Building Material Object Imaging for Crane Placement Accuracy

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Solution Overview

Problem

Current construction practices face challenges in accurately identifying and positioning building material objects at construction sites due to human error in interpreting handwritten indicia, misidentification of objects, and manufacturing errors, leading to inefficiencies and potential collisions during the steel erection process.

Innovation Solution

An imaging system equipped with machine learning algorithms and geometric property measurement capabilities is used to automatically identify and verify the specifications of building material objects, providing real-time guidance to crane operators through a 3D representation and collision avoidance to ensure correct placement.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of operation

If handwritten indicia are used to identify building material objects, then the identification process is simple and quick, but human error in interpreting these indicia leads to misidentification and placement errors

Engineering Contradiction:

Improveidentification processVSAvoididentification accuracy

Core Design Contradiction:

Ease of operationVSReliability

Solution Approach 1:

The patent replaces the manual visual interpretation of handwritten indicia with an automated imaging system that captures images of building material objects and uses machine learning algorithms to identify and verify their specifications. This substitution eliminates human error in reading handwritten markings while maintaining the simplicity of the identification process.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system creates a digital copy (image) of the building material object and its handwritten indicia, then processes this copy through machine learning algorithms to extract identification information. This allows verification against the lifting list without requiring human operators to directly interpret the handwritten markings.

Inventive Principle:

Principle #26Copying

2Reliability

If automated imaging systems with machine learning are implemented, then identification accuracy is improved, but system complexity and cost increase

Engineering Contradiction:

Improveidentification accuracyVSAvoidsystem complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The imaging system is designed to perform multiple functions: capturing images of building material objects, identifying them through machine learning, verifying specifications against the lifting list, and providing real-time guidance to crane operators. This multi-functionality consolidates several separate systems into one, reducing overall complexity despite the advanced capabilities.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Solution Approach 2:

The machine learning model is trained to autonomously identify building material objects and verify their specifications without requiring human intervention. The system self-corrects for perspective distortion and automatically compares captured images against the lifting list, reducing the need for complex human-in-the-loop verification processes.

Inventive Principle:

Principle #25Self-service

3Device complexity

If manual identification and verification processes are used, then system complexity is low, but time is lost due to misidentification and remanufacturing errors

Engineering Contradiction:

Improvesystem complexityVSAvoiddowntime

Core Design Contradiction:

Device complexityVSLoss of time

Solution Approach 1:

The system performs identification and verification of building material objects before they are hoisted and placed. By capturing images and verifying specifications in advance, the system prevents misidentification errors from occurring during the hoisting process, eliminating the need to return incorrectly identified objects for remanufacturing or re-identification.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system provides real-time feedback to crane operators through a display device, showing whether the identified building material object matches the expected object from the lifting list. This immediate feedback allows operators to correct any identification issues before hoisting, preventing time losses from errors discovered after placement.

Inventive Principle:

Principle #23Feedback

4Measurement precision

If real-time imaging and verification is implemented, then placement accuracy is improved, but energy consumption and operational complexity increase

Engineering Contradiction:

Improveplacement accuracyVSAvoidenergy consumption

Core Design Contradiction:

Measurement precisionVSUse of energy by moving object

Solution Approach 1:

The imaging system captures images at periodic intervals during the hoisting process rather than continuously, reducing energy consumption while maintaining sufficient measurement precision for accurate placement verification at critical stages.

Inventive Principle:

Principle #19Periodic action

Data Source

PatentUS20250270075A1Systems and methods for identifying and locating building material objects

Publication Date: 2025.08.28 STRUCTURAL SERVICES INC

AI summary

Based upon the identification of a structural member, a projective path and final attachment location for the structural member is presented to the crane operator. Further, the dimensions of each structural member are determined and compared against a construction site database. Structural members not conforming to the dimensions listed in the construction site database are identified and the crane operator alerted.