Safety Assessment of Scaffolding on Construction Site using AI
Prabhu, Sameer, Patwardhan, Amit, Karim, Ramin
–arXiv.org Artificial Intelligence
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.
arXiv.org Artificial Intelligence
Sep-29-2025
- Country:
- Europe
- Sweden > Norrbotten County
- Luleå (0.04)
- Switzerland (0.04)
- Sweden > Norrbotten County
- Europe
- Genre:
- Research Report (0.64)
- Workflow (0.46)
- Industry:
- Construction & Engineering (0.69)
- Health & Medicine (0.46)
- Information Technology > Services (0.34)
- Technology:
- Information Technology
- Artificial Intelligence
- Applied AI (0.84)
- Machine Learning > Neural Networks
- Deep Learning (0.94)
- Representation & Reasoning (1.00)
- Vision (1.00)
- Data Science > Data Mining (1.00)
- Sensing and Signal Processing > Image Processing (1.00)
- Artificial Intelligence
- Information Technology