2D Drawing Alignment for Automated Construction Clash Detection

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Solution Overview

Problem

Construction projects face challenges in identifying and resolving object clashes in two-dimensional drawings, which are time-consuming, cumbersome, and prone to human error, leading to potential construction delays and cost overruns.

Innovation Solution

A software technology for automated clash detection in two-dimensional drawings that aligns and analyzes multiple drawings to identify object clashes, using image processing and machine learning to automate the clash detection process.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If manual review of construction drawings is performed to identify object clashes, then detection capability is achieved, but time consumption and human error increase

Engineering Contradiction:

Improveclash detection accuracyVSAvoidtime for clash detection

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The patent replaces the manual mechanical review process with an automated computer-based system that uses image processing and machine learning algorithms to detect clashes in construction drawings, eliminating human labor while maintaining or improving detection accuracy

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system enables self-service clash detection by automatically analyzing drawings without requiring human intervention for the detection process itself, with the computer system performing all analysis functions autonomously

Inventive Principle:

Principle #25Self-service

2Reliability

If multiple two-dimensional drawings are manually aligned and analyzed for clash detection, then comprehensive clash identification is achieved, but process complexity and effort increase

Engineering Contradiction:

Improveclash detection completenessVSAvoidcomplexity of clash detection process

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The patent merges multiple drawing analysis functions into a single integrated automated system that simultaneously processes multiple two-dimensional drawings, aligns them, and detects clashes across all drawings in one unified operation

Inventive Principle:

Principle #5Merging (Combining)

Solution Approach 2:

The automated system performs multiple functions including drawing alignment, object identification, and clash detection within a single platform, eliminating the need for separate manual processes for each function

Inventive Principle:

Principle #6Universality (Multi-functionality)

3Productivity

If automated clash detection is implemented, then productivity and accuracy improve, but technological complexity increases

Engineering Contradiction:

Improveclash detection efficiencyVSAvoidcomplexity of detection system

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The patent replaces complex manual analysis processes with automated computer-based image processing and machine learning systems, which handle the technological complexity internally while presenting a simplified interface to users

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS20250245799A1Automated Clash Detection Using Two-Dimensional Drawings

Publication Date: 2025.07.31 PROCORE TECHNOLOGIES INC

AI summary

Techniques for performing an automated clash detection analysis on two-dimensional (2D) drawings associated with a given location of a construction project involve obtaining a set of 2D drawings for a construction project and identifying a subset of the 2D drawings that are associated with the given location of the construction project. From the subset of 2D drawings, a first 2D drawing and a second 2D drawing are selected for inclusion in the automated clash detection analysis. Based on respective sets of key points, the first and second 2D drawings are aligned and layered to produce an overlaid view. Objects in each 2D drawing are identified, and the overlaid view is analyzed to identify clashes between objects in the first 2D drawing and objects in the second 2D drawing. Respective visual representations of identified clashes may be displayed for user interaction.