Why Point Cloud Processing Is Essential for ICT Construction: Thorough Explanation of Reasons and Benefits

What position does "point cloud processing" occupy within ICT construction?

In recent years, the construction industry has been rapidly adopting ICT construction (construction that utilizes information and communication technology). Driven by Ministry of Land, Infrastructure, Transport and Tourism–led i-Construction and municipal DX promotion initiatives, the incorporation of digital technologies into site management is gaining momentum. Among these, a foundational technology attracting particular attention is "point cloud processing." Point cloud processing refers to the technology that uses large numbers of three-dimensional point data (point clouds) acquired by laser scanners or photogrammetry to digitally measure and analyze site terrain and structures.

In ICT construction, it is required to manage and verify site as-built conditions (the completed shape) and construction processes with data. Point cloud processing can be said to be the core technology that meets this need to "digitize the entire site." Whereas traditional 2D drawings and photos could not fully capture depth and form, point cloud data can record them directly in 3D.

For example, in earthwork with heavy machinery, scanning the terrain before and after construction with drones or LiDAR and converting it to point clouds makes it possible to accurately calculate fill and excavation volumes and instantly check discrepancies from the design cross-sections. In structural work, measuring the dimensions and positions of finished members on the point cloud and comparing them with the design model allows objective quality evaluation. In this way, point cloud processing has become an indispensable key technology for realizing the ICT construction goals of "visualization and automation of construction."

Why is point cloud processing demanded?

Why has the importance of point cloud processing increased so much? Behind this trend are changing challenges and needs in the industry.

• Responding to labor shortages and work-style reform: The construction site faces a serious shortage of skilled workers and surveying technicians. With urgent needs to reduce individual burdens and improve productivity, point cloud processing is expected as a means to perform efficient site measurement and management with few people. Measurements that traditionally required two to three people and a full day can, in some cases, be completed quickly by one person using point cloud scans. The ability to perform accurate surveying without large personnel input also contributes to promoting two-day weekends and correcting long working hours.

• Emphasis on quality proof and evidence: Especially in public works, the trend toward proving construction quality with data is intensifying. With photos and paper records alone, it is difficult to later verify "whether it truly matches the design," causing concern for clients. Point cloud data allow the completed object’s shape to be preserved as a faithful 3D record. As objective evidence, it enables third parties to verify construction accuracy later, dramatically improving the reliability of quality assurance. Storing construction history as point clouds also helps future renovation work or root-cause investigations in case of trouble.

• Need for objectivity and transparency in construction management: For clients and site supervisors, highly transparent construction management based on data is indispensable. There is increasing demand to understand the site with quantitative data rather than relying solely on verbal reports or experiential rules. Using point cloud processing, the current condition can be shared with numerical and visual information that is not influenced by subjectivity. This also contributes to smoother communication between subcontractors, prime contractors, and clients, helping to secure transparency in the construction process.

As described above, point cloud processing is demanded as a means to simultaneously overcome labor shortages, enhance quality assurance, and improve reliability through objective data.

Comparison with other methods: Differences between TS, photo records, and point cloud processing (density, speed, usability)

To better understand the usefulness of point cloud processing, let’s compare it with other recording and measurement methods traditionally used. We organize the differences with representative total station (TS) surveying and photo records from the perspectives of "data density," "operation speed," and "usability."

• Data density and coverage: TS and staff surveying measure points manually, so the obtained data are discrete and limited. For example, even if measuring ten key points is enough to check ground elevation after grading, the fine undulations between them cannot be understood. In contrast, point cloud scanning allows the terrain and structures to be measured as surfaces with high density. From a collection of millions of points, even slight hollows or inclinations are captured without omission. Also, while photo records can preserve visual information, they cannot quantitatively capture dimensions or shapes; point clouds, on the other hand, include depth data not visible in images and can record the "entire site"—a major difference.

• Operation speed and efficiency: Because point cloud measurement can acquire wide-area data at once, it enables substantial time savings in surveying work. For example, there are reported cases where terrain surveys of a development site that previously took three days were completed in about half a day by drone photogrammetry. Rather than walking to measure hundreds of points with a TS, placing a laser scanner and pressing a button covers a much wider area more quickly. Recently, handheld scanning using iPhone or iPad LiDAR has appeared, further improving mobility. As a result, heavy machinery wait times are reduced and construction periods shortened, leading to dramatic productivity improvements.

• Usability of data: TS measurement results are mainly used to create points and lines on drawings, so there has been limited scope for secondary use of acquired data. Photos are similar: they allow later situation confirmation but are not suitable for measurement or detailed analysis. By contrast, point cloud data are characterized by a very wide range of post-acquisition uses. From a single acquired point cloud, you can extract arbitrary cross-sections, calculate volumes, and perform error checks by overlaying with a 3D design model, enabling multifaceted analysis. As a true digital twin of the site, it generates long-term value from construction management and as-built verification to maintenance. Even if the data are referenced for other purposes in the future, detailed historical information can be retrieved without new surveying, preventing situations like "we forgot to measure this" or "there is no record"—another major advantage.

From these comparisons, point cloud processing has overwhelmingly greater information content and speed than traditional methods, and the acquired data can be used for many purposes. These strengths are highly attractive when promoting ICT construction.

Benefits of point cloud processing in ICT construction

What concrete benefits can be obtained by using point cloud processing in actual ICT construction site operations? We organize the main points into three sections.

• Automation and instant as-built management One of the greatest benefits of point cloud processing is the labor-saving and real-time nature of as-built management tasks. Traditionally, after construction, measurement data had to be brought back to the office and compared with drawings to determine conformity. By using point clouds, this process can be almost fully automated. For example, if you scan the site immediately after construction, you can instantly compare the captured point cloud with the design shape. With dedicated software or cloud services, differences from the design can be displayed as heat maps from the point cloud, allowing deviation areas from standards to be identified at a glance. You can notice insufficient fills or over-excavation on the spot and make immediate corrections, greatly reducing rework later. Point cloud measurement can also automatically calculate as-built quantities and instantly generate reports. Tasks that used to be done manually for as-built management can be completed by button operation, enabling real-time quality inspection—an innovative benefit unique to ICT construction.

• Improved construction accuracy through design comparison and AR visualization Point cloud data are also a powerful tool to improve construction accuracy through comparison with design data. By overlaying the acquired point cloud with a 3D design model, you can analyze in detail the differences between as-built and design. For example, recording the shape of a structure after concrete placement with a point cloud and matching it with BIM design data might immediately reveal that a column is off by a few centimeters (a few in). Recently, combining this with AR (augmented reality) technology has attracted attention. If you overlay point clouds or 3D design models onto the camera view on a tablet or smartphone, you can intuitively see deviations between design and reality in the real world. Being able to check on-site whether the erection of steel frames or the height of fills matches the design in AR during construction prevents quality defects in advance and moves closer to zero rework. Such on-the-spot verification–based construction represents the next stage in quality and accuracy management.

• Efficiency in remote support, inspections, and reporting Detailed 3D information obtained from point cloud processing is also powerful for sharing information with stakeholders who cannot visit the site. For example, if point cloud data are shared via the cloud, personnel at headquarters or designers can check the site’s 3D condition from the office. Contents that were traditionally conveyed by photos or phone can be accurately handled on the point cloud—measuring dimensions or checking cross-sections enable precise remote support. Also, if point cloud data are shared prior to client attendance inspections, on-site confirmation becomes smoother and, in some cases, remote inspections may substitute for simple matters. In as-built reporting, instead of paper forms with many photos pasted in, you can create reports that use color 3D visuals and difference heat maps based on point clouds, making the situation understandable at a glance. 3D reports that anyone can intuitively grasp reduce explanation time and misunderstandings, facilitating consensus building among stakeholders. Point cloud processing thus overcomes geographic and temporal constraints to share site information and improves efficiency in both construction management and communication.

Relationship with government guidelines: alignment with as-built management guidelines and expansion of application

The use of point cloud processing is closely linked to the as-built management guidelines established by national and municipal governments. Recently, the Ministry of Land, Infrastructure, Transport and Tourism published the "as-built management guidelines (draft) using three-dimensional measurement technology," clarifying the role of point cloud measurement in ICT-enabled construction. As a result, as-built management based on point cloud data is increasingly recognized officially as a method of construction management.

Specifically, standardization began with earthworks, where drone photogrammetry and laser scanners have been used for as-built management, and systems were established to evaluate fill and cut volumes based on as-built measurement data (point clouds). Following this success, the application of 3D point cloud measurement is expanding to other types of work such as bridge substructures, river structures, and paving works. The as-built management guidelines (draft) indicate procedures such as removing unnecessary points from point cloud measurements and creating "as-built evaluation point data" that meets required point density, establishing a system whereby point cloud data can be used for quality evaluation equivalent to traditional TS points.

This trend encourages site digitalization and effectively means that point cloud processing skills will become essential for contractors. In government-funded projects, using three-dimensional as-built management technology may be given evaluation points or bonuses, and it is suggested that in the future it could become mandatory for specific types of work. Site representatives and management engineers need to understand the latest guidelines and standards and build systems that can handle as-built management using point cloud processing. In other words, point cloud processing is shifting from an "optional advanced technology" to a "should-have standard technology."

Barriers at introduction and the LRTK solution approach: simple devices, one-person operation, instant cloud linkage

Although point cloud processing offers great benefits, it is true that several barriers are encountered when introducing it to the field. Typical barriers to introduction include the following points.

• Concerns about initial costs: High-performance 3D laser scanners and surveying instruments can cost several million yen, leading some to say that the capital investment is too large. With limited budgets, some organizations have been unable to take the plunge to introduce them.

• Concerns about technical learning and personnel: Acquiring and processing point cloud data requires operation skills for specialized software, and companies tend to avoid it thinking "we have no one who can use it" or "training will take too long." Especially in companies with few experienced personnel, handling new technologies is perceived as a high hurdle.

• Questions about accuracy and operation: Because it differs from traditional surveying, concerns such as "can it really measure with millimeter-level accuracy (about 0.04 in)?" and "will it be accepted in government inspections?" are heard. There are also concerns about operational burdens such as large data volumes and processing time.

An approach gaining attention as one way to solve these issues and smartly deploy point cloud processing on site is the use of "LRTK." LRTK is a solution composed of a palm-sized GNSS receiver device that attaches to a smartphone and a dedicated app, designed to enable anyone to perform high-precision point cloud measurement and AR visualization easily. Let’s look at how LRTK addresses the aforementioned barriers.

• Lower cost with simple equipment: LRTK is used by attaching a small device to a smartphone or tablet (iPhone or iPad). There is no need to purchase expensive dedicated equipment, and it can be introduced with relatively inexpensive subscriptions or cloud service fees. By combining the iPhone’s built-in LiDAR or camera with the LRTK device’s high-precision position information, point cloud data with accuracy comparable to surveying instruments that previously cost millions of yen can be obtained. The "smartphone + small device" simple equipment configuration greatly lowers the initial investment barrier.

• One-person operation and intuitive operation reduce personnel hurdles: LRTK is designed for on-site use and has very simple operation procedures. Start the dedicated app, press the "start scan" button, and walk around the area you want to measure—the point cloud acquisition completes automatically. The UI is easy to understand and intuitive enough that people without specialized knowledge can use it, enabling veterans and newcomers alike to adopt it quickly. Because it can be carried and operated by one person, it is suitable for sites with few workers. The ease of use that allows the site foreman or supervisor to think, "Let’s just measure this now," without requesting the surveying department is revolutionary. This dispels previous concerns such as "we don’t have anyone who can use it" or "training is a burden."

• Instant cloud linkage and high precision for operational confidence: Point cloud and photo data obtained with LRTK can be uploaded directly to the cloud for storage and sharing. There is no need to worry about troublesome file conversions or processing on a heavy PC; 3D data can be viewed and used from an office PC or tablet via a browser. The LRTK device receives real-time correction information from Japan’s quasi-zenith satellites (Michibiki) and other sources, providing centimeter-class positioning accuracy (half-inch accuracy) to the smartphone. This gives absolute coordinates to the smartphone point cloud, and measurement errors are typically within 2-3 cm (0.8-1.2 in), and with optimization, under 1 cm (0.4 in). You can check the acquired data on-site via the cloud and immediately perform additional measurements if anything is missing, enabling flexible operations. The cloud also supports one-stop processing such as automatically analyzing point clouds overlaid with design models or preparing AR display data. These mechanisms for immediacy and precision management allow point cloud operations to be established without worries like "can we trust the data?" or "is processing too burdensome?"

By utilizing LRTK in this way, anyone can start point cloud measurement and utilization on site immediately even without expensive equipment or specialized skills. This is why LRTK is attracting attention as a solution that removes the barriers to introducing point cloud processing.

Conclusion: An era when point cloud processing becomes essential—how to introduce it with LRTK without strain

Going forward, point cloud processing is transforming from a technology that is "nice to have" to one that is "indispensable" on construction sites. As a trump card for productivity improvement and quality assurance, governments and companies alike are promoting its use, and point cloud processing has become the core of ICT construction. Its usefulness as a key to solving problems such as labor shortages, advanced as-built management, and meeting client accountability is beyond dispute.

At the same time, applying new technology in the field naturally brings anxieties. However, as described in this article, by using the latest tools that leverage smartphones and the cloud (such as LRTK), point cloud processing can be incorporated into daily operations astonishingly easily. Start by trying it on a small scale to experience its simplicity and effectiveness. Handling point cloud data is no longer a task solely for specialists; it is becoming a new norm that anyone on site can perform.

You cannot avoid introducing point cloud processing if you want to strengthen ICT construction capabilities. Rather, view this as an opportunity and, using advanced case studies as references, gradually deploy it across your sites. Fortunately, solutions like LRTK that combine "simplicity, high precision, and immediate usability" have emerged, significantly lowering traditional barriers. Use this tailwind to integrate point cloud processing into your standard operations and improve operational efficiency and competitiveness.

To avoid falling behind the wave of site DX and, most importantly, to realize reliable and safe construction management—learning and utilizing point cloud processing will become an unavoidable mission for future site managers and supervisors. Take this opportunity to harness the latest technologies and step into the next generation of construction management.