{"id":158576,"date":"2026-01-22T12:40:26","date_gmt":"2026-01-22T12:40:26","guid":{"rendered":"https:\/\/www.pbctoday.co.uk\/news\/?p=158576"},"modified":"2026-01-22T13:16:01","modified_gmt":"2026-01-22T13:16:01","slug":"ai-lidar-transform-scaffolding-safety-new-era-construction-site-management","status":"publish","type":"post","link":"https:\/\/www.pbctoday.co.uk\/news\/digital-construction-news\/construction-technology-news\/ai-lidar-transform-scaffolding-safety-new-era-construction-site-management\/158576\/","title":{"rendered":"Study highlights the role of AI and LiDAR in advancing scaffolding safety"},"content":{"rendered":"

Advances in cloud-based artificial intelligence are introducing new approaches to scaffolding safety inspection and compliance within construction site management<\/h2>\n

In construction, few structures are as ubiquitous \u2013 and as potentially hazardous \u2013 as scaffolding. Despite decades of regulation and improved training, scaffolding-related accidents remain one of the leading causes of workplace injuries<\/a> and fatalities. The problem is not the technology of scaffolding itself but the way it\u2019s monitored.<\/p>\n

Most inspections are still carried out manually through visual checks, relying heavily on human judgement and experience. On large or complex sites, this can be inconsistent, time-consuming and prone to error.<\/p>\n

Now, a new research-led solution from Lule\u00e5 University of Technology in Sweden promises to change that dynamic. The study, Safety Assessment of Scaffolding on Construction Site Using AI<\/a>, proposes a cloud-based artificial intelligence (AI) system that automates scaffolding inspections using LiDAR scanning<\/a> and digital twin technology, delivering faster, safer, and more accurate safety assessments.<\/p>\n

From manual checks to digital intelligence<\/h3>\n

According to the research team \u2013 Sameer Prabhu, Amit Patwardhan and Ramin Karim\u2013traditional visual inspections are inherently limited. As construction progresses, scaffolding is often modified to accommodate access needs or shifting site conditions. Missing braces, non-compliant alterations, or structural deformations can easily go unnoticed until it\u2019s too late.<\/p>\n

Their proposed AI-powered inspection platform transforms this process into a proactive, data-driven safety system. By integrating LiDAR point cloud data, cloud computing, and graph-based analysis, the system continuously monitors scaffolding against its certified design model.<\/p>\n

As shown in Figure 1, the workflow begins with an initial certified scan when the scaffolding is first erected. This digital model becomes the benchmark, or \u201creference twin,\u201d against which all subsequent scans are compared. Periodic site scans \u2013 captured via drones, stationary sensors, or even robotic dogs \u2013 are uploaded to the cloud, where the AI automatically detects any deviations or missing elements.<\/p>\n

If a potential safety concern is identified, an alert is instantly sent to the site manager\u2019s dashboard.<\/p>\n

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Figure 1 \u2013 This flow diagram visualises how the AI-driven process automates inspections\u2014from routine LiDAR scanning and data acquisition through to structural health monitoring and safety alerts for site managers.<\/figcaption><\/figure>\n

Inside the cloud: Where AI meets construction<\/h3>\n

At the heart of the system is a cloud-based analytics platform that processes and interprets 3D point cloud data from the site. As detailed in Figure 2, the platform\u2019s architecture is divided into three core stages:<\/p>\n