Building Material Verification With Imaging-Guided Crane Hoisting
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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 interpretation errors of handwritten indicia, misidentification of objects, and manufacturing defects, leading to inefficiencies and potential collisions during hoisting.
Innovation Solution
An imaging system equipped with machine learning algorithms and inertial navigation is used to automatically identify and measure building material objects, compare specifications with a construction site database, and provide real-time guidance to crane operators to ensure correct placement and avoid collisions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If handwritten indicia are used to identify building material objects, then the identification process is simple and low-cost, but human interpretation errors occur leading to misidentification
Solution Approach 1:
The patent replaces the manual visual interpretation of handwritten indicia with an automated imaging system using machine learning algorithms. The system captures images of building material objects, automatically reads and interprets the indicia, and identifies objects without human intervention, thereby eliminating interpretation errors while maintaining the simplicity of handwritten labeling.
2Reliability
If automated imaging systems with machine learning are deployed, then identification accuracy is improved, but system complexity and cost increase
Solution Approach 1:
The patent introduces an intermediary imaging system that acts as a bridge between the simple handwritten indicia and the complex machine learning algorithms. The imaging system captures images and pre-processes them, making the data more accessible to the machine learning model while shielding users from the underlying complexity of the automated recognition system.
3Object-affected harmful factors
If real-time verification is performed during hoisting, then collision risks are reduced, but processing time and operational delays increase
Solution Approach 1:
The patent performs verification actions in advance by capturing images of building material objects before hoisting and processing them through the imaging system. The system pre-identifies objects and verifies their positions, so that when hoisting begins, the verification is already complete or near-complete, minimizing real-time delays while maintaining collision prevention.
Data Source
AI summary
The present disclosure presents systems and methods for assisting a crane operator. An imaging system automatically images each building material object contained within a shakeout field on a construction site and processes the images to determine each object's identifying indicium and its geometric properties. These values are compared with a construction site database to ensure that all necessary building materials are present. A positioning device tracks, in real time, the location of the imaging system, the location of structural members within the shakeout field, and/or other important features of the job site, such as obstacles that the crane operator will need to avoid while lifting a structural member from its initial location to its destination location. Real-time images of the construction site, including indications of the next building material object to be hoisted and/or a path between the object's initial and final locations, can be generated to guarantee that the crane operator hoists the expected object to the expected location.