## 1 Introduction
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**No.** & **Year** & **Authors(s)** & **Research Content** & **Research Findings** & **Literatures** \\ \hline
19 & 2021 & [PERSON] et al. & Presented a reconstitution method for assessing tunnel spatiotemporal deformation using 3D laser scanning, focusing on stability warming mechanisms. & The findings contributed to the understanding of tunnel behavior over time, offering a framework for preventive maintenance and timely interventions based on deformation monitoring. & The research demonstrated improved reconstruction accuracy for tunnel geometries, facilitating better assessments of tunnel integrity and supporting more informed engineering decisions. & [21] \\
20 & 2022 & [PERSON] et al. & Proposed a RANSAC-based method for multi-primitive building reconstruction from 3D point clouds, targeting tunnel structures for better geometric accuracy. & The research demonstrated improved reconstruction accuracy for tunnel geometries, facilitating better assessments of tunnel integrity and supporting more informed engineering decisions. & This study enhanced the efficiency of processing large-scale 3D point cloud data, allowing for quicker and more reliable evaluations of tunnel conditions post-blasting. & [22] \\
21 & 2022 & [PERSON] et al. & Developed an efficient plane extraction technique using RANSAC and normal estimation for processing 3D point clouds, aimed at tunnel applications. & This study enhanced the efficiency of processing large-scale 3D point cloud data, allowing for quicker and more reliable evaluations of tunnel conditions post-blasting. & [23] \\
22 & 2023 & [PERSON] et al. & Introduced a central axis elevation extraction method for metro shield tunnels based on 3D laser scanning technology, enhancing structural monitoring. & The method improved the assessments and provided a basis for ongoing maintenance strategies, ensuring safer operations within tunnel environments. & [24] \\
23 & 2023 & [PERSON] et al. & Developed a semi-supervised learning-based point cloud network for segmenting 3D tunnel scenes, aimed at enhancing automation in tunnel inspections. & This innovative approach significantly improved the speed and accuracy of tunnel inspections, facilitating better maintenance practices and ensuring compliance with safety standards. & [25] \\
24 & 2023 & [PERSON] et al. & Proposed a novel SfM-DLT method for metro tunnel 3D reconstruction, integrating different data sources for comprehensive visualization. & The research contributed to more detailed and accurate visualizations of tunnel environments, aiding in both operational planning and risk assessment during construction phases. & [26] \\
25 & 2024 & [PERSON] et al. & Developed a framework for integrating 3D point cloud data with traditional survey methods to enhance tunnel blasting evaluation processes. & This integration enhanced the overall accuracy of blasting assessments, leading to improved operational efficiency and safety in tunnel construction projects. & [27] \\
26 & 2024 & [PERSON] et al. & Investigated the impact of rock mass characteristics on the effectiveness of blasting in tunnels, focusing on data-driven approaches to optimize blasting outcomes. & The study emphasized the importance of understanding geological factors in blasting design, leading to more efficient and safer blasting practices in tunnel construction. & [28] \\ \hline \hline \end{tabular}
\end{table} 
Table 1: _Cont._Building on this foundation, our research aims to achieve two primary objectives. First, we conduct a comprehensive review of current methodologies in tunnel blasting evaluation, with particular emphasis on the advances in 3D reconstruction technologies and their applications [29]. Second, we introduce and validate an innovative approach for assessing half porosity by adapting established algorithms from other fields--namely, Structure-from-Motion (SfM), Scale-Invariant Feature Transform (SIFT), and Random Sample Consensus (RANSAC)--for the specific challenges encountered in tunnel blasting contexts.