In this article, we will explain in simple terms the importance of utilizing point cloud data in the civil engineering industry and how it will impact the future. As digital transformation (DX) sweeps across the civil engineering industry, "point cloud data" plays a central role in this shift. Below, we will discuss how the use of point cloud data improves construction accuracy and efficiency, and explore the future of the industry.

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1. What is Civil Engineering DX? The Importance of Point Cloud Data

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DX in the civil engineering industry refers to the significant transformation of the design, construction, and maintenance processes through the use of ICT and digital technologies. For example, starting from the 2023 fiscal year, the Ministry of Land, Infrastructure, Transport, and Tourism has begun applying the principles of BIM/CIM to its direct construction projects, accelerating the digitalization of the entire industry. This shift is also driven by the need to address labor shortages and work style reforms (the so-called "2024 problem"), making it imperative to improve productivity and ensure safety through DX.

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In the context of DX, point cloud data is particularly important. Point cloud data is a collection of countless 3D points obtained through laser scanning or photogrammetry, which digitally records the terrain and structures of a site. It accurately reproduces the detailed shapes of the site that cannot be captured by drawings or models, serving as the foundation for creating a "digital twin," a replica of the real-world environment. This allows for the 3D modeling of aging infrastructure even without drawings, enabling the management and analysis of site conditions through data.

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The benefits of utilizing point cloud data are significant, directly contributing to improved construction accuracy and cost reduction. For example, traditional surveying tasks that used to take a lot of manpower and time can now be completed much faster by capturing point clouds with drones. There have been reports stating that "surveying that used to take 2 days was completed in just 0.5 days." In this way, point cloud data is gaining attention as a key element in driving DX, enabling tasks to be completed quickly and efficiently.

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2. Latest Trends in Point Cloud Data and CIM Integration

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An example of a digital twin integrating on-site point cloud data (terrain) with the CIM model of a sediment retention dam. By overlaying the design model with the current point cloud, it can be used to optimize the construction plan.

There is a growing trend to integrate point cloud data with 3D models in CIM (Construction Information Modeling) and BIM, which is one of the latest trends. By combining the 3D models created during the design phase (BIM/CIM models) with point cloud data from before and after construction, a digital twin of the entire site can be built. On this digital twin, comparisons and simulations between the design and the current state can be performed, allowing issues such as interferences and challenges that are often overlooked in traditional 2D drawings to be identified in advance.

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As a specific example, a major civil engineering company has integrated the point cloud data obtained from laser scanners with CIM models of earthworks, structures, and temporary structures to create a digital twin of a sediment retention dam project. By using this digital twin to develop the construction plan, they are now able to quickly and accurately calculate the volume of excavation and embankment, the amount of concrete required, and the quantities of formwork and scaffolding materials. As a result, they can create construction plans with minimal waste, leading to cost reductions and shortened project timelines.

The Ministry of Land, Infrastructure, Transport, and Tourism is also promoting the use of BIM/CIM, and point cloud data integration is featured as an example of "efficiency in supervision and inspection through the use of BIM/CIM." With the integration of point cloud data and CIM, an environment is being established where design, construction, and inspection are seamlessly linked, further supporting the transition to Smart Construction.

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3. Utilization of Point Cloud Data in Smart Construction

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Smart construction refers to the initiative to enhance and automate the construction process by fully utilizing ICT technologies. Point cloud data is used in various stages of smart construction, particularly excelling in as-built management and volume measurement.

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For example, in the as-built management of bridge foundation work, traditional methods involved using surveying equipment and plumb bobs to measure the tilt and eccentricity of piles one by one. In contrast, by using a laser scanner to measure and analyze the entire excavation area as point cloud data, it became possible to safely and comprehensively assess the as-built conditions, even in deep foundation pits. In a demonstration by Wako Construction, point cloud-based as-built measurement was performed on a deep foundation with a diameter of 12m and a depth of 25.5m, confirming both labor savings and improved safety. The need for human presence was reduced, preventing human error and ensuring quality.

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Additionally, the automation of volume calculations using point cloud data is a crucial aspect of smart construction. Traditionally, volumes were calculated by measuring heights on-site and comparing them with drawings. However, with point cloud data, excavated and embanked volumes can be immediately calculated by simply comparing data before and after excavation. In the previously mentioned digital twin example, comparing the point cloud with the model allowed the excavation and embankment volumes to be determined quickly and with high precision. By integrating 3D design data with point cloud data, it becomes possible to visually confirm deviations and discrepancies during construction, leading to reduced rework and improved accuracy.

In actual case studies, there have been reports of point cloud data being used in slope work to evaluate as-built conditions and reduce work time, as well as in tunnel excavation to compare point clouds with design models to manage excavation excesses and shortages. The use of point cloud data has dramatically shortened the "measurement → analysis → correction" cycle, making it a foundational technology supporting smart construction.

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4. Utilization of Point Cloud Data in Construction Management and Surveying

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Point cloud data is significantly transforming existing methods in construction management and surveying. In the field of surveying, both accuracy and efficiency have dramatically improved. By processing point clouds obtained through drone-based photogrammetry or laser scanning, traditional manual terrain surveying has been greatly simplified. As mentioned earlier, there have been examples where the surveying period was reduced to a quarter of the original time using drone surveying, marking a productivity revolution in surveying itself. Additionally, numerical terrain models (DTMs) and contour maps can be automatically generated from the acquired point cloud data and immediately utilized for design and construction planning.

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Furthermore, point cloud data is also expanding its applications in the maintenance and management of existing infrastructure. In regular inspections of roads and bridges, laser scanning is used to record and compare areas of deformation on the point cloud, making the detection of cracks and displacement measurements more efficient. Reports have also shown that filtering and classifying point cloud data to visualize features can significantly streamline tasks such as forest management, facility maintenance, and disaster recovery site inspections. For instance, in disaster areas, collapsed terrain can be immediately modeled using drone point clouds to identify hazardous areas, estimate the amount of debris, and plan recovery efforts. Point cloud data is advancing the "visualization" of site conditions and contributing to faster and more accurate decision-making.

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Moreover, integration with drone surveying is indispensable for construction management. Drones, which can quickly scan large areas from the air, are being used in projects like dam construction, land development, and slope work in mountainous regions. The acquired point clouds can be shared with stakeholders via the cloud, allowing remote progress monitoring or enabling experts to provide advice from afar. Recently, drones equipped with high-precision RTK-GNSS have also emerged, enabling the addition of highly accurate positioning information to the acquired point clouds. The evolution of surveying and point cloud data is supporting the reduction of labor and the advancement of construction management.

5. Utilization of LRTK: Ease of Point Cloud Acquisition and AR

In recent years, devices that make point cloud measurement, previously a high barrier, much more accessible have emerged. For example, LRTK Phone is a small device that attaches to a smartphone, enabling centimeter-level positioning and point cloud scanning using RTK-GNSS. With the dedicated app, users can simply point their smartphone at the surroundings on-site and instantly capture 3D point cloud data. The acquired data is associated with high-precision location information, so distances and volumes on the point cloud can be calculated immediately. For example, scanning embankments or deposited soil allows for instant volume calculations, making it possible to directly measure and calculate volumes on-site. What used to be outsourced to specialized companies for point cloud measurement can now be done by in-house staff using just their smartphones, greatly accelerating the digital transformation (DX) of the site.

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On the other hand, for high-precision measurement over a wider area, dedicated LiDAR devices like LRTK LiDAR are effective. LRTK LiDAR is hardware capable of long-range laser scanning and functions as a ground-based 3D laser scanner. Even for large-scale land development sites or complex plant installations, it can quickly acquire high-density point clouds. The revolutionary aspect is that high-cost laser scanners, which were previously expensive, are now available in a more affordable and user-friendly form. The LRTK series also offers a range of devices to make on-site position measurement and point cloud acquisition easier, including the wearable LRTK gear and GNSS terminal integrated into helmets. By combining devices suited to your specific needs, the use of point cloud data can be further expanded.

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Additionally, integration with drones is key for large-scale sites. Areas that cannot be covered by the LRTK device can be supplemented with photo-based point clouds or UAV laser scanning from drone aerial photography, and by combining ground and aerial data, detailed 3D data of the entire site can be created. For example, in mountain tunnel construction, point clouds of the tunnel interior can be obtained using ground-based LiDAR, and the terrain outside the tunnel can be captured with a drone. These can be merged to provide a comprehensive understanding of the terrain. LRTK's high-precision positioning technology can also be used for georeferencing (position correction) in drone-based photogrammetry, ensuring the accuracy of point clouds generated from aerial photos. By acquiring point cloud data across multiple platforms, flawless digital records can be achieved for any site.
 

Finally, the visualization of point cloud data using AR (Augmented Reality) technology is also worth noting. By displaying the site through tablets or smartphones and overlaying point cloud data and design 3D models onto the footage, the situation can be intuitively understood. For example, by displaying the completed design model in AR on a construction site, the as-built conditions (progress) can be instantly assessed, and discrepancies from the plan can be quickly identified. A major construction company has developed a system that aligns surrounding point cloud data with BIM models, visualizing building layouts and pipe locations in AR. As a result, it is reported that this has significantly reduced the time required for foundation inspections and reinforcement checks. In this way, using AR eliminates the need to manually compare drawings with the site, allowing all stakeholders to share the same image. This leads to early detection of construction errors, prevention of rework, and improved accuracy in quality management. In the future, using LRTK’s high-precision devices to upload point clouds to the cloud and share them for viewing with AR glasses will likely become commonplace.

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6. Future Outlook and the Future of the Industry

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The use of point cloud data is expected to continue evolving and play a significant role in shaping the future of civil engineering. One area to watch is the fusion of point cloud data and AI. Research is progressing on using AI to automatically extract useful information from vast point clouds. For example, technology is being developed to automatically detect deterioration or deformations of structures on point clouds, or for AI to recognize excavation and embankment progress and feed this back into schedule management. This will allow tasks that previously relied on the experience of seasoned professionals, such as checks, to be automated and streamlined, further advancing quality control. In fact, technologies for classifying point cloud data with machine learning to identify features are already being put into practice, and point cloud automatic classification and analysis services, like ScanX mentioned earlier, have emerged. With the advancement of AI, it will soon be possible to fully unlock the potential of point cloud data.
 

The progress of communication technologies also cannot be overlooked. Real-time construction management using 5G and cloud services is becoming increasingly feasible. With the high-speed, high-capacity 5G network, high-precision point cloud data captured on-site can be instantly uploaded to the cloud, allowing 3D site conditions to be monitored in real-time from the office or remote locations. Supervisors and clients can check progress and issue instructions based on point cloud data without physically visiting the site, making remote site supervision and remote construction management the norm. In fact, the Ministry of Land, Infrastructure, Transport, and Tourism is currently developing guidelines for remote site supervision, and there are increasing instances of sharing point cloud and video data for inspections and site attendance. The point cloud data stored in the cloud will also serve as a digital archive for future renovation projects or disaster response. Future developments, such as simulations and predictive maintenance using digital twins, are also highly anticipated.

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As the future of smart construction progresses, the required skills are also changing. In addition to traditional knowledge of surveying and construction management, digital skills such as drone operation, 3D data processing, and the basics of AI analysis will be necessary for engineers. The government has also set forth "i-Construction Talent Development," and there is an urgent need to cultivate talent capable of handling 3D data. Conversely, acquiring these skills will increase an individual’s value in the industry and make them a key player in driving civil engineering in the DX era. Digital transformation presents an opportunity for companies to enhance their competitiveness, and investing in digital technologies, including point cloud data, will become increasingly important in the future.

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7. Conclusion:
The Future of Civil Engineering Transformed by Point Cloud Data

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Point cloud data, emerging as a key element of civil engineering DX, is driving innovation across a wide range of fields, from surveying and construction planning to quality management and maintenance. By precisely digitizing the "present" of the site and integrating it with design data, we have made it possible to build and maintain infrastructure more intelligently and safely. The first step is to begin utilizing point cloud data, even in small ways. For example, experimenting by 3D scanning a part of the site and comparing it with traditional methods will quickly show the benefits. Additionally, sharing and reviewing point cloud data within the company deepens stakeholders' understanding of digital data.

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Fortunately, tools like LRTK Phone have made it easy for anyone to capture point cloud data. By introducing devices that don’t require specialized knowledge, companies can begin driving site DX starting tomorrow. Leveraging point cloud data for operational improvements directly leads to increased productivity and cost reduction, contributing to work style reforms and addressing labor shortages. For enhancing competitiveness, adopting point cloud measurement technology is highly beneficial for companies.

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It is no exaggeration to say that the future of civil engineering will be determined by those who control data. Companies and engineers who can harness the new "resource" of point cloud data will lead the way in infrastructure development. As a first step toward utilizing point cloud data, consider introducing small RTK devices and offering employee training, and begin digitizing site 3D data to the extent possible. These small steps will eventually result in significant DX outcomes.