In the Fourth Industrial Revolution, research and development of application technologies that combine high-tech technologies have been actively conducted. Building information modeling (BIM) technology using advanced equipment is considered promising for future construction projects. In particular, using a 3D laser scanner, LIDAR is expected to be a solution for future building safety inspections. This work proposes a new method for evaluating building stability using a 3D laser scanner. In this study, an underground parking lot was analyzed using a 3D laser scanner. Further, structural analysis was performed using the finite element method (FEM) by applying the figure and geometry data acquired from the laser scan. This process includes surveying the modeled point cloud data of the scanned building, such as identifying the relative deflection of the floor slab, and the sectional shape and inclination of the column. Consequently, safety diagnosis was performed using the original evaluation criteria. This confirms that it is precise and efficient to use a 3D laser scanner for building stability assessment. This paper presents a digital point cloud-based approach using a 3D laser scanner to evaluate the stability of buildings.

Concrete cracks can threaten the usability of structures and degrade the aesthetics of buildings. Furthermore, minor cracks can develop into large-scale cracks that may lead to structural failure when exposed to excessive external loads. In addition, the concrete crack width and depth should be precisely measured to investigate the effects of concrete cracks on the stability of structures. Thus, a nondestructive and noncontact testing method was introduced for detecting concrete crack depth using thermal images and machine learning. The thermal images of the cracked specimens were obtained using a constant test setup for several months under daylight conditions, which provided sufficient heat for measuring the temperature distributions of the specimens, with recording parameters such as air temperature, humidity, and illuminance. From the thermal images, the crack and surface temperatures were obtained depending on the crack widths and depths using the parameters. Four machine-learning algorithms (decision tree, extremely randomized tree, gradient boosting, and AdaBoost) were selected, and the results of crack depth prediction were compared to identify the best algorithm. In addition, data bias analysis using principal component analysis, singular value decomposition, and independent component analysis were conducted to evaluate the efficiency of machine learning.

The development of unmanned aerial vehicles (UAVs) is expected to become one of the most commercialized research areas in the world over the next decade. Globally, unmanned aircraft have been increasingly used for safety surveillance in the construction industry and civil engineering fields. This paper presents an aerial image-based approach using UAVs to inspect cracks and deformations in buildings. A state-of-the-art safety evaluation method termed SMART SKY EYE (Smart building safety assessment system using UAV) is introduced; this system utilizes an unmanned airplane equipped with a thermal camera and programmed with various surveying efficiency improvement methods, such as thermography, machine-learning algorithms, and 3D point cloud modeling. Using this method, crack maps, crack depths, and the deformations of structures can be obtained. Error rates are compared between the proposed and conventional methods.

In this era of the fourth industrial revolution, the integration of big data and 3D printing technology with the construction industry has maximized productivity. Currently, there is an active effort to research the optimal cladding structure through 3D printing technology to reduce production costs. This paper proposes a new type of 3D print curtain wall, using a high-strength ABS-M30 polymer panel, which is stronger than the standard acrylonitrile butadiene styrene (ABS) polymer, as an internally reinforced structure. This structure is fabricated via fused deposition modeling, a 3D printing method, to reduce the weight of the general cement panel. In addition, the shape of the polymer board was designed; three shapes were considered—O, W, and X types—which aided in further reducing the weight of the cladding. After comparing the center deformation of the structure through a lateral load test and finite element method analysis, the optimal model was selected. The measured data of the two methods at a design wind speed of 100% showed a difference of approximately 10%; however, at 150% of the design wind speed, the difference between the two sets of data increased to 27%.