# Recent Advancements in Non-Destructive Testing Techniques for Structural Health Monitoring
## 7 Laser Scanners Technique  
Laser Scanners are part of the remote sensing technologies that have been widely explored in civil engineering applications, namely for detailed documentation and inspection of large structures in recent years. The preference of laser scanners over traditional routine procedures is the ability of laser scanners to collect a huge amount of accurate data, which includes the geometry as well as different radiometric attributes [69]. Laser scanners can be considered as LiDAR (Light Detection and Ranging) or LaDAR (Laser Detection and Ranging) systems [70; 71; 72]. The principle of a laser system is the use of focused pulses of coherent light, where the system calculates the time of flight of the light (converted to distance) while it is transmitted and returned back from the measured object, see Figure 10. The generated scan offers a three-dimensional map of the collected points commonly called a \"point cloud\". The detailed 3D map (in millimeter accuracy) of the measured object can be generated by formed polygons, which are created via connecting the point clouds. One of the limitations of this system is only able to measure and generate a 3D map of visible surfaces of scanned objects, so its prime application is to measure deformations of visible objects such as girders of a bridge, i.e., the laser system is not able to detect any internal damages. Inadequate lighting and the low reflectivity of the scanned object can compromise the quality of the image and a slower scan rate may be required to improve the quality of the image [23]. Since the laser was applied in interferometry as an alternative for the traditional discharge lamps more than 50 years ago, a new type of measurement became possible [73];  
Figure 10: Laser monitoring system. this section focusses on recent applications of laser in monitoring the health structures, as discussed below. Laser reflection is being used for defects detection in reinforced concrete systems. [PERSON] and [PERSON] [74] the experimental results demonstrated that laser reflection techniques instantly and economically detect the occurrence of defects, but cannot measure the sizes of the defects. [PERSON] et al. [75] found, through simulations and experiments, the laser methods are active in the inspections of the concrete systems compared to halogen lamps. [PERSON] et al. [75] showed that the laser methods offer a wider inspection ranges (more than five meters), high sensitivity for damages, low power consumption (15 Watts laser excitation), and reduces wrong alarms because of external noise. The occurrence of cracks is also detectable by the laser scanners depending on the difference between the temperatures of the cracked and the solid areas. [PERSON] et al. [76] used a Laser Spot Thermography (LST) for detecting cracks in the surfaces of concrete slabs, the results showed that laser scanners not only detect the location of the surface cracks, but the thermal gaps across the depth of the cracks distinguish between shallow and deep cracks. The sensitivity of the laser beams for the variation in the thermal gaps in the concrete systems made it possible to use deep learning in the detection of cracks and fractures in the concrete systems. [PERSON] et al. [77] used deep learning technology and laser sensors for detecting and quantifying cracks on the surface of concrete systems. The YOLO algorithm was employed in deep learning to provide real-time detections and quantifying of the cracks. The laser was not only used to scan the concrete systems for cracks, it was also used to detect other defects and properties of concrete. [PERSON] [78] used laser methods to investigate the substrate roughness in patch repairs in concrete systems. Laboratory results showed that the laser methods are active in the characterization of the substrate roughness. The laser scanners generate a huge amount of data (big data) that is challenging to store, process, and interpret for traditional data management systems.