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As civil engineering structures become larger, non-contact inspection technology is required to measure the overall shape and size of structures and evaluate safety. Structures are easily exposed to the external environment and may not be able to perform their original functions depending on the continuous load for a long time. Therefore, in this study, we propose a method for estimating the vertical displacement of structures using light detection and ranging, which enables non-contact measurement. The point cloud acquired through laser scanning was rearranged into a three-dimensional space, and internal nodes were created by continuously dividing the space. The generated node has its own location information, and the vertical displacement value was calculated by searching for the node where the deformation occurred. The performance of the proposed displacement estimation technique was verified through static loading experiments, and the octree space partitioning method is expected to be applied and utilized in structural health monitoring.

A terrestrial light detection and ranging (LiDAR) can be used to construct the building information modeling as well as to measure shape deformation that varies with time or load during or ...

As high-rise buildings and aging structures increase, researches are underway to effectively inspect structures and prevent accidents in Korea. The structure cannot maintain its original shape due to natural disasters and loads, and deformation occurs. The accidents caused by the deformation of the structure have become a common news in the surroundings. Therefore, this study proposes a noncontact shape management monitoring method that can check structures and detect deformation.

In recent years, building energy consumption has increased in response to climate change, resulting in a worldwide reduction of energy efficiency. A strong response is required, through both the enhancement of building energy efficiency and the reduction of power usage. These objectives could be achieved by pursuing “Blackout” prevention, through developing a control unit such as that of the urban energy grid system that was used in the Energy Operation Center (EOC) for smart cities. In this context, this paper presents an optimization operation technique for Building Energy Management Systems (BEMS), using control monitor-based Building Information Modeling (BIM) for the efficient operation of the EOC. BIM is one of the approaches that can be used for the visual representation, management, and exchange of information on all aspects of a building. The EOC should be able to efficiently represent the data from the building information, and the operator maintaining it should be able to promptly acquire the data for handling it. This suggests that the control of energy consumption by a Building Automation System (BAS) to maximize building energy efficiency will lead to improved total energy performance, reduced operating costs, and reduced environmental impact.

Terrestrial laser scanning (TLS) provides a rapid remote sensing technique to model 3D objects but can also be used to assess the surface condition of structures. In this study, an effective image processing technique is proposed for crack detection on images extracted from the octree structure of TLS data. To efficiently utilize TLS for the surface condition assessment of large structures, a process was constructed to compress the original scanned data based on the octree structure. The point cloud data obtained by TLS was converted into voxel data, and further converted into an octree data structure, which significantly reduced the data size but minimized the loss of resolution to detect cracks on the surface. The compressed data was then used to detect cracks on the surface using a combination of image processing algorithms. The crack detection procedure involved the following main steps: (1) classification of an image into three categories (i.e., background, structural joints and sediments, and surface) using K-means clustering according to color similarity, (2) deletion of non-crack parts on the surface using improved subtraction combined with median filtering and K-means clustering results, (3) detection of major crack objects on the surface based on Otsu&rsquo, s binarization method, and (4) highlighting crack objects by morphological operations. The proposed technique was validated on a spillway wall of a concrete dam structure in South Korea. The scanned data was compressed up to 50% of the original scanned data, while showing good performance in detecting cracks with various shapes.

The global warming has been recognized as a serious problem. To solve this problem, the country of all the world have conducted techniques such as energy saving and reduction of greenhouse gas. The 30% of total energy is being consumed by buildings domestically and BAS/BEMS are being operated for the management of building energy. But, BEMS is unsatisfactory condition to manage the energy efficiently. In this study, We investigate real application on Chamsaem elementary school as a target buildings and develop 3D Web Browser platform. The spatial information of target buildings is described with used BIM and the energy information is presented for facilities operation and electricity consumption in floor and facility. We perform the quantitative evaluation based on ISO/IEC 9126 and operate this system for two months. in result, energy decreased by about 16%. We expect that the proposed 3D Web Browser system will bring operating efficiency improvement of the current BEMS.

In this study, the representative data extraction is performed for the shape information model of civil infrastructures. The scan data is extracted by octree data processing. The octree data processing generates a voxel of 3D space which is recursively subdivided into eight sub-voxels. The point cloud of the scan data was converted to voxels and sampled. The experimental site for terrestrial laser scanning is located at Sungkyunkwan University. The scanned structure is a steel girder bridge. For Terrestrial Laser Scanning(TLS), the Leica ScanStation C10 was used. The scan data was condensed 92% and the octree model was constructed with a 2 millimeter resolution. Accuracy verification was carried out in order to confirm that the data characteristic were retained. The objective of this study is to use Octree data processing to reduce large amounts of point clouds. Octree data processing will be the foundation for shape information model of the large structures such as double-deck tunnels, buildings and bridges. The research will be expected to improve the efficiency of shape information model.

Owing to the large ratio of consumption in the building sector, energy-saving strategies are required. Energy feedback is an energy-saving strategy that prompts consumers to change their energy-consumption behaviors. The strategy has been principally focused on providing energy-consumption information. However, the realization of energy savings using only consumption information remains limited. In this paper, a building-energy, three-dimensional (3D) visualization solution is thus proposed. The aim is to determine if the building manager will replace the facility after our recommendation to improve the building-energy efficiency derived from the energy information is given. This solution includes the process of diagnosing a building and providing a prediction of energy requirements if a building improvement effort is undertaken. Accurate diagnostic information is provided by real-time measurement data from sensors and building models using a close-range photogrammetry method, without depending on blueprints. The information is provided by employing visualization effects to increase the energy-feedback efficiency. The proposed strategy is implemented on two testbeds, and building diagnostics are performed accordingly. For the first testbed, the predicted energy improvement amount resulting from the facility upgrade is provided. The second testbed is provided with a 3D visualization of the energy information. The predicted value of energy improvement was derived from the improvement plan through energy diagnosis in each testbed as about 30% and as about 28%, respectively. Unlike existing systems, which provide only ambiguous data that lack quantitative information, this study is meaningful because it provides energy information with the aid of visualization effects before and after building improvements.