scope and draw schedule (either system default or proposed alternative). Optionally, as shown at step 320, the system calculates and records after repair value (ARV). At step 322, the lender accesses borrower financial position and payment history, property details and valuation, and project scope and ARV.”; see at least Brown: ¶ 54 “The condition scoring module 200 can be specific to: a use case (e.g., real estate valuation, insurance loss estimation, maintenance/repair cost, etc.”; see also Brown: ¶ 47 “The attribute module 100 can be specific to: a use case (e.g., real estate valuation, insurance loss estimation, maintenance/repair cost, etc.), a measurement type (e.g., 2D measurement, 3D measurement, interior measurement, exterior measurement, etc.),”; see also Brown: ¶ 112 “the weights can be selected based on maintenance or repair cost per property component associated with the attribute.”; see also Brown: ¶ 125 “he condition score can be used with: personal and/or commercial lines insurance (e.g., rating, inspection optimization, etc.), real estate property investing (e.g., identify underpriced properties that can increase in value through renovation and/or repairs, incorporate condition score into a valuation model to establish the offer price, etc.”).
Referring to Claim 8, the combination of Brown, Davison, and Heatherly teaches the method of claim 1, wherein computing, based, at least in part, on the estimate of the resources further comprises: initiating a smart contract for an amount based, at least in part, on the amount of the financial resource premium amount (see at least Davison: ¶ 33).
Therefore, it would have been obvious to one of ordinary skill in the art at the time of filing to apply the known technique of on-line management of real estate purchase, renovation and sale transactions wherein financing is procured in consideration of future planned improvements (as disclosed by Davison) to the known method and system for managing real estate transactions wherein the system provides an estimate related to a property valuation which incorporates the estimate for repair or modification of a real property asset and an estimated cost (as disclosed by Brown) to reduce inspection fees and wait times ¶ 23; track the flipping process end-to-end from initial purchase of the subject property through financing, renovation and sale to consumers ¶ 2; and allow renovators, lenders, vendors and inspectors to record aspects of the purchase, renovation and sale of the real estate in the blockchain (see at least Davison: Abstract). One of ordinary skill in the art would have been motivated to apply the known technique of on-line management of real estate purchase, renovation and sale transactions wherein financing is procured in consideration of future planned improvements because it would to reduce inspection fees and wait times ¶ 23; track the flipping process end-to-end from initial purchase of the subject property through financing, renovation and sale to consumers ¶ 2; and allow renovators, lenders, vendors and inspectors to record aspects of the purchase, renovation and sale of the real estate in the blockchain (see at least Davison: Abstract).
Referring to Claim 9, the combination of Brown, Davison, and Heatherly teaches the method of claim 8, wherein the amount of the smart contract corresponds to the financial resource premium amount (see at least Davison: ¶ 33).
Therefore, it would have been obvious to one of ordinary skill in the art at the time of filing to apply the known technique of on-line management of real estate purchase, renovation and sale transactions wherein financing is procured in consideration of future planned improvements (as disclosed by Davison) to the known method and system for managing real estate transactions wherein the system provides an estimate related to a property valuation which incorporates the estimate for repair or modification of a real property asset and an estimated cost (as disclosed by Brown) to reduce inspection fees and wait times ¶ 23; track the flipping process end-to-end from initial purchase of the subject property through financing, renovation and sale to consumers ¶ 2; and allow renovators, lenders, vendors and inspectors to record aspects of the purchase, renovation and sale of the real estate in the blockchain (see at least Davison: Abstract). One of ordinary skill in the art would have been motivated to apply the known technique of on-line management of real estate purchase, renovation and sale transactions wherein financing is procured in consideration of future planned improvements because it would to reduce inspection fees and wait times ¶ 23; track the flipping process end-to-end from initial purchase of the subject property through financing, renovation and sale to consumers ¶ 2; and allow renovators, lenders, vendors and inspectors to record aspects of the purchase, renovation and sale of the real estate in the blockchain (see at least Davison: Abstract).
Referring to Claim 10, the combination of Brown, Davison, and Heatherly teaches the method of claim 1, wherein the graphical user interface coupled to the one or more computer processors comprises: an application program interface operating on a mobile communications device (see at least Brown: ¶ 58-59, 84, 95, and 99).
Referring to Claim 11, the combination of Brown, Davison, and Heatherly teaches the method of claim 1, wherein the first entity corresponds to a real asset flipper (see at least Brown: ¶ 60 “The database 400 can be a SQL database, NoSQL database, and/or any other suitable database. The database 400 can be queried to retrieve the measurements, condition scores, attributes, parcel data, auxiliary data, and/or any other suitable information used to perform the method. The query can include geographic coordinates, an address, and/or any other property identifier (e.g., used to identify a parcel and/or group of parcels”; see also Brown: ¶ 54 “The condition scoring module 200 can be specific to: a use case (e.g., real estate valuation, insurance loss estimation, maintenance/repair cost, etc.”; see also Brown: ¶ 47 “The attribute module 100 can be specific to: a use case (e.g., real estate valuation, insurance loss estimation, maintenance/repair cost, etc.), a measurement type (e.g., 2D measurement, 3D measurement, interior measurement, exterior measurement, etc.),”; see also Brown: ¶ 112 “the weights can be selected based on maintenance or repair cost per property component associated with the attribute.”; see also Brown: ¶ 125 “he condition score can be used with: personal and/or commercial lines insurance (e.g., rating, inspection optimization, etc.), real estate property investing (e.g., identify underpriced properties that can increase in value through renovation and/or repairs, incorporate condition score into a valuation model to establish the offer price, etc.”; see also Brown: ¶ 33-36 and 77-78: discussing the system storing a record of materials based on the specified modification to the real asset… “property component parameters (e.g., area, enclosure, presence, structure type, count, material, construction type, area condition, spacing, etc.” and “Attributes associated with a property component can include: location (e.g., centroid location), boundary, distance (e.g., to another property component, to a geographic landmark, to wildland, setback distance, etc.), material, type, presence, count, density, geometry parameters (e.g., footprint and/or area, area ratios and/or percentages, complexity, number of facets and/or other elements, slope, height, etc.), condition (e.g., a condition rating), hazard context, geographic context, vegetation context (e.g., based on an area larger than the property), weather context, terrain context, historical construction information, ratios or comparisons therebetween, counts, and/or any other parameter associated with one or more property components…Structural attributes can include: the structure footprint, structure density, count, structure class/type, proximity information and/or setback distance (e.g., relative to a primary structure, relative to another property component, etc.), building height, parcel area, number of bedrooms, number of bathrooms, number of stories, roof parameters (e.g., area, area relative to structure area, geometry/shape, slope, complexity, number of facets, height, material, roof extension, solar panel presence, solar panel area, etc.), framing parameters (e.g., material), flooring (e.g., floor type), historical construction information (e.g., year built, year updated/improved/expanded, etc.), area of living space, ratios or comparisons therebetween, and/or other attribute descriptive of the physical property construction”; see also Davison: ¶ 20 “The blockchain may be enabled to record proof of delivery of material, labor, or other services that improve a property and to record payments for delivery of material, labor, or other services. Proof may include digital scans or photos of delivery documentation, digital recording of acceptance of delivery, or photo or video documentation with embedded location information. The blockchain may be enabled to manage a network of verifiers who review documentation related to delivery of material, labor, or other services that improve a property and to record results for use in authorizing payment. The blockchain system maintains information about verifiers, including performance reviews, for use in manual or automated routing of requests for verification. The blockchain system manages payment of verifiers. The blockchain may be enabled to record evidence of improvements on a property, including photo and video documentation of in progress and completed work. The blockchain system also provides evidence of vendor payment for improvements. The blockchain system also records any applicable warranties for material, labor, or other services that improve a property.”; see at least Davison: ¶ 20 “The blockchain may be enabled to manage information used to underwrite a loan for acquisition of real property and planned improvement”; see at least Davison: ¶ 16 “FIG. 1 is a block diagram of exemplary stakeholders in a typical property flip process. The flipper 10 must obtain financing from a lender 20 for property purchase and/or rehab construction work on the subject property.”; see also Davison: ¶ 19 “The user, who may be the flipper, a lender or a third party consultant records the project scope in the system 210. The user, or the system determines as-repaired value (“ARV”) 212. This may be done automatically by the system based on publicly available market data”; see also Davison: ¶ 20-21 “The blockchain may be enabled to calculate the value of property prior to improvement and calculate an ARV based on factors including scope of work and comparable sales… the borrower records property details and valuation. Optionally, as shown in step 316, the system calculates and records property valuation. At step 318, the borrower records project scope and draw schedule (either system default or proposed alternative). Optionally, as shown at step 320, the system calculates and records after repair value (ARV). At step 322, the lender accesses borrower financial position and payment history, property details and valuation, and project scope and ARV.”; see at least Brown: ¶ 54 “The condition scoring module 200 can be specific to: a use case (e.g., real estate valuation, insurance loss estimation, maintenance/repair cost, etc.”; see also Brown: ¶ 47 “The attribute module 100 can be specific to: a use case (e.g., real estate valuation, insurance loss estimation, maintenance/repair cost, etc.), a measurement type (e.g., 2D measurement, 3D measurement, interior measurement, exterior measurement, etc.),”; see also Brown: ¶ 112 “the weights can be selected based on maintenance or repair cost per property component associated with the attribute.”; see also Brown: ¶ 125 “he condition score can be used with: personal and/or commercial lines insurance (e.g., rating, inspection optimization, etc.), real estate property investing (e.g., identify underpriced properties that can increase in value through renovation and/or repairs, incorporate condition score into a valuation model to establish the offer price, etc.”).
Referring to Claim 13, the combination of Brown, Davison, and Heatherly teaches the system of claim 12, wherein the graphical user interface operates to present a plurality of options for user-selectable material parameters and/or material specifications to the user via an application programming interface operating on a mobile cellular device (see at least Brown: ¶ 60 “The database 400 can be a SQL database, NoSQL database, and/or any other suitable database. The database 400 can be queried to retrieve the measurements, condition scores, attributes, parcel data, auxiliary data, and/or any other suitable information used to perform the method. The query can include geographic coordinates, an address, and/or any other property identifier (e.g., used to identify a parcel and/or group of parcels”; see also Brown: ¶ 54 “The condition scoring module 200 can be specific to: a use case (e.g., real estate valuation, insurance loss estimation, maintenance/repair cost, etc.”; see also Brown: ¶ 47 “The attribute module 100 can be specific to: a use case (e.g., real estate valuation, insurance loss estimation, maintenance/repair cost, etc.), a measurement type (e.g., 2D measurement, 3D measurement, interior measurement, exterior measurement, etc.),”; see also Brown: ¶ 112 “the weights can be selected based on maintenance or repair cost per property component associated with the attribute.”; see also Brown: ¶ 125 “he condition score can be used with: personal and/or commercial lines insurance (e.g., rating, inspection optimization, etc.), real estate property investing (e.g., identify underpriced properties that can increase in value through renovation and/or repairs, incorporate condition score into a valuation model to establish the offer price, etc.”; see also Brown: ¶ 33-36 and 77-78: discussing the system storing a record of materials based on the specified modification to the real asset… “property component parameters (e.g., area, enclosure, presence, structure type, count, material, construction type, area condition, spacing, etc.” and “Attributes associated with a property component can include: location (e.g., centroid location), boundary, distance (e.g., to another property component, to a geographic landmark, to wildland, setback distance, etc.), material, type, presence, count, density, geometry parameters (e.g., footprint and/or area, area ratios and/or percentages, complexity, number of facets and/or other elements, slope, height, etc.), condition (e.g., a condition rating), hazard context, geographic context, vegetation context (e.g., based on an area larger than the property), weather context, terrain context, historical construction information, ratios or comparisons therebetween, counts, and/or any other parameter associated with one or more property components…Structural attributes can include: the structure footprint, structure density, count, structure class/type, proximity information and/or setback distance (e.g., relative to a primary structure, relative to another property component, etc.), building height, parcel area, number of bedrooms, number of bathrooms, number of stories, roof parameters (e.g., area, area relative to structure area, geometry/shape, slope, complexity, number of facets, height, material, roof extension, solar panel presence, solar panel area, etc.), framing parameters (e.g., material), flooring (e.g., floor type), historical construction information (e.g., year built, year updated/improved/expanded, etc.), area of living space, ratios or comparisons therebetween, and/or other attribute descriptive of the physical property construction”; see also Davison: ¶ 20 “The blockchain may be enabled to record proof of delivery of material, labor, or other services that improve a property and to record payments for delivery of material, labor, or other services. Proof may include digital scans or photos of delivery documentation, digital recording of acceptance of delivery, or photo or video documentation with embedded location information. The blockchain may be enabled to manage a network of verifiers who review documentation related to delivery of material, labor, or other services that improve a property and to record results for use in authorizing payment. The blockchain system maintains information about verifiers, including performance reviews, for use in manual or automated routing of requests for verification. The blockchain system manages payment of verifiers. The blockchain may be enabled to record evidence of improvements on a property, including photo and video documentation of in progress and completed work. The blockchain system also provides evidence of vendor payment for improvements. The blockchain system also records any applicable warranties for material, labor, or other services that improve a property.”; see at least Davison: ¶ 20 “The blockchain may be enabled to manage information used to underwrite a loan for acquisition of real property and planned improvement”; see at least Davison: ¶ 16 “FIG. 1 is a block diagram of exemplary stakeholders in a typical property flip process. The flipper 10 must obtain financing from a lender 20 for property purchase and/or rehab construction work on the subject property.”; see also Davison: ¶ 19 “The user, who may be the flipper, a lender or a third party consultant records the project scope in the system 210. The user, or the system determines as-repaired value (“ARV”) 212. This may be done automatically by the system based on publicly available market data”; see also Davison: ¶ 20-21 “The blockchain may be enabled to calculate the value of property prior to improvement and calculate an ARV based on factors including scope of work and comparable sales… the borrower records property details and valuation. Optionally, as shown in step 316, the system calculates and records property valuation. At step 318, the borrower records project scope and draw schedule (either system default or proposed alternative). Optionally, as shown at step 320, the system calculates and records after repair value (ARV). At step 322, the lender accesses borrower financial position and payment history, property details and valuation, and project scope and ARV.”; see at least Brown: ¶ 54 “The condition scoring module 200 can be specific to: a use case (e.g., real estate valuation, insurance loss estimation, maintenance/repair cost, etc.”; see also Brown: ¶ 47 “The attribute module 100 can be specific to: a use case (e.g., real estate valuation, insurance loss estimation, maintenance/repair cost, etc.), a measurement type (e.g., 2D measurement, 3D measurement, interior measurement, exterior measurement, etc.),”; see also Brown: ¶ 112 “the weights can be selected based on maintenance or repair cost per property component associated with the attribute.”; see also Brown: ¶ 125 “he condition score can be used with: personal and/or commercial lines insurance (e.g., rating, inspection optimization, etc.), real estate property investing (e.g., identify underpriced properties that can increase in value through renovation and/or repairs, incorporate condition score into a valuation model to establish the offer price, etc.”).
Referring to Claim 14, the combination of Brown, Davison, and Heatherly teaches the system of claim 13, wherein the graphical user interface is to interact with a computer-aided design module, which operates to model of a certain aspects of the real asset (see at least Brown: ¶ 29 “the visual appearance (e.g., wherein the measurement depicts the property or surrounding geographic region), a geometry (e.g., depth), a chemical composition, audio, and/or any other parameter. The measurement can be: 2D, 3D or geometric, and/or have any other set of dimensions. Examples of measurements can include: images (e.g., 2D images, 3D images, etc.), surface models (e.g., digital surface models (DSM), digital elevation models (DEM), digital terrain models (DTM), etc.), point clouds (e.g., generated from LIDAR, RADAR, stereoscopic imagery, etc.), depth maps, depth images, virtual models (e.g., geometric models, mesh models), audio, video, and/or any other suitable measurement”; see also Brown: ¶ 47 “a measurement type (e.g., 2D measurement, 3D measurement, interior measurement, exterior measurement, etc.)”; see also Brown: ¶ 54 and 66; see also Davison: ¶ 33).
Referring to Claim 15, the combination of Brown, Davison, and Heatherly teaches the system of claim 14, wherein the one or more computer processors coupled to the at least one memory device is additionally to: generate, without user input, a listing of material specifications and/or contractor work descriptions responsive to communicating with the computer-aided design module (see at least Brown: ¶ 60 “The database 400 can be a SQL database, NoSQL database, and/or any other suitable database. The database 400 can be queried to retrieve the measurements, condition scores, attributes, parcel data, auxiliary data, and/or any other suitable information used to perform the method. The query can include geographic coordinates, an address, and/or any other property identifier (e.g., used to identify a parcel and/or group of parcels”; see also Brown: ¶ 54 “The condition scoring module 200 can be specific to: a use case (e.g., real estate valuation, insurance loss estimation, maintenance/repair cost, etc.”; see also Brown: ¶ 47 “The attribute module 100 can be specific to: a use case (e.g., real estate valuation, insurance loss estimation, maintenance/repair cost, etc.), a measurement type (e.g., 2D measurement, 3D measurement, interior measurement, exterior measurement, etc.),”; see also Brown: ¶ 112 “the weights can be selected based on maintenance or repair cost per property component associated with the attribute.”; see also Brown: ¶ 125 “he condition score can be used with: personal and/or commercial lines insurance (e.g., rating, inspection optimization, etc.), real estate property investing (e.g., identify underpriced properties that can increase in value through renovation and/or repairs, incorporate condition score into a valuation model to establish the offer price, etc.”; see also Brown: ¶ 33-36 and 77-78: discussing the system storing a record of materials based on the specified modification to the real asset… “property component parameters (e.g., area, enclosure, presence, structure type, count, material, construction type, area condition, spacing, etc.” and “Attributes associated with a property component can include: location (e.g., centroid location), boundary, distance (e.g., to another property component, to a geographic landmark, to wildland, setback distance, etc.), material, type, presence, count, density, geometry parameters (e.g., footprint and/or area, area ratios and/or percentages, complexity, number of facets and/or other elements, slope, height, etc.), condition (e.g., a condition rating), hazard context, geographic context, vegetation context (e.g., based on an area larger than the property), weather context, terrain context, historical construction information, ratios or comparisons therebetween, counts, and/or any other parameter associated with one or more property components…Structural attributes can include: the structure footprint, structure density, count, structure class/type, proximity information and/or setback distance (e.g., relative to a primary structure, relative to another property component, etc.), building height, parcel area, number of bedrooms, number of bathrooms, number of stories, roof parameters (e.g., area, area relative to structure area, geometry/shape, slope, complexity, number of facets, height, material, roof extension, solar panel presence, solar panel area, etc.), framing parameters (e.g., material), flooring (e.g., floor type), historical construction information (e.g., year built, year updated/improved/expanded, etc.), area of living space, ratios or comparisons therebetween, and/or other attribute descriptive of the physical property construction”; see also Davison: ¶ 20 “The blockchain may be enabled to record proof of delivery of material, labor, or other services that improve a property and to record payments for delivery of material, labor, or other services. Proof may include digital scans or photos of delivery documentation, digital recording of acceptance of delivery, or photo or video documentation with embedded location information. The blockchain may be enabled to manage a network of verifiers who review documentation related to delivery of material, labor, or other services that improve a property and to record results for use in authorizing payment. The blockchain system maintains information about verifiers, including performance reviews, for use in manual or automated routing of requests for verification. The blockchain system manages payment of verifiers. The blockchain may be enabled to record evidence of improvements on a property, including photo and video documentation of in progress and completed work. The blockchain system also provides evidence of vendor payment for improvements. The blockchain system also records any applicable warranties for material, labor, or other services that improve a property.”; see at least Davison: ¶ 20 “The blockchain may be enabled to manage information used to underwrite a loan for acquisition of real property and planned improvement”; see at least Davison: ¶ 16 “FIG. 1 is a block diagram of exemplary stakeholders in a typical property flip process. The flipper 10 must obtain financing from a lender 20 for property purchase and/or rehab construction work on the subject property.”; see also Davison: ¶ 19 “The user, who may be the flipper, a lender or a third party consultant records the project scope in the system 210. The user, or the system determines as-repaired value (“ARV”) 212. This may be done automatically by the system based on publicly available market data”; see also Davison: ¶ 20-21 “The blockchain may be enabled to calculate the value of property prior to improvement and calculate an ARV based on factors including scope of work and comparable sales… the borrower records property details and valuation. Optionally, as shown in step 316, the system calculates and records property valuation. At step 318, the borrower records project scope and draw schedule (either system default or proposed alternative). Optionally, as shown at step 320, the system calculates and records after repair value (ARV). At step 322, the lender accesses borrower financial position and payment history, property details and valuation, and project scope and ARV.”; see at least Brown: ¶ 54 “The condition scoring module 200 can be specific to: a use case (e.g., real estate valuation, insurance loss estimation, maintenance/repair cost, etc.”; see also Brown: ¶ 47 “The attribute module 100 can be specific to: a use case (e.g., real estate valuation, insurance loss estimation, maintenance/repair cost, etc.), a measurement type (e.g., 2D measurement, 3D measurement, interior measurement, exterior measurement, etc.),”; see also Brown: ¶ 112 “the weights can be selected based on maintenance or repair cost per property component associated with the attribute.”; see also Brown: ¶ 125 “he condition score can be used with: personal and/or commercial lines insurance (e.g., rating, inspection optimization, etc.), real estate property investing (e.g., identify underpriced properties that can increase in value through renovation and/or repairs, incorporate condition score into a valuation model to establish the offer price, etc.”; see at least Brown: ¶ 29 “the visual appearance (e.g., wherein the measurement depicts the property or surrounding geographic region), a geometry (e.g., depth), a chemical composition, audio, and/or any other parameter. The measurement can be: 2D, 3D or geometric, and/or have any other set of dimensions. Examples of measurements can include: images (e.g., 2D images, 3D images, etc.), surface models (e.g., digital surface models (DSM), digital elevation models (DEM), digital terrain models (DTM), etc.), point clouds (e.g., generated from LIDAR, RADAR, stereoscopic imagery, etc.), depth maps, depth images, virtual models (e.g., geometric models, mesh models), audio, video, and/or any other suitable measurement”; see also Brown: ¶ 47 “a measurement type (e.g., 2D measurement, 3D measurement, interior measurement, exterior measurement, etc.)”; see also Brown: ¶ 54 and 66; see also Davison: ¶ 33).
Referring to Claim 16, the combination of Brown, Davison, and Heatherly teaches the system of claim 14, wherein the financial resource premium is based, at least in part, on output signals from the computer-aided design module (see at least Brown: ¶ 29 “the visual appearance (e.g., wherein the measurement depicts the property or surrounding geographic region), a geometry (e.g., depth), a chemical composition, audio, and/or any other parameter. The measurement can be: 2D, 3D or geometric, and/or have any other set of dimensions. Examples of measurements can include: images (e.g., 2D images, 3D images, etc.), surface models (e.g., digital surface models (DSM), digital elevation models (DEM), digital terrain models (DTM), etc.), point clouds (e.g., generated from LIDAR, RADAR, stereoscopic imagery, etc.), depth maps, depth images, virtual models (e.g., geometric models, mesh models), audio, video, and/or any other suitable measurement”; see also Brown: ¶ 47 “a measurement type (e.g., 2D measurement, 3D measurement, interior measurement, exterior measurement, etc.)”; see also Brown: ¶ 54 and 66; see also Davison: ¶ 33).
Referring to Claim 18, the combination of Brown, Davison, and Heatherly teaches the method of claim 1including wherein the computer-readable instructions are additionally operable to: compute a fraction of the amount of the financial resource premium provided to the first entity responsive to a second entity procuring the real asset (see at least Davison: ¶ 20 “The blockchain may be enabled to manage information used to underwrite a loan for acquisition of real property and planned improvements. The blockchain may be enabled in a draw schedule for funds disbursement as milestones are achieved, record funds transfers based on achievement of milestones, with optional transfers directly from lender to vendors, record payments made by the borrower, and record the loan payoff”; see also Davison: ¶ 21 “the borrower records project scope and draw schedule (either system default or proposed alternative). Optionally, as shown at step 320, the system calculates and records after repair value (ARV). At step 322, the lender accesses borrower financial position and payment history, property details and valuation, and project scope and ARV. At step 324, the lender records a loan offer, including draw schedule.”; see also Davison: ¶ 22 “At step 426, if draw requirements are met, the system initiates (or executes) and records payment from lender to borrower (or vendor(s), if specified) for draw amount.”; see also Davison: ¶ 25 “the system pays the vendor based on payment terms. At step 626, when a vendor is associated with a draw in a draw schedule and the draw is approved, system initiates (or executes) and records a transfer directly from the lender to the vendor.”).
Therefore, it would have been obvious to one of ordinary skill in the art at the time of filing to apply the known technique of on-line management of real estate purchase, renovation and sale transactions wherein financing is procured in consideration of future planned improvements (as disclosed by Davison) to the known method and system for managing real estate transactions wherein the system provides an estimate related to a property valuation which incorporates the estimate for repair or modification of a real property asset and an estimated cost (as disclosed by Brown) to reduce inspection fees and wait times ¶ 23; track the flipping process end-to-end from initial purchase of the subject property through financing, renovation and sale to consumers ¶ 2; and allow renovators, lenders, vendors and inspectors to record aspects of the purchase, renovation and sale of the real estate in the blockchain (see at least Davison: Abstract). One of ordinary skill in the art would have been motivated to apply the known technique of on-line management of real estate purchase, renovation and sale transactions wherein financing is procured in consideration of future planned improvements because it would to reduce inspection fees and wait times ¶ 23; track the flipping process end-to-end from initial purchase of the subject property through financing, renovation and sale to consumers ¶ 2; and allow renovators, lenders, vendors and inspectors to record aspects of the purchase, renovation and sale of the real estate in the blockchain (see at least Davison: Abstract).
Referring to Claim 19, the combination of Brown, Davison, and Heatherly teaches the article of claim 17, wherein the group of digitized parameters representing the real asset correspond to construction parameters of the real asset (see at least Brown: ¶ 60 “The database 400 can be a SQL database, NoSQL database, and/or any other suitable database. The database 400 can be queried to retrieve the measurements, condition scores, attributes, parcel data, auxiliary data, and/or any other suitable information used to perform the method. The query can include geographic coordinates, an address, and/or any other property identifier (e.g., used to identify a parcel and/or group of parcels”; see also Brown: ¶ 54 “The condition scoring module 200 can be specific to: a use case (e.g., real estate valuation, insurance loss estimation, maintenance/repair cost, etc.”; see also Brown: ¶ 47 “The attribute module 100 can be specific to: a use case (e.g., real estate valuation, insurance loss estimation, maintenance/repair cost, etc.), a measurement type (e.g., 2D measurement, 3D measurement, interior measurement, exterior measurement, etc.),”; see also Brown: ¶ 112 “the weights can be selected based on maintenance or repair cost per property component associated with the attribute.”; see also Brown: ¶ 125 “he condition score can be used with: personal and/or commercial lines insurance (e.g., rating, inspection optimization, etc.), real estate property investing (e.g., identify underpriced properties that can increase in value through renovation and/or repairs, incorporate condition score into a valuation model to establish the offer price, etc.”; see also Brown: ¶ 33-36 and 77-78: discussing the system storing a record of materials based on the specified modification to the real asset… “property component parameters (e.g., area, enclosure, presence, structure type, count, material, construction type, area condition, spacing, etc.” and “Attributes associated with a property component can include: location (e.g., centroid location), boundary, distance (e.g., to another property component, to a geographic landmark, to wildland, setback distance, etc.), material, type, presence, count, density, geometry parameters (e.g., footprint and/or area, area ratios and/or percentages, complexity, number of facets and/or other elements, slope, height, etc.), condition (e.g., a condition rating), hazard context, geographic context, vegetation context (e.g., based on an area larger than the property), weather context, terrain context, historical construction information, ratios or comparisons therebetween, counts, and/or any other parameter associated with one or more property components…Structural attributes can include: the structure footprint, structure density, count, structure class/type, proximity information and/or setback distance (e.g., relative to a primary structure, relative to another property component, etc.), building height, parcel area, number of bedrooms, number of bathrooms, number of stories, roof parameters (e.g., area, area relative to structure area, geometry/shape, slope, complexity, number of facets, height, material, roof extension, solar panel presence, solar panel area, etc.), framing parameters (e.g., material), flooring (e.g., floor type), historical construction information (e.g., year built, year updated/improved/expanded, etc.), area of living space, ratios or comparisons therebetween, and/or other attribute descriptive of the physical property construction”; see also Davison: ¶ 20 “The blockchain may be enabled to record proof of delivery of material, labor, or other services that improve a property and to record payments for delivery of material, labor, or other services. Proof may include digital scans or photos of delivery documentation, digital recording of acceptance of delivery, or photo or video documentation with embedded location information. The blockchain may be enabled to manage a network of verifiers who review documentation related to delivery of material, labor, or other services that improve a property and to record results for use in authorizing payment. The blockchain system maintains information about verifiers, including performance reviews, for use in manual or automated routing of requests for verification. The blockchain system manages payment of verifiers. The blockchain may be enabled to record evidence of improvements on a property, including photo and video documentation of in progress and completed work. The blockchain system also provides evidence of vendor payment for improvements. The blockchain system also records any applicable warranties for material, labor, or other services that improve a property.”; see at least Davison: ¶ 20 “The blockchain may be enabled to manage information used to underwrite a loan for acquisition of real property and planned improvement”; see at least Davison: ¶ 16 “FIG. 1 is a block diagram of exemplary stakeholders in a typical property flip process. The flipper 10 must obtain financing from a lender 20 for property purchase and/or rehab construction work on the subject property.”; see also Davison: ¶ 19 “The user, who may be the flipper, a lender or a third party consultant records the project scope in the system 210. The user, or the system determines as-repaired value (“ARV”) 212. This may be done automatically by the system based on publicly available market data”; see also Davison: ¶ 20-21 “The blockchain may be enabled to calculate the value of property prior to improvement and calculate an ARV based on factors including scope of work and comparable sales… the borrower records property details and valuation. Optionally, as shown in step 316, the system calculates and records property valuation. At step 318, the borrower records project scope and draw schedule (either system default or proposed alternative). Optionally, as shown at step 320, the system calculates and records after repair value (ARV). At step 322, the lender accesses borrower financial position and payment history, property details and valuation, and project scope and ARV.”; see at least Brown: ¶ 54 “The condition scoring module 200 can be specific to: a use case (e.g., real estate valuation, insurance loss estimation, maintenance/repair cost, etc.”; see also Brown: ¶ 47 “The attribute module 100 can be specific to: a use case (e.g., real estate valuation, insurance loss estimation, maintenance/repair cost, etc.), a measurement type (e.g., 2D measurement, 3D measurement, interior measurement, exterior measurement, etc.),”; see also Brown: ¶ 112 “the weights can be selected based on maintenance or repair cost per property component associated with the attribute.”; see also Brown: ¶ 125 “he condition score can be used with: personal and/or commercial lines insurance (e.g., rating, inspection optimization, etc.), real estate property investing (e.g., identify underpriced properties that can increase in value through renovation and/or repairs, incorporate condition score into a valuation model to establish the offer price, etc.”).
Referring to Claim 20, the combination of Brown, Davison, and Heatherly teaches the article of claim 19, wherein the construction parameters of the real asset correspond to at least one of: a floor plan, a type of flooring in one or more sections of the real asset, a roof type, cabinetry parameters, installed appliance parameters, countertop parameters, outside landscaping parameters, kitchen fixture parameters, bathroom fixture parameters, interior wall coloring, and exterior coloring (see at least Brown: ¶ 92 “In a sixth variant, S300 can include using a condition scoring model that directly ingests the measurement depicting the property and outputs the condition score. The condition scoring model can optionally ingest a property description vector extracted from a property description (e.g., from a real estate listing service) using an NLP model, keywords identified in the property description (e.g., “turnkey”, “potential”, “as-is”), and/or other attributes extracted from the property description; example shown in FIG. 7 .”; see also Brown: ¶ 30 “The condition score can be discrete, continuous, binary, multiclass, numerical, categorical, and/or otherwise structured. The condition score can be a label, or not be a label. The condition score can be a multi-class label (e.g., severe, poor, fair, good, excellent, etc.), a binary label (e.g., good or poor corresponding to 1 or 0), a value (e.g., 0-5, 0-10, 0-100, etc.; an integer value, a decimal value, etc.), and/or any other suitable score.”; see also Brown: ¶ 38 “Attribute values can be discrete, continuous, binary, multiclass, and/or otherwise structured.”; see also Brown: ¶ 45, 51, 73, 77-79: binary use) binary digits (see also Brown: ¶ 30 “The condition score can be discrete, continuous, binary, multiclass, numerical, categorical, and/or otherwise structured. The condition score can be a label, or not be a label. The condition score can be a multi-class label (e.g., severe, poor, fair, good, excellent, etc.), a binary label (e.g., good or poor corresponding to 1 or 0), a value (e.g., 0-5, 0-10, 0-100, etc.; an integer value, a decimal value, etc.), and/or any other suitable score.”; see also Brown: ¶ 38 “Attribute values can be discrete, continuous, binary, multiclass, and/or otherwise structured.”; see also Brown: ¶ 45, 51, 73, 77-79: binary use; see also Brown: ¶ 125 “The condition score can be used to determine: automated valuation model error, insurance loss ratio (e.g., insurance loss divided by premium), and/or any other value. The condition score can be used with: personal and/or commercial lines insurance (e.g., rating, inspection optimization, etc.), real estate property investing (e.g., identify underpriced properties that can increase in value through renovation and/or repairs, incorporate condition score into a valuation model to establish the offer price, etc.), real estate loan trading (e.g., use condition score to evaluate the quality of a loan pool and adjust bid price accordingly; use condition score to identify acute condition issues that can result in removal of a loan from the pool during due diligence; use condition score as an input into a model that predicts probability of default; etc.), real estate mortgage origination (e.g., GSEs can use the condition score to determine whether they will allow a property inspection waiver; originators of non-agency or agency loans can use the condition score as an input into their underwriting criteria; etc.), real estate valuations (e.g., use condition score as an input to an automated valuation model; use condition score as a supplement to a property-level valuation report; etc.), and/or otherwise used”; see also Brown: ¶ 126 “The property attributes and/or component values can be used to determine: automated valuation model error, automated valuation model accuracy, automated property valuation or price, and/or any other suitable value. The AVM can be: retrieved from a database, determined dynamically, and/or otherwise determined”; see also Brown: ¶ 130 “the attributes can describe property components (e.g., age of vegetation, age of roof of built structure, age of paved surface, price to replace roof, price to replace surface, etc.)”).
Referring to Claim 21, the combination of Brown, Davison, and Heatherly teaches the article of claim 20, wherein the instructions are additionally operable to: form a record of materials and/or material specifications, and to transmit the record of the materials and/or the material specifications to a contracting entity (see at least Brown: ¶ 60 “The database 400 can be a SQL database, NoSQL database, and/or any other suitable database. The database 400 can be queried to retrieve the measurements, condition scores, attributes, parcel data, auxiliary data, and/or any other suitable information used to perform the method. The query can include geographic coordinates, an address, and/or any other property identifier (e.g., used to identify a parcel and/or group of parcels”; see also Brown: ¶ 54 “The condition scoring module 200 can be specific to: a use case (e.g., real estate valuation, insurance loss estimation, maintenance/repair cost, etc.”; see also Brown: ¶ 47 “The attribute module 100 can be specific to: a use case (e.g., real estate valuation, insurance loss estimation, maintenance/repair cost, etc.), a measurement type (e.g., 2D measurement, 3D measurement, interior measurement, exterior measurement, etc.),”; see also Brown: ¶ 112 “the weights can be selected based on maintenance or repair cost per property component associated with the attribute.”; see also Brown: ¶ 125 “he condition score can be used with: personal and/or commercial lines insurance (e.g., rating, inspection optimization, etc.), real estate property investing (e.g., identify underpriced properties that can increase in value through renovation and/or repairs, incorporate condition score into a valuation model to establish the offer price, etc.”; see also Brown: ¶ 33-36 and 77-78: discussing the system storing a record of materials based on the specified modification to the real asset… “property component parameters (e.g., area, enclosure, presence, structure type, count, material, construction type, area condition, spacing, etc.” and “Attributes associated with a property component can include: location (e.g., centroid location), boundary, distance (e.g., to another property component, to a geographic landmark, to wildland, setback distance, etc.), material, type, presence, count, density, geometry parameters (e.g., footprint and/or area, area ratios and/or percentages, complexity, number of facets and/or other elements, slope, height, etc.), condition (e.g., a condition rating), hazard context, geographic context, vegetation context (e.g., based on an area larger than the property), weather context, terrain context, historical construction information, ratios or comparisons therebetween, counts, and/or any other parameter associated with one or more property components…Structural attributes can include: the structure footprint, structure density, count, structure class/type, proximity information and/or setback distance (e.g., relative to a primary structure, relative to another property component, etc.), building height, parcel area, number of bedrooms, number of bathrooms, number of stories, roof parameters (e.g., area, area relative to structure area, geometry/shape, slope, complexity, number of facets, height, material, roof extension, solar panel presence, solar panel area, etc.), framing parameters (e.g., material), flooring (e.g., floor type), historical construction information (e.g., year built, year updated/improved/expanded, etc.), area of living space, ratios or comparisons therebetween, and/or other attribute descriptive of the physical property construction”; see also Davison: ¶ 20 “The blockchain may be enabled to record proof of delivery of material, labor, or other services that improve a property and to record payments for delivery of material, labor, or other services. Proof may include digital scans or photos of delivery documentation, digital recording of acceptance of delivery, or photo or video documentation with embedded location information. The blockchain may be enabled to manage a network of verifiers who review documentation related to delivery of material, labor, or other services that improve a property and to record results for use in authorizing payment. The blockchain system maintains information about verifiers, including performance reviews, for use in manual or automated routing of requests for verification. The blockchain system manages payment of verifiers. The blockchain may be enabled to record evidence of improvements on a property, including photo and video documentation of in progress and completed work. The blockchain system also provides evidence of vendor payment for improvements. The blockchain system also records any applicable warranties for material, labor, or other services that improve a property.”; see at least Davison: ¶ 20 “The blockchain may be enabled to manage information used to underwrite a loan for acquisition of real property and planned improvement”; see at least Davison: ¶ 16 “FIG. 1 is a block diagram of exemplary stakeholders in a typical property flip process. The flipper 10 must obtain financing from a lender 20 for property purchase and/or rehab construction work on the subject property.”; see also Davison: ¶ 19 “The user, who may be the flipper, a lender or a third party consultant records the project scope in the system 210. The user, or the system determines as-repaired value (“ARV”) 212. This may be done automatically by the system based on publicly available market data”; see also Davison: ¶ 20-21 “The blockchain may be enabled to calculate the value of property prior to improvement and calculate an ARV based on factors including scope of work and comparable sales… the borrower records property details and valuation. Optionally, as shown in step 316, the system calculates and records property valuation. At step 318, the borrower records project scope and draw schedule (either system default or proposed alternative). Optionally, as shown at step 320, the system calculates and records after repair value (ARV). At step 322, the lender accesses borrower financial position and payment history, property details and valuation, and project scope and ARV.”; see at least Brown: ¶ 54 “The condition scoring module 200 can be specific to: a use case (e.g., real estate valuation, insurance loss estimation, maintenance/repair cost, etc.”; see also Brown: ¶ 47 “The attribute module 100 can be specific to: a use case (e.g., real estate valuation, insurance loss estimation, maintenance/repair cost, etc.), a measurement type (e.g., 2D measurement, 3D measurement, interior measurement, exterior measurement, etc.),”; see also Brown: ¶ 112 “the weights can be selected based on maintenance or repair cost per property component associated with the attribute.”; see also Brown: ¶ 125 “he condition score can be used with: personal and/or commercial lines insurance (e.g., rating, inspection optimization, etc.), real estate property investing (e.g., identify underpriced properties that can increase in value through renovation and/or repairs, incorporate condition score into a valuation model to establish the offer price, etc.”).
Response to Arguments
101 Rejection
Applicant's arguments filed with respect to the rejection of the claims under 35 USC 101 have been fully considered but they are not persuasive.
Applicant “respectfully submits that amended claim 1 includes an additional element that applies 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 claims as a whole are more than a drafting effort designed to monopolize the exception, which the 2019 Guidance is indicative that the additional element (or combination of elements) may have integrated the exception into a practical application”. Examiner respectfully disagrees and submits that the claimed invention amounts to using computing elements as a tool to implement the identified judicial exceptions and do not amount to a practical application under the guidance.
Examiner notes that claims 1-21 recite a method, system, and apparatus for customizing a real asset, comprising: forming, via one or more computer processors coupled to at least one memory device, a group of digitized parameters representing the real asset; receiving, via a graphical user interface coupled to the one or more computer processors, specified proposed modifications to the real asset; storing, in the at least one memory device, binary digits corresponding to an as- is value of the real asset, binary digits corresponding to an estimate of resources allocated to modify the real asset in accordance with the specified proposed modifications, and an estimated value of the real asset that is to include the specified proposed modifications; computing, based, at least in part, on the estimate of the resources via the one or more computer processors, an amount of a financial resource premium for a proposed agreement between a current owner of the real asset and a first entity that permits [[a]] the first entity to procure the real asset at the as-is value or a specified percentage thereof within a specified period of time and that directs that the financial resource premium be provided by the first entity for the purpose of implementing the specified proposed modifications; and forming a record of materials and/or material specifications based, at least in part, on the specified proposed modifications to the real asset which is directed to concepts that are performed mentally and a product of human mental work. The limitations suggest a process similar to receiving information related to real estate planned improvements and valuations, processing the information and storing the information within the system, and the steps involved human judgments, observations and evaluations that can be practically or reasonably performed in the human mind, the claim recites an abstract idea consistent with the “mental process” grouping set forth in the see MPEP 2106.04(a)(2)(III).
Alternatively, Examiner notes that claims 12-21 recite a method, system, and apparatus for customizing a real asset, comprising: forming, via one or more computer processors coupled to at least one memory device, a group of digitized parameters representing the real asset; receiving, via a graphical user interface coupled to the one or more computer processors, specified proposed modifications to the real asset; storing, in the at least one memory device, binary digits corresponding to an as- is value of the real asset, binary digits corresponding to an estimate of resources allocated to modify the real asset in accordance with the specified proposed modifications, and an estimated value of the real asset that is to include the specified proposed modifications; computing, based, at least in part, on the estimate of the resources via the one or more computer processors, an amount of a financial resource premium for a proposed agreement between a current owner of the real asset and a first entity that permits [[a]] the first entity to procure the real asset at the as-is value or a specified percentage thereof within a specified period of time and that directs that the financial resource premium be provided by the first entity for the purpose of implementing the specified proposed modifications; and forming a record of materials and/or material specifications based, at least in part, on the specified proposed modifications to the real asset, and is similar to the abstract idea identified in MPEP 2106.04(a)(2)(II) in grouping “II” in that the claims recite certain methods of organizing human activity such as real estate transactions. This is merely further embellishments of the abstract idea and does not further limit the claimed invention to render the claims patentable subject matter. The limitations, substantially comprising the body of the claim, recite standard processes found in standard practice in transfer of real estate property for commercial or residential flippers. The purchasers are able to get approval from their respective banks for the purchase of “as-is” properties and associating planned improvement financing to the overall funding agreement. This is common practice in every area of real estate wherein the property is purchased at a price that accounts for the condition of the property, account for potential plans in the granting of funding based on the planned improvements and construction wherein the funding is dispersed based on the completed aspects of the improvements. Because the limitations above closely follow the steps standard in interactions between people and businesses such as real estate transactions such as flipping houses, and the steps of the claims involve organizing human activity, the claim recites an abstract idea consistent with the “organizing human activity” grouping set forth in the see MPEP 2106.04(a)(2)(II).
Claims can recite a mental process (judicial exception) even if they are claimed as being performed on a computer. The Supreme Court recognized this in Benson, determining that a mathematical algorithm for converting binary coded decimal to pure binary within a computer’s shift register was an abstract idea. The Court concluded that the algorithm could be performed purely mentally even though the claimed procedures "can be carried out in existing computers long in use, no new machinery being necessary." 409 U.S at 67, 175 USPQ at 675. See also Mortgage Grader, 811 F.3d at 1324, 117 USPQ2d at 1699 (concluding that concept of "anonymous loan shopping" recited in a computer system claim is an abstract idea because it could be "performed by humans without a computer").
In evaluating whether a claim that requires a computer recites a mental process, examiners should carefully consider the broadest reasonable interpretation of the claim in light of the specification. For instance, examiners should review the specification to determine if the claimed invention is described as a concept that is performed in the human mind and applicant is merely claiming that concept performed 1) on a generic computer, or 2) in a computer environment, or 3) is merely using a computer as a tool to perform the concept. In these situations, the claim is considered to recite a mental process.
An example of a case identifying a mental process performed on a generic computer as an abstract idea is Voter Verified, Inc. v. Election Systems & Software, LLC, 887 F.3d 1376, 1385, 126 USPQ2d 1498, 1504 (Fed. Cir. 2018). In this case, the Federal Circuit relied upon the specification in explaining that the claimed steps of voting, verifying the vote, and submitting the vote for tabulation are "human cognitive actions" that humans have performed for hundreds of years. The claims therefore recited an abstract idea, despite the fact that the claimed voting steps were performed on a computer. 887 F.3d at 1385, 126 USPQ2d at 1504. Another example is FairWarning IP, LLC v. Iatric Sys., Inc., 839 F.3d 1089, 120 USPQ2d 1293 (Fed. Cir. 2016). The patentee in FairWarning claimed a system and method of detecting fraud and/or misuse in a computer environment, in which information regarding accesses of a patient’s personal health information was analyzed according to one of several rules (i.e., related to accesses in excess of a specific volume, accesses during a pre-determined time interval, or accesses by a specific user) to determine if the activity indicates improper access. 839 F.3d. at 1092, 120 USPQ2d at 1294. The court determined that these claims were directed to a mental process of detecting misuse, and that the claimed rules here were "the same questions (though perhaps phrased with different words) that humans in analogous situations detecting fraud have asked for decades, if not centuries." 839 F.3d. at 1094-95, 120 USPQ2d at 1296.
An example of a case in which a computer was used as a tool to perform a mental process is Mortgage Grader, 811 F.3d. at 1324, 117 USPQ2d at 1699. The patentee in Mortgage Grader claimed a computer-implemented system for enabling borrowers to anonymously shop for loan packages offered by a plurality of lenders, comprising a database that stores loan package data from the lenders, and a computer system providing an interface and a grading module. The interface prompts a borrower to enter personal information, which the grading module uses to calculate the borrower’s credit grading, and allows the borrower to identify and compare loan packages in the database using the credit grading. 811 F.3d. at 1318, 117 USPQ2d at 1695. The Federal Circuit determined that these claims were directed to the concept of "anonymous loan shopping", which was a concept that could be "performed by humans without a computer." 811 F.3d. at 1324, 117 USPQ2d at 1699. Another example is Berkheimer v. HP, Inc., 881 F.3d 1360, 125 USPQ2d 1649 (Fed. Cir. 2018), in which the patentee claimed methods for parsing and evaluating data using a computer processing system. The Federal Circuit determined that these claims were directed to mental processes of parsing and comparing data, because the steps were recited at a high level of generality and merely used computers as a tool to perform the processes. 881 F.3d at 1366, 125 USPQ2d at 1652-53.
Both product claims (e.g., computer system, computer-readable medium, etc.) and process claims may recite mental processes. For example, in Mortgage Grader, the patentee claimed a computer-implemented system and a method for enabling borrowers to anonymously shop for loan packages offered by a plurality of lenders, comprising a database that stores loan package data from the lenders, and a computer system providing an interface and a grading module. The Federal Circuit determined that both the computer-implemented system and method claims were directed to "anonymous loan shopping", which was an abstract idea because it could be "performed by humans without a computer." 811 F.3d. at 1318, 1324-25, 117 USPQ2d at 1695, 1699-1700. See also FairWarning IP, 839 F.3d at 1092, 120 USPQ2d at 1294 (identifying both system and process claims for detecting improper access of a patient's protected health information in a health-care system computer environment as directed to abstract idea of detecting fraud); Content Extraction & Transmission LLC v. Wells Fargo Bank, N.A., 776 F.3d 1343, 1345, 113 USPQ2d 1354, 1356 (Fed. Cir. 2014) (system and method claims of inputting information from a hard copy document into a computer program). Accordingly, the phrase "mental processes" should be understood as referring to the type of abstract idea, and not to the statutory category of the claim.
Examples of product claims reciting mental processes include: An application program interface for extracting and processing information from a diversity of types of hard copy documents – Content Extraction, 776 F.3d at 1345, 113 USPQ2d at 1356; and A computer readable medium containing program instructions for detecting fraud – CyberSource, 654 F.3d at 1368 n. 1, 99 USPQ2d at 1692 n.1.
Examiner notes that the claimed in invention is similar to the Voter Verified, Inc., FairWarning, Mortgage Grader, Berkheimer, Content Extraction and CyberSource applications wherein the court identified computer system or “one or more computer processors coupled to at least one memory device” is merely server as a generic computer, computing environment, or tool to perform the abstract idea.
The second part of the Alice/Mayo test is often referred to as a search for an inventive concept. Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 573 U.S. 208, 217, 110 USPQ2d 1976, 1981 (2014) (citing Mayo Collaborative Servs. v. Prometheus Labs., Inc., 566 U.S. 66, 71-72, 101 USPQ2d 1961, 1966 (2012)).
Evaluating additional elements to determine whether they amount to an inventive concept requires considering them both individually and in combination to ensure that they amount to significantly more than the judicial exception itself. Because this approach considers all claim elements, the Supreme Court has noted that "it is consistent with the general rule that patent claims ‘must be considered as a whole.’" Alice Corp., 573 U.S. at 218 n.3, 110 USPQ2d at 1981 (quoting Diamond v. Diehr, 450 U.S. 175, 188, 209 USPQ 1, 8-9 (1981)). Consideration of the elements in combination is particularly important, because even if an additional element does not amount to significantly more on its own, it can still amount to significantly more when considered in combination with the other elements of the claim. See, e.g., Rapid Litig. Mgmt. v. CellzDirect, 827 F.3d 1042, 1051, 119 USPQ2d 1370, 1375 (Fed. Cir. 2016) (process reciting combination of individually well-known freezing and thawing steps was "far from routine and conventional" and thus eligible); BASCOM Global Internet Servs. v. AT&T Mobility LLC, 827 F.3d 1341, 1350, 119 USPQ2d 1236, 1242 (Fed. Cir. 2016) (inventive concept may be found in the non-conventional and non-generic arrangement of components that are individually well-known and conventional).
Limitations that the courts have found not to be enough to qualify as "significantly more" when recited in a claim with a judicial exception include ii. Simply appending well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, e.g., a claim to an abstract idea requiring no more than a generic computer to perform generic computer functions that are well-understood, routine and conventional activities previously known to the industry, as discussed in Alice Corp., 573 U.S. at 225, 110 USPQ2d at 1984 (see MPEP § 2106.05(d)); and Generally linking the use of the judicial exception to a particular technological environment or field of use, e.g., a claim describing how the abstract idea of hedging could be used in the commodities and energy markets, as discussed in Bilski v. Kappos, 561 U.S. 593, 595, 95 USPQ2d 1001, 1010 (2010) or a claim limiting the use of a mathematical formula to the petrochemical and oil-refining fields, as discussed in Parker v. Flook, 437 U.S. 584, 588-90, 198 USPQ 193, 197-98 (1978) (MPEP § 2106.05(h)).
It is important to note that in order for a method claim to improve computer functionality, the broadest reasonable interpretation of the claim must be limited to computer implementation. That is, a claim whose entire scope can be performed mentally, cannot be said to improve computer technology. Synopsys, Inc. v. Mentor Graphics Corp., 839 F.3d 1138, 120 USPQ2d 1473 (Fed. Cir. 2016) (a method of translating a logic circuit into a hardware component description of a logic circuit was found to be ineligible because the method did not employ a computer and a skilled artisan could perform all the steps mentally). Similarly, a claimed process covering embodiments that can be performed on a computer, as well as embodiments that can be practiced verbally or with a telephone, cannot improve computer technology. See RecogniCorp, LLC v. Nintendo Co., 855 F.3d 1322, 1328, 122 USPQ2d 1377, 1381 (Fed. Cir. 2017) (process for encoding/decoding facial data using image codes assigned to particular facial features held ineligible because the process did not require a computer).
Examples that the courts have indicated may not be sufficient to show an improvement in computer-functionality: ii. Accelerating a process of analyzing audit log data when the increased speed comes solely from the capabilities of a general-purpose computer, FairWarning IP, LLC v. Iatric Sys., 839 F.3d 1089, 1095, 120 USPQ2d 1293, 1296 (Fed. Cir. 2016), iii. Mere automation of manual processes, such as using a generic computer to process an application for financing a purchase, Credit Acceptance Corp. v. Westlake Services, 859 F.3d 1044, 1055, 123 USPQ2d 1100, 1108-09 (Fed. Cir. 2017) or speeding up a loan-application process by enabling borrowers to avoid physically going to or calling each lender and filling out a loan application, LendingTree, LLC v. Zillow, Inc., 656 Fed. App'x 991, 996-97 (Fed. Cir. 2016) (non-precedential); vii. Providing historical usage information to users while they are inputting data, in order to improve the quality and organization of information added to a database, because "an improvement to the information stored by a database is not equivalent to an improvement in the database’s functionality," BSG Tech LLC v. Buyseasons, Inc., 899 F.3d 1281, 1287-88, 127 USPQ2d 1688, 1693-94 (Fed. Cir. 2018).
To show that the involvement of a computer assists in improving the technology, the claims must recite the details regarding how a computer aids the method, the extent to which the computer aids the method, or the significance of a computer to the performance of the method. Merely adding generic computer components to perform the method is not sufficient. Thus, the claim must include more than mere instructions to perform the method on a generic component or machinery to qualify as an improvement to an existing technology. See MPEP § 2106.05(f) for more information about mere instructions to apply an exception.
Examples that the courts have indicated may not be sufficient to show an improvement to technology include: i. A commonplace business method being applied on a general purpose computer, Alice Corp., 573 U.S. at 223, 110 USPQ2d at 1976; Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015).
Like Alice and Versata Dev. Group, Inc., the claimed invention is implementing the common business method of real estate transactions and financing of real estate transaction on general purpose computers.
The claims stand rejected.
103 Rejection
Applicant’s arguments with respect to claim(s) under 35 USC 103 have been considered but the rejection has been updated to reflect the submitted amendments. The claims stand rejected.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MICHAEL C YOUNG whose telephone number is (571)272-1882. The examiner can normally be reached M-F: 7:00 p.m.- 3:00 p.m. EST.
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/Michael Young/ Examiner, Art Unit 3626
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