## 3 The State-of-the-Art Review in Tunnel Blasting Evaluation
### Monitoring and Assessment Technologies  
Monitoring and assessment technologies have become essential components in the evaluation of tunnel blasting effects, enabling real-time data collection and analysis of structural integrity. These advancements not only enhance safety but also improve the overall efficiency of tunnel construction and maintenance. Various methodologies have emerged that leverage innovative technologies to monitor tunnel conditions, assess the impact of blasting, and ensure compliance with engineering standards. One of the most significant contributions in this area is the work by [PERSON] et al. (2014), who developed a methodology for monitoring newly constructed circular train tunnels using laser scanning technology. This approach allows for precise tracking of changes in tunnel shape and stability over time, providing valuable data that informs maintenance strategies and enhances safety measures [11]. By employing laser scanning, engineers can detect minute deformations and assess the structural integrity of tunnels, which is critical in identifying potential issues before they escalate. Moreover, the integration of remote sensing data with distinct element analysis has been highlighted by [PERSON] et al. (2021). Their research illustrated the effectiveness of combining these analytical methods to enhance safety assessments in challenging geological conditions [21]. This integration facilitates a comprehensive understanding of the interactions between blasting activities and geological factors, leading to more informed decision-making during tunnel construction and operation. In addition to laser scanning and remote sensing, the utilization of advanced imaging technologies such as 3D reconstruction plays a pivotal role in monitoring tunnel conditions. [PERSON] et al. (2020) proposed a method for detecting over and underdigging of tunnels using 3D reconstruction from images, specifically applying Structure-from-Motion (SfM) and semiglobal matching techniques [18]. This innovative methodology enables real-time monitoring of excavation deviations, ensuring that tunnel construction adheres to specified engineering requirements and enhancing safety throughout the blasting process. The role of data analytics in monitoring and assessment technologies cannot be over-stated. [PERSON] (2017) emphasized the importance of processing and visualizing tunnel point cloud data, focusing on techniques for noise reduction and accuracy enhancement [14]. Effective noise reduction methods significantly improve the reliability of tunnel assessments, which is crucial when analyzing the effects of blasting operations on rock integrity and tunnel stability. The ability to produce clear and accurate visual representations of tunnel conditions allows engineers to make timely interventions and optimize blasting strategies. Furthermore, the digital identification techniques developed by [PERSON] et al. (2018) for detecting half porosity in tunnel blasting underscore the role of monitoring technologies in enhancing blasting performance. Utilizing 3D point cloud data extraction provides a reliable means of assessing the effects of blasting, enabling engineers to monitor and optimize blasting outcomes effectively [15]. This method not only improves the accuracy of assessments but also aids in the continuous evaluation of tunnel integrity post-blasting. Recent advancements in machine learning and artificial intelligence are also revolutionizing monitoring technologies in tunnel construction. For instance, [PERSON] et al. (2023) explored a semi-supervised learning-based point cloud network for segmenting 3D tunnel scenes, which enhances automation in tunnel inspections [25]. This innovative approach significantly improves the speed and accuracy of inspections, allowing for better maintenance practices and ensuring compliance with safety standards. Consequently, monitoring and assessment technologies are crucial for evaluating the effects of tunnel blasting.