用AI分析脚手架点云数据，自动识别结构异常，提升工地安全
Safety Assessment of Scaffolding on Construction Site using AI
- 基于云端AI平台对比最新点云与标准设计数据，检测脚手架改动
- 实现自动化检测，减少人工巡检时间和误判风险
- 适合建筑安全管理、智能巡检系统研发人员参考
在建筑行业，安全评估对保障资产可靠性和工人安全至关重要。脚手架作为关键结构支撑，需定期检查以发现偏离设计规范的变更，避免影响整体稳定。当前主要依赖现场管理人员或持证人员进行视觉检查，但该方法耗时且易受人为因素影响，可能导致安全隐患。本文探讨利用人工智能（AI）与数字化技术提升脚手架检查的准确性，增强工地安全。开发了一套基于云的AI平台，用于处理和分析脚手架的点云数据。系统通过比对经认证的参考数据与近期采集的点云数据，实现对结构变化的自动检测。该方法可支持脚手架的自动化监控，在降低人工巡检时间与工作量的同时，显著提升施工现场的安全水平。
原文摘要 · Abstract (English)
In the construction industry, safety assessment is vital to ensure both the reliability of assets and the safety of workers. Scaffolding, a key structural support asset requires regular inspection to detect and identify alterations from the design rules that may compromise the integrity and stability. At present, inspections are primarily visual and are conducted by site manager or accredited personnel to identify deviations. However, visual inspection is time-intensive and can be susceptible to human errors, which can lead to unsafe conditions. This paper explores the use of Artificial Intelligence (AI) and digitization to enhance the accuracy of scaffolding inspection and contribute to the safety improvement. A cloud-based AI platform is developed to process and analyse the point cloud data of scaffolding structure. The proposed system detects structural modifications through comparison and evaluation of certified reference data with the recent point cloud data. This approach may enable automated monitoring of scaffolding, reducing the time and effort required for manual inspections while enhancing the safety on a construction site.
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