Building construction site safety analysis system and method based on artificial intelligence

Through the building construction site safety analysis system based on artificial intelligence, scaffolding data is collected and analyzed, and the optimal structural layout is generated using optimization algorithms, which solves the problem of insufficient safety on construction sites in the existing technology and achieves an efficient and safe construction environment.

CN119808293AInactive Publication Date: 2025-04-11江苏聚利源机械制造有限公司
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Patent Information

Application Number
CN202411771094.2
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2024-12-04
Publication Date
2025-04-11
Estimated Expiration
Not applicable · inactive patent

AI Technical Summary

Technical Problem

The existing technology is difficult to fully meet the requirements of modern building construction for efficiency and safety at construction sites, especially in the design, construction, management and safety analysis of scaffolding, which has threatened the lives and safety of construction workers.

Method used

An artificial intelligence-based building construction site safety analysis system is adopted. This system collects scaffolding images and basic data, uses a pre-trained recognition model to mark components, and inputs a stability decision model in combination with an offset angle to output stability results. If the result is unstable, the system generates the optimal scaffolding structure layout through an optimization heuristic algorithm and transforms it.

Benefits of technology

It improves the accuracy of scaffolding safety assessment, reduces manual identification errors, timely discovers potential safety hazards, realizes efficient use and safety improvement of scaffolding, and reduces construction risks.

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Abstract

The invention discloses a building construction site safety analysis system and method based on artificial intelligence. The method comprises the steps that scaffold images and scaffold basic data of a construction site are collected; the deviation angle of the scaffold material on the construction site is collected; inputting the scaffold image into a pre-trained recognition model, and outputting scaffold component labeling information; the scaffold component labeling information, the scaffold basic data and the deviation angle are input into a pre-trained stability decision model, and a stability result is output and comprises stability and instability; if the stability result is unstable, optimizing the scaffold structure through an optimization heuristic algorithm based on the set target condition and constraint condition, outputting the optimal scaffold structure layout, and transforming the existing scaffold according to the optimal scaffold structure layout; according to the whole system, through scientific modeling and optimization analysis, the collapse risk of the scaffold is greatly reduced, and the overall safety level of a construction site is improved.
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