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1. 发明申请

WO2022256460A1 SYSTEMS FOR RAPID ACCURATE COMPLETE DETAILING AND COST ESTIMATION FOR BUILDING CONSTRUCTION FROM 2D PLANS 审中-公开
公开(公告)号：WO2022256460A1
公开(公告)日：2022-12-08
申请号：PCT/US2022/031847
申请日：2022-06-01
申请人： BUILDINGESTIMATES.COM LIMITED , ALTMAN, Daniel, E.
发明人： POWLES, Benjamin, John , THOMAS, Stephen, James , MIRPURU, Shaveer, Rajan
IPC分类号： G06Q10/06 , G06Q50/08 , G06N20/00 , G06N3/08 , G06T7/136 , G06V30/262
摘要： A structural building design system for processing, interpreting and analysing holistically a multipage set of two-dimensional (2D) real-world building construction plans for a building and yielding near real time accurate material type, quantity, and specification outputs as required for construction of a compliant building from said plans, through computationally generating a mathematical feature vector space dataset, the system comprising: one or more processors configured to: receive a two-dimensional real-world architectural plan for construction of a structural building, wherein the two-dimensional real-world architectural plan includes objects comprising: architectural symbols, lines, shading, or text; perform pre-processing, of characteristics on or associated with the objects on the two dimensional real-world architectural plan on a pixel by pixel basis for measurement or adjacent multi-pixel basis for object detection, wherein the pre-processing comprises two or more of: object detection and recognition, semantic segmentation, or text recognition to identify a plurality of objects, on the two dimensional real-world architectural plan to identify the characteristic features thereof; computationally transforming at least one characteristic feature of known (learned) and unknown (unlearned) detected objects into a mathematical representation thereof to form part of a future vector space dataset; and wherein said transformations for learned and unlearned detected objects have both high level and low level classifications of identified characteristic features; performing a comparison of the future feature vector space dataset for the identified detected objects to confirm the detected objects meet a predetermined confidence threshold for the classification of each detected object; performing a correlation analysis of the characteristic features for detected objects meeting the pre-determined confidence threshold level, wherein the comparison and correlation analyses above include one or more of determining shape, position, adjacent objects and using said pre -processing and results of correlation analysis of the feature vector space dataset via the algorithms to provide output information regarding the 2D plan including producing autonomous, and highly accurate creation of at least one or more of the following outputs: near real time accurate building takeoffs; complete construction estimates; complete construction detailing; detailed bill of materials for the construction of the building; or a document summarizing differences or similarities between building plans.

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