DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Election/Restrictions
Applicant’s election without traverse of claims 1-15 in the reply filed on 8/21/2025 is acknowledged.
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 1-15 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claim 1 recites receiving a blueprint dataset for a structure; classifying portions of the blueprint dataset; generating feature datasets for the classified portions of the blueprint dataset based on processing of the classified portions of the blueprint dataset by the one or more models; generating more material pack datasets based on the feature datasets; and causing presentation of a visual representation of the one or more material pack datasets. These limitations involve building project management and relate to using blueprint data to determine the materials needed for the building project, which reasonably falls within the abstract idea grouping of certain methods of organizing human activity, specifically commercial interactions (sales activities or behaviors, business relations).
This judicial exception is not integrated into a practical application. Claim 1 includes the following additional elements: causing presentation, by communications hardware, of a builder project management user interface (UI); by the communications hardware; by classifier circuitry and using a classifier model, by modeling circuitry and using one or more models; digitized data; by a calculation engine; via the builder project management UI. These additional elements, when considered alone and in combination, are claimed at a high level of generality, amounting to no more than mere instructions to implement the recited abstract idea on a computer.
Claim 1 further does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above, causing presentation, by communications hardware, of a builder project management user interface (UI); by the communications hardware; by classifier circuitry and using a classifier model, by modeling circuitry and using one or more models; digitized data; by a calculation engine; via the builder project management UI, when considered alone and in combination, are claimed at a high level of generality, and amount to no more than mere instructions to implement the recited abstract idea on a computer.
With regards to dependent claims 2-15, these claims recite limitations that further narrow the recited abstract idea identified above with respect to claim 1.
For additional elements, claim 2 further includes input analysis circuitry; Claim 7 includes three-dimensional circuitry and a builder project management UI; claims 9 and 10 includes a material calculation engine; claim 11 includes a supplier bid circuitry; claim 12 includes ordering circuitry and a scheduling engine; Claim 13 includes a builder project management UI; claim 14 includes a scheduling engine. When considering the additional elements in each of these claims alone, and in combination with the claims on which they depend, these elements are claimed at a high level of generality, amounting to no more than mere instructions to implement the recited abstract idea on a computer. The claims invoke computers merely as a tool in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data). See MPEP 2106.05(f). This fails to integrate the recited abstract idea into a practical application or provide significantly more.
With regards to claims 3-4, these claims include the additional elements of converting, by the input analysis circuitry, from a first file format to a second file format and the second file is a rasterized filed Considering these additional elements alone, and in combination with the claims on which they depend, they are claimed at a high level of generality with no specificity of how they are performed and are simply invoking a general purpose computer component to a recited abstract idea. For claim 5, the claim includes the additional elements of modeling circuitry and retraining. Considering these additional elements alone, and in combination with the claims on which they depend, they are claimed at a high level of generality with no specificity of how they are performed and are simply invoking a general-purpose computer component to a recited abstract idea. Further, retraining is recited only as an idea of a solution or outcome without details of how a solution to a problem is accomplished. See MPEP 2106.05(f). Therefore, the additional elements of claims 3-5, when considered alone and in combination, fail to integrate the recited abstract idea into a practical application or provide significantly more.
The claims are ineligible.
.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-9 are rejected under 35 U.S.C. 103 as being unpatentable over Fink et al. (US 2024/0111927) in view of Cantwell et al. (WO 2021/174060).
As per claim 1, Fink et al. teaches a method comprising:
causing presentation, by communications hardware, of a builder project management user interface (UI) (See paragraphs 37, 56, 92, where a user interface is presented. See also figures 2 and 9);
receiving, by the communications hardware, a blueprint dataset for a structure (See at least paragraphs 22, 29, and 40, where blueprint information for a structure is received);
classifying, by classifier circuitry and using a classifier model, portions of the blueprint dataset (See at least paragraphs 28, 31, 33, 45, 66, where blueprints are provided to a machine learning model such as a neural network where information is extracted and classified);
generating, by modeling circuitry and using one or more models, digitized feature datasets for the classified portions of the blueprint dataset based on processing of the classified portions of the blueprint dataset by the one or more models (See at least paragraphs 28, 31, 33, 41, 52, and 60, where information and blueprint data is digitized);
compiling, by an engine and based on the digitized feature datasets, one or more material pack datasets (See paragraphs 27, 95-96, and 104, where data representing materials needed for building a portion of a structure are compiled from the information and shown as an inventory list on a screen);
causing presentation, by the communications hardware, of a visual representation of the one or more material pack datasets via the builder project management UI (See at least paragraphs 27, 30, 95-96, and 104, where data representing materials needed for building a portion of a structure are compiled from the information and shown as an inventory list on a screen).
Fink et al. teaches compiling, based on the digitized feature datasets, one or more material pack datasets using vendor specifications and information that includes any information that is relevant to the structure being constructed, pursuant to blueprints, such as inventory lists of various supplies, and building materials (See paragraph 30). However, Fink et al. does not explicitly generate the one or more material pack datasets by a material calculation engine.
Cantwell specifically discloses generating the one or more material pack datasets by a material calculation engine (See paragraphs 98-104, with emphasis on paragraphs 101-103. A material takeoff is generated using the computer, that includes quantities and a materials list).
Both Fink et al. and Cantwell et al. are concerned with converting and extracting information from images in the construction space. Fink et al. extracts and compiles information about materials needed as an inventory list. Cantwell et al. specifically discusses generating a materials pack using the computer system. It would have been obvious before the effective filing date of the invention to include the specifics of generating the materials pack from Cantwell et al. in the system of Fink et al. in order to more efficiently and effectively generate material takeoffs with lists of materials that are more accurate and reflect adjustments. See paragraphs 101-103 of Cantwell et al.
Per claim 2, Fink et al. teaches the method of claim 1, further comprising:
pre-processing, by input analysis circuitry, the blueprint dataset prior to classifying the portions of the blueprint dataset (See at least paragraphs 31, 43, 46, 67, and 79 which process the file type of the blueprints).
Per claim 3, Fink et al. teaches the method of claim 2, wherein pre-processing the blueprint dataset comprises:
converting, by the input analysis circuitry, the blueprint dataset from a first file format to a second file format (See at least paragraphs 31, 43, 46, 67, and 79 which process the file type of the blueprints).
Per claim 4, Fink et al. teaches the second file format comprises a rasterized image file format (See paragraphs 68-69, disclosing a higher resolution image with pixels/elements. All images defined by pixels are considered raster images). While not relied upon, please also see paragraphs 97, 102-103 of Cantwell et al.
Per claim 5, Fink et al. teaches the method of claim 1, further comprising:
receiving, by the communications hardware and prior to generating the one or more material pack datasets, one or more updated digitized feature datasets (See paragraphs 33 and 45, where results are received); and
causing, by the modeling circuitry, re-training of at least one of the one or more models based on the updated digitized feature datasets (See paragraphs 33 and 45, where the results are fed back into the initially trained model to retrain and enhance subsequent classifications),
wherein the one or more material pack datasets are compiled based further on the one or more updated digitized feature datasets (See paragraph 30).
Cantwell specifically discloses generating the one or more material pack datasets by a material calculation engine (See paragraphs 98-104, with emphasis on paragraphs 101-103. A material takeoff is generated using the computer, that includes quantities and a materials list).
Both Fink et al. and Cantwell et al. are concerned with converting and extracting information from images in the construction space. Finks et al. extracts and compiles information about materials needed as an inventory list. Cantwell et al. specifically discusses generating a materials pack using the computer system. It would have been obvious before the effective filing date of the invention to include the specifics of generating the materials pack from Cantwell et al. in the system of Fink et al. in order to more efficiently and effectively generate material takeoffs with lists of materials that are more accurate and reflect adjustments. See paragraphs 101-103 of Cantwell et al.
Per claim 6, Fink et al. teaches the method of claim 5, wherein a respective material pack dataset comprises data representing materials needed for building a portion of the structure associated with a respective digitized feature dataset (See at least paragraphs 27, 30, 95-96, and 104, where data representing materials needed for building a portion of a structure are shown).
Per claim 7, Fink et al. discloses a method of claim 1, further comprising:
generating, by three-dimensional modeling circuitry, a three-dimensional (3D) model of the structure based on the digitized feature datasets (See paragraphs 24, 35, 46, 54, where a #D model is generated from the data extracted from the blueprint); and
causing presentation, by the communications hardware, of the 3D model of the structure via the builder project management UI (See paragraphs 88, 100, and 101, where the 3D model is presenting in the interface. See also figure 6).
As per claim 8, Fink et al. teaches wherein the digitized feature datasets comprise line and measurement data for respective portions of the blueprint dataset (See paragraphs 67, 69-70, 75, 94, wherein data is extracted from the blueprints including scale, line and measurement).
As per claim 9, Fink et al. does not expressly disclose and Cantwell discloses wherein generating the one or more material pack datasets comprises:
determining, by the material calculation engine and using one or more optimized subroutines, an optimal amount of material needed for a respective portion of the structure based on the line and measurement data (See paragraphs 102-104, 106 that discloses techniques for increasing accuracy in amounts through more accurate dimension determination).
Both Fink et al. and Cantwell et al. are concerned with converting and extracting information from images in the construction space. Finks et al. extracts and compiles information about materials needed as an inventory list, and extracts data from blueprints including scale, line and measurement. Cantwell et al. specifically discusses generating a materials pack using the computer system, and further increased accuracy in determining dimensions so that enhanced and context-rich takeoffs can be generated. It would have been obvious before the effective filing date of the invention to include the enhanced and context-rich takeoffs and the more accurate dimensions of Cantwell et al. in the system of Fink et al. in order to increase accuracy and better validate information for quicker, higher quality, and improve services such as to . See paragraphs 104 and 106 of Cantwell et al.
Claims 10-13 are rejected under 35 U.S.C. 103 as being unpatentable over Fink et al. (US 2024/0111927) in view of Cantwell et al. (WO 2021/174060) and in further view of Bradt et al. (WO 01/67346).
As per claim 10, neither Fink et al. nor Cantwell et al. disclose, and Bradt et al. discloses:
assigning, by the material calculation engine and for a respective digitized feature set, a base stock keeping unit (SKU) to each material needed for building a portion of the structure (See page 11, lines 10-12, page 39, lines 20-24, and page 41, lines 23-27, wherein SKU are assigned to materials. See also figure 25); and
mapping, by the material calculation engine, the base SKU to one or more supplier SKUs based on a user preference set (See page 11, lines 10-12, page 39, lines 20-24, page 40, lines 5-11 and 17-27, and page 41, lines 23-27, where the supplier has the power to manage its product catalog including details such as the stock keeping units (SKU) and the ability to set preferred pricing per customer based upon volume or other factors. Availability is able to be determined and price can be set or varied based upon particularly agreements or arrangements with certain builders or similar customers).
Both Fink et al. and Cantwell et al. are concerned with converting and extracting information from images in the construction space. Bradt et al. also discloses homebuilders and construction, and the use of floor plans / construction documents to determine materials that will be used in construction. It would have been obvious to one of ordinary skill in the art before the effective filing date to include the particulars of Bradt’s ordering and scheduling management systems and interfaces, including the use of SKUs, in the construction management system of Fink et al., which includes purchasing links with vendor information and automatically ordering supplies, in order to allow the user to more efficiently manage orders associated with the construction project. See for example abstract and page 11 of Bradt et al.
As per claim 11, Fink et al. teaches the method of claim 1, further comprising: Providing purchasing links with vendor information to allow for automated ordering and quick access to construction plans, inventory lists, and other vendor/contractor specifications or information (See paragraphs 95-96 and 106). Cantwell et al. discloses the concept of price and formatting a bid (see at least paragraphs 97-99).
However, neither reference explicitly discloses and Bradt discloses applying, by supplier bid circuitry, pricing information to the one or more material pack datasets based on supplier inventory data (See page 11, lines 1-12, page 40, lines 5-11 and 17-27, where the supplier has the power to manage its product catalog including details such as the stock keeping units (SKU) and the ability to set preferred pricing per customer based upon volume or other factors. Availability is able to be determined and price can be set or varied based upon particularly agreements or arrangements with certain builders or similar customers).
Both Fink et al. and Cantwell et al. are concerned with converting and extracting information from images in the construction space. Bradt et al. also discloses homebuilders and construction, and the use of floor plans / construction documents to determine materials that will be used in construction. It would have been obvious to one of ordinary skill in the art before the effective filing date to include the particulars of Bradt’s ordering and scheduling management systems and interfaces, including the use of pricing information from the supplier, in the construction management system of Fink et al., which includes purchasing links with vendor information and automatically ordering supplies, in order to allow the user to more efficiently manage orders associated with the construction project. See for example abstract and page 11 of Bradt et al.
As per claim 12, Fink et al. teaches the method of claim 11, further comprising providing purchasing links with vendor information and automatically ordering supplies based on status information (See paragraphs 95-96 and 106). However, neither Fink et al. nor Cantwell et al. disclose, and Bradt et al. discloses:
receiving, by the communications hardware, a user order indication of at least one material pack dataset via the builder project management UI, wherein the user order indication comprises a requested delivery date (see figure 23, page 37, line 25-page 38, line 4, wherein an order is received in the system);
executing, by ordering circuitry, an order of materials associated with the at least one material pack dataset (See page 37, lines 13-24);
scheduling, by a scheduling engine, a delivery of the order of materials based at least on the requested delivery date (See abstract; figure 23, page 38, lines 5-10, where information includes requested delivery);
causing presentation, by the communications hardware, of a visual representation of an order status for the at least one material pack dataset. (Figures 24 and 25, page 38, lines 12-20 and line 28-page 39, line 5, where and order detail page is presented including an order status).
Both Fink et al. and Cantwell et al. are concerned with converting and extracting information from images in the construction space. Bradt et al. also discloses homebuilders and construction, and the use of floor plans / construction documents to determine materials that will be used in construction. It would have been obvious to one of ordinary skill in the art before the effective filing date to include the particulars of Bradt’s ordering and scheduling management systems and interfaces, including tracking order status, in the construction management system of Fink et al., which includes purchasing links with vendor information and automatically ordering supplies, in order to allow the user to more efficiently manage orders associated with the construction project. See for example abstract and page 11 of Bradt et al.
As per claim 13, neither Fink et al. nor Cantwell et al. disclose, and Bradt et al. discloses wherein causing presentation of the visual representation of the one or more material pack datasets via the builder project management UI comprises simultaneously displaying order statuses of the one or more material pack datasets within the builder project management UI (See figures 25, 26, 28, where the order status of each material pack is displayed along with what has been ordered and shipped).
Both Fink et al. and Cantwell et al. are concerned with converting and extracting information from images in the construction space. Bradt et al. also discloses homebuilders and construction, and the use of floor plans / construction documents to determine materials that will be used in construction. It would have been obvious to one of ordinary skill in the art before the effective filing date to include the particulars of Bradt’s ordering and scheduling management systems and interfaces, including display of order statuses, in the construction management system of Fink et al., which includes purchasing links with vendor information and automatically ordering supplies, in order to allow the user to more efficiently manage orders associated with the construction project. See for example abstract and page 11 of Bradt et al.
Claims 14-15 are rejected under 35 U.S.C. 103 as being unpatentable over Fink et al. (US 2024/0111927) in view of Cantwell et al. (WO 2021/174060) and Bradt et al. (WO 01/67346) and in further view of Adesh (US 2023/0394400).
As per claim 14, Fink discloses materials associated with one or more material pack datasets based on the blueprint dataset and builder profile information associated with the received blueprint dataset (See paragraphs 27, 95-96, and 104). However, neither Fink et al. nor Cantwell et al. disclose generating, by a scheduling engine, a delivery schedule for materials.
Bradt et al. discloses generating a delivery schedule for materials (See abstract; figure 23, page 38, lines 5-10, where information includes requested delivery) but does not explicitly disclose a generating, by a scheduling engine, a recommended delivery schedule for materials.
Adesh et al. discloses generating, by a scheduling engine, a recommended delivery schedule for materials (See at least abstract, paragraphs 79 and 88, where weather risks impact scheduling recommendations).
Fink et al., Cantwell et al. and Bradt et al. are analogous because they all involve the homebuilding and construction space as well as determining and acquiring needed materials. Bradt et al. specifically includes order management systems and interfaces for managing and scheduling material delivery. Adesh et al. discloses risk and impact to scheduling related to weather. It would have been obvious to one of ordinary skill in the art before the effective filing date to include the scheduling risks, such as weather, of Adesh et al. when scheduling delivery dates in Bradt et al. in order to efficiently complete a series of tasks and manage the workflow and supplies of construction jobs in a cost-effective manner by scheduling tasks and delivery of materials using a variety of job reports. See at least abstract of Bradt et al.
As per claim 15, neither Fink et al. nor Cantwell et al. disclose the recommended delivery schedule is generated based further on one or more parameters, the parameters including: forecasted weather data, regional building practice and code information, calendar event data, supplier restriction data, and builder restriction data.
Bradt et al. discloses generating a delivery schedule for materials (See abstract; figure 23, page 38, lines 5-10, where information includes requested delivery) but does not explicitly disclose a recommended delivery schedule generated based further on one or more parameters, the parameters including: forecasted weather data, regional building practice and code information, calendar event data, supplier restriction data, and builder restriction data.
Adesh et al. discloses , the parameters including: forecasted weather data, (See at least abstract, paragraphs 79 and 88, where weather risks impact scheduling recommendations).
Fink et al., Cantwell et al. and Bradt et al. are analogous because they all involve the homebuilding and construction space as well as determining and acquiring needed materials. Bradt et al. specifically includes order management systems and interfaces for managing and scheduling material delivery. Adesh et al. discloses risk and impact to scheduling related to weather. It would have been obvious to one of ordinary skill in the art before the effective filing date to include the scheduling risks, such as weather, of Adesh et al. when scheduling delivery dates in Bradt et al. in order to efficiently complete a series of tasks and manage the workflow and supplies of construction jobs in a cost-effective manner by scheduling tasks and delivery of materials using a variety of job reports. See at least abstract of Bradt et al.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Jalia (US 2021/0294299) discusses estimating the amounts of construction materials or elements, and calculates the cost.
Yellin et al. (US 2021/0073694) discusses a construction management (CM) system including a takeoff quantifying a material quantity required for a construction project, including measuring items from a set of drawings and a bidding process.
Oaks et al. (US 11,321,500) teaches accessing a 3D file of a building, extracting architectural data, and calculating the amount of a material needed to complete the building.
Kumar et al. (US 2023/0034172) discloses dynamic bill-of-materials generation from architectural models and drawings.
Powles et al. (US 11625553) teaches virtual representations of building structures, utilizing neural networks to recognize and interpret characteristics, and create a bill of materials.
Ogilby et al (US 20170193415) teaches using a classification UI with a construction project, and estimating materials and cost.
Wright et al. (US 2018/0032643) discloses design management system that ingests architectural objects and groups and classifies them.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to BETH V BOSWELL whose telephone number is (571)272-6737. The examiner can normally be reached M-F 8AM - 4:30PM.
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/BETH V BOSWELL/Supervisory Patent Examiner, Art Unit 3625
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