# Simplified Scan-vs-BIM Frameworks for Automated Structural Inspection of Steel Structures
## 2 Literature Review  
### Scan-vs-BIM in Construction  
Within the architectural, engineering, and construction (AEC) industry, traditional integrity evaluation methodologies are predominantly manual-based. These approaches rely heavily on subjective estimation, observational skills, and the expertise of professional workers, rendering them prone to incomplete and inaccurate reporting [2]. Such reliance on human judgment introduces variability and inconsistencies in the assessment process. To address these limitations, substantial research efforts are underway to develop efficient and objective integrity assessment methods. Among these, three-dimensional (3D) laser scanning has been proposed as a powerful tool for integrity evaluation due to its ability to accurately capture the As-Built state in three dimensions [5]. The 3D laser scanning technique is one of the major computer vision technologies that has been used since the 1990s [16]. It has the advantage of providing fast, accurate, comprehensive, and detailed 3D data about the scanned scene. It can capture a scene accurately in millimeters, and the captured information is saved as a 3D point cloud model that is typically called an As-Built scene. The collected 3D point cloud can be used to create an As-Built 3D Computer-Aided Design (CAD) model that can be applied to building design, reconstruction projects, tracking of project progress, and quality control [9]. Despite its numerous advantages, 3D laser scanning is not without its limitations. One of the primary challenges associated with this technology is the time required to perform each scan, particularly in complex environments where multiple scans from different vantage points are needed to achieve adequate resolution and minimize physical obstructions between the scanner and the target object [17]. The variability inherent in construction environments, coupled with the ambiguity surrounding the standards for optimal scanning results, poses significant challenges for practitioners seeking to adopt 3D laser scanning as a standard evaluation practice. In recognition of these challenges, the US General Services Administration (GSA) has developed guidelines for procuring and evaluating 3D imaging services, with the objective of clearly defining acceptable margins of error for 3D scan data [18]. The GSA's deliverable selection matrix, illustrated in Table 1, classifies the Level of Detail (LOD) into four levels. At Level 1, the tolerance for the collected data is \(\pm\)51 mm, whereas at Level 4--the most detailed level--the permissible tolerance is reduced to \(\pm\)3 mm. These classifications serve as benchmarks for establishing acceptable error ranges and ensuring consistency in the quality of 3D scan data used for construction integrity evaluations. Three-dimensional laser scanning has become an essential tool for a range of construction activities, including surveying, earthmoving, monitoring concrete casting progress, highway alignment, paving operations, and construction quality control [4]. It has emerged as a highly prevalent data collection technique for integrity evaluation and is extensively utilized in the reconstruction of As-Built data and in performing \"As-Planned-As-Built Comparisons\" [5]. This technology offers a detailed and accurate representation of physical environments, thereby facilitating more reliable evaluations of construction processes and outcomes. [PERSON] and [PERSON] [19] proposed a method for automated detection, recognition, and identification of objects in laser-scanned point cloud data by leveraging prior information from 3D CAD/BIM models. This concept was defined as \"Scan-vs-BIM\". The data used for detection are the range point clouds obtained from laser scans, representing the As-Built environment of construction sites. The prior information consists of the detailed 3D CAD models of the objects as designed (As-Planned).