Automated Imaging System for Crane Hoisting Collision Avoidance
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Solution Overview
Problem
Current construction practices face challenges in accurately and automatically identifying building material objects at the shakeout field, determining their specifications, and preventing collisions during the hoisting process.
Innovation Solution
An imaging system that automatically images building material objects, processes the images to decipher identifying indicia, measures geometric properties, and compares them with database specifications, while also providing a visual representation of the shakeout field and hoisting path to assist the crane operator.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual identification methods are used for building material objects, then the system complexity is low, but the identification accuracy and productivity are reduced
Solution Approach 1:
The patent replaces manual identification methods with an automated imaging system that uses computer vision and image processing algorithms to automatically capture, process, and analyze images of building material objects, thereby improving identification accuracy while reducing reliance on human operators
Solution Approach 2:
The system creates digital copies (images) of building material objects and their identifying indicia, then processes these copies through automated algorithms to extract identification information, eliminating the need for direct manual reading and comparison
2Productivity
If automated imaging system is implemented, then the productivity is improved, but the device complexity increases
Solution Approach 1:
The imaging system captures images of building material objects and their identifying indicia in advance before the hoisting process, allowing for automated comparison and verification to be performed beforehand, which streamlines the subsequent hoisting operations and improves overall productivity
Solution Approach 2:
The system provides automated feedback by comparing the captured identifying indicia with the lifting list information, enabling real-time verification and correction of identification errors, which enhances the efficiency and accuracy of the hoisting process
3Reliability
If visual inspection is used to prevent collisions, then the equipment cost is low, but the reliability of collision prevention is reduced
Solution Approach 1:
The patent replaces visual inspection with an automated imaging and image processing system that objectively analyzes the positions and trajectories of building material objects, providing more reliable collision detection and prevention capabilities
Solution Approach 2:
The system introduces an intermediary automated analysis layer between the physical hoisting operations and collision detection, using processed image data to identify potential collision risks before they occur, thereby enhancing safety reliability
Data Source
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.