Photo-based surveying surpassed by smartphone RTK positioning? LRTK boosts efficiency in infrastructure inspections

For local governments and construction-site engineers responsible for infrastructure management, photogrammetry has in recent years become an indispensable method for on-site 3D recording and surveying. By generating 3D models from large numbers of aerial or ground photos, it enables dimensional measurement and recordkeeping of terrain and structures, and is widely used for bridge and road inspections, as-built management at construction sites, and more. However, photogrammetry also poses challenges in data processing effort and ensuring accuracy. A newly notable approach combines smartphones with RTK (real-time kinematic) technology for positioning. By attaching a compact high-precision GNSS receiver to a smartphone, GPS errors that used to be on the order of several meters (several ft) can be reduced to a few centimeters (a few in), allowing acquisition of accurate position information and 3D data on-site. A representative example is a solution called LRTK, an innovative initiative that turns a smartphone into an all-in-one surveying device for each worker. This article compares photogrammetry and smartphone RTK positioning (LRTK) and clearly explains the benefits for infrastructure inspection tasks. We will look in detail at the effects of LRTK’s features—reliable positioning from high-precision GNSS, point-cloud acquisition anyone can do with a smartphone, on-site verification using AR, geotagging of photos, and cloud-enabled data sharing—on infrastructure maintenance and management. Finally, we will consider the transformations that adopting such smartphone RTK–based lightweight surveying brings to the field.

What is photogrammetry? Digitalization advancing in infrastructure inspection

First, what is photogrammetry? As the name suggests, it is a technique for measuring the shape and dimensions of objects from photographs; by analyzing the positional relationships between multiple photos and feature points on the target, a 3D model (point cloud data or 3D mesh) is generated. In recent years, aerial photogrammetry using drones has become widespread and has been highly effective for creating topographic maps and digitally recording infrastructure structures. For example, in bridge and tunnel inspections, drones can photograph high or inaccessible locations to obtain detailed 3D models, enabling safe and efficient detection of defects and dimensional measurements that were previously difficult. In as-built management, photogrammetry can record terrain before and after construction to calculate earthwork volumes or compare with design plans, contributing to DX (digital transformation) in construction management.

The strength of photogrammetry lies in capturing large areas in relatively short time while obtaining detailed visual data. 3D models generated from high-resolution images can record fine details that might be missed by the naked eye, and can be analyzed later in the office. In infrastructure inspection, this means structures can often be evaluated at the desk without repeated site visits. Photogrammetry is also attracting attention as a method to create digital twins of existing facilities, enabling advanced uses such as comparing inspection results over time to monitor aging.

On the other hand, photogrammetry has some noted challenges. First, data processing requires time and expertise. Creating a high-precision 3D model from many photos requires dedicated software for feature-point matching and triangulation calculations between photos, so results usually cannot be obtained immediately on site. Processing demands high-performance PCs or cloud services and can take several hours or more. Also, establishing control points for accuracy is important. To align photogrammetric models to an accurate coordinate system, multiple reference points (targets) with known coordinates must be installed on-site and included in the images; this extra work and the surveying knowledge required can be a barrier to adoption. Using drones also brings issues of flight permissions and safety management, and weather or time-of-day restrictions may impede planned shooting. In indoor spaces or under bridges where GPS signals do not reach, drone flights are difficult and photogrammetry may be hard to apply.

Thus, while photogrammetry is a groundbreaking technology, it has limitations in real-time capability and ease of use. Smartphone RTK positioning has emerged to fill this gap. Next, we will look at LRTK, this new approach.

What is smartphone RTK positioning (LRTK)? A new technology that changes the field

RTK (real-time kinematic) is a technology that corrects satellite positioning errors (GPS, GLONASS, QZSS, etc.) in real time to enable centimeter-level high-precision positioning. It receives correction information from a base station and uses the carrier phase of satellite signals for high-precision position calculation. Traditionally, using RTK required large, expensive equipment such as fixed GNSS receivers and antennas, communication modems, and sometimes paired base and rover units. However, recent miniaturization of hardware and development of communication infrastructure have made RTK’s benefits accessible on everyday devices. Smartphone RTK positioning refers to solutions that combine a smartphone with an external RTK-capable GNSS receiver. LRTK is an advanced product that realizes smartphone RTK: by simply attaching an ultra-compact receiver weighing approximately 125 g and only about 1.3 cm (0.5 in) thick to a smartphone, position accuracy that used to have errors of about 5–10 m (16.4–32.8 ft) on typical built-in GPS can be improved at once to a few centimeters (a few in).

LRTK supports not only network RTK (base-station corrections via the Internet) but also CLAS, the nationwide instantaneous positioning augmentation service provided by Japan’s QZSS (Michibiki), so it can receive augmentation signals from satellites and achieve centimeter-level positioning even in mountainous areas without mobile-phone coverage. This allows stable high-precision position information to be obtained in locations where GNSS positioning is usually unstable, such as tunnel entrances or under trees (although full indoor environments where satellite signals cannot be received still present challenges, hybrid corrections combining inertial measurement can bridge positions for short periods).

What changes with the advent of smartphone RTK? In short, the impact of “a smartphone becoming a surveying instrument for each person” is enormous. Traditionally, surveying and inspection required specialist surveyors with expensive equipment to perform positioning, with other staff recording and organizing the data—processes that took manpower and time. With LRTK, field staff can complete surveying and recording themselves with a smartphone in hand. A single smartphone with an LRTK terminal attached can handle not only high-precision positioning but also 3D point-cloud measurement, photo capture with position recording, navigation to stakeout points, and more. This reduces the need to switch dedicated equipment or return to the office for analysis, dramatically improving the efficiency of infrastructure inspections and surveying. Moreover, device miniaturization and use of general-purpose devices reduce costs, making advanced technologies more accessible to municipalities and small-to-medium enterprises that had been reluctant to adopt them. Now, let us compare the main differences between photogrammetry and smartphone RTK (LRTK).

Comparison of photogrammetry and smartphone RTK (LRTK)

Both photogrammetry and smartphone RTK (LRTK) digitally record and measure field conditions, but their approaches and strengths differ. Below we compare them from several perspectives.

• Position accuracy and coordinate acquisition: With photogrammetry, even if the relative accuracy (shape fidelity) of the resulting 3D model is high, aligning it to real-world coordinates requires separate tasks like control-point surveying. In contrast, LRTK’s RTK-GNSS can directly acquire absolute coordinates such as latitude, longitude, and height in a global datum. In other words, data captured and scanned on-site are tagged with accurate coordinates from the start, eliminating later alignment work. For example, if a crack on a bridge pier is recorded by photogrammetry, you might know its location on the model but need extra work to find where that is on a map; with LRTK you can record from the outset “crack at latitude/longitude ○○, height ○○ m (○○ ft).”

• Immediacy of data acquisition: Photogrammetry requires post-processing in the office to obtain point clouds or models after shooting, whereas LRTK can provide results in real time on-site. If you scan the surroundings by waving a smartphone, point-cloud data are generated on the spot, and you can immediately measure distances or calculate volumes. Because you don’t need to wait for complex post-processing, you can verify and re-shoot on-site, preventing missed data. Also, LRTK’s geotagged photo function saves coordinates at the moment of capture, removing the need to “organize photo locations after returning to the office.”

• Required equipment and cost: High-precision photogrammetry often requires high-quality cameras, RTK-capable drones, terrestrial laser scanners, etc., and different equipment depending on the situation. Personnel to operate them and software license costs add up. LRTK, by contrast, can be largely completed with just a smartphone and a compact receiver. Because one device can serve multiple roles, equipment consolidation reduces costs compared to assembling dedicated instruments. Subscription-based services like LRTK can further lower initial investment, making adoption easier for small and medium organizations.

• Coverage range: Drone photogrammetry is suitable for wide areas and locations where people cannot enter, but it is not effective for indoor spaces or behind bridge girders. Smartphone RTK has the advantage of being able to position and record anywhere a person can go. If someone can walk under a bridge or inside a tunnel and perform a LiDAR scan with a smartphone, shapes can be captured, and high-precision coordinates obtained near entrances can be used to tie partial surveys together. Of course, for overviewing large forests or precipitous cliffs from above, photogrammetry is more suitable, and using both methods together as appropriate is effective.

• Data use and visualization: Photogrammetry produces highly detailed 3D models and orthophotos with excellent visual clarity. LRTK directly leverages point clouds and survey points, enabling workflows where collected point clouds are overlaid on CAD drawings with colorized deviations, or shared in the cloud for collaborative comments—real-time data utilization workflows. As described later, AR visualization that overlays design models and as-built data on a smartphone is also easy with LRTK, enabling decision-making directly on-site rather than just producing models.

In summary, photogrammetry is well suited for creating precise wide-area models and aerial observation, while smartphone RTK (LRTK) excels at immediate on-site measurement, position recording, and data sharing. Next, focusing on infrastructure inspection tasks, let’s look concretely at what benefits LRTK brings.

LRTK functions and benefits that are useful for infrastructure inspection

In fieldwork for infrastructure maintenance, LRTK’s features directly improve inspection efficiency and accuracy. Below we detail LRTK’s main characteristics—high-precision positioning, point-cloud acquisition, AR display, geotagged records, and cloud sharing—while comparing them to photogrammetry where useful.

Accurate position awareness from centimeter-class GNSS positioning

In infrastructure inspection, it is crucial to know the “exact position” of deterioration spots or planned repair locations. Traditionally, photogrammetry or conventional GPS had large position errors, and on-site markings or paper ledgers filled gaps; LRTK’s centimeter-level positioning provides reassurance. For example, photographing a crack on a bridge with LRTK records the photo with latitude/longitude coordinates at an accuracy of ± a few centimeters (± a few in). Later during repair work, that coordinate can be used to pinpoint the exact location, enabling reliable sharing of “which member and which position had the defect.” Because LRTK continuously tracks the current position with high precision while measuring, it can also guide workers to arbitrary points using a coordinate navigation (guidance) function. By following an arrow on the smartphone screen toward specified inspection points in the cloud, workers can find hidden markers or equipment that is hard to see at night or obscured by vegetation. In this way, high-precision GNSS greatly increases the reliability of position management in infrastructure inspections.

Easy 3D point-cloud acquisition with a smartphone

Inspection tasks often require three-dimensional records of object shapes or quantitative assessment of deformation and damage. LRTK enables this via smartphone 3D point-cloud scanning. On LiDAR-equipped devices such as iPhone or iPad Pro, the LRTK app can capture point-cloud data simply by walking around the structure while scanning. Because the smartphone’s self-position is corrected in real time by RTK, distortion or drift does not accumulate in the point cloud even after long-distance scans. Normally, standalone smartphone AR scans can gradually accumulate error and distort the model, but with LRTK the current position is always known with cm-level accuracy (half-inch accuracy), allowing accurate shape capture even for large structures. In fact, there is an example of successfully scanning a castle keep from about 60 m (196.9 ft) away across the moat using LRTK. Detailed measurements that previously required expensive laser scanners or scaffolding can now be completed in minutes with a smartphone in hand.

Captured point-cloud data can be reviewed on the smartphone screen on-site, distances between any two points measured, and area/volume calculated immediately. For example, you can calculate the collapsed volume of a road slope from point clouds or measure deflection of a bridge girder in a cross-section on-site. If additional measurements are needed, they can be taken right away, reducing wasted re-visits after discovering missing data back at the office. Point-cloud measurement data can be stored as detailed as-built records of infrastructure and serve as valuable assets for longitudinal comparisons and repair planning.

On-site overlay display using AR

One distinctive LRTK feature is AR-based overlay display of data. This projects 3D models or drawing information onto the smartphone screen as if they existed on-site, bringing innovation to inspection and construction management. For example, overlaying the as-built point cloud obtained with LRTK and the design 3D model can generate a heatmap to visually check construction accuracy at a glance. Areas matching the design show green or blue, while deviations appear red, making it intuitive to see where rework is needed. Where previously it took time to analyze survey data and compare it with drawings, an AR heatmap allows immediate pass/fail judgment on-site, greatly increasing inspection and correction efficiency.

AR is also powerful for visualizing buried utilities. If you have previously measured and scanned subsurface water/sewer pipes and cables with LRTK, you can AR-display those point clouds or models on-site to know their locations without excavating. During the next excavation, avoiding the AR-projected pipe positions reduces the risk of accidentally damaging lifelines. AR can also display boundary stakes or design lines: projecting virtual lines or points on boundary lines makes it easy to visually confirm land boundaries or curve inflection points that are hard to interpret from survey plans alone.

LRTK’s AR function has the advantage that displays do not shift when you move. In normal smartphone AR, displayed objects can drift from reality while walking around, but LRTK places objects based on absolute coordinates, so positional relationships remain correct even across a wide site. This makes it simple for clients and contractors to view the same completion image together on-site. By seamlessly integrating on-site conditions and digital data through AR, sharing inspection results and reaching consensus become far smoother.

Efficient records with geotagged photos

Photo records are indispensable in infrastructure inspection. Photographing cracks or corrosion and compiling reports is routine, but organizing “where each photo was taken” afterward has been time-consuming. LRTK’s geotagged photo function smartly solves this. When you take a photo with a smartphone, it automatically records the high-precision coordinate value and the camera orientation (bearing) at the moment of capture. For example, if you photograph a crack on a tunnel inner wall, the image file can be tagged with “tunnel ○○ m (○○ ft) point, left wall, height ○○ m (○○ ft), bearing northeast.” This eliminates the need for handwritten notes and lets on-site recordkeeping be completed with one button.

If geotagged photos are uploaded to the cloud, you can plot shooting locations on a map and check shooting directions. Field staff, supervisors, and other departments in the office can share information in real time, enabling decisions and instructions such as “prioritize repair at this spot” right on-site. Because photos and position information are bundled, they can be output directly as a report PDF, greatly shortening report preparation time. Before LRTK, the usual flow was to bring handwritten notes back and organize a photo ledger, but now a digital ledger can be auto-generated on-site with a single button press.

Smooth data sharing through cloud integration

LRTK is designed to integrate with cloud services, allowing all on-site data to be uploaded and shared with one tap. Point clouds, geotagged photos, measurement coordinates, and notes sync to the cloud instantly, enabling remote offices to monitor field conditions in real time. For example, while a field worker scans a bridge pier, an engineer in the office can view the point cloud in the cloud and promptly instruct, “Also capture the backside here,” enabling two-way communication. This helps prevent missed data and supports immediate on-site decision-making, improving the reliability of inspection work.

Data aggregated in the cloud are organized by date and location and stored for easy inspection-history management. Comparing past data or automating report creation can be semi-automated with cloud tools, far more efficient than manually organizing paper ledgers or spreadsheets. Created 3D point clouds and photos can be shared externally by generating a shareable URL, serving as explanatory material for contracting companies or residents. Recipients can view 3D data in a web browser without special software. Rapidly sharing inspection results with all stakeholders and establishing a common understanding is an important step in DX for infrastructure maintenance.

Conclusion: Easy, high-precision infrastructure management with smartphone RTK

Photogrammetry has driven major digitalization of infrastructure inspection, and smartphone RTK (LRTK) further evolves this into an accessible, real-time method. The style of “measuring while recording and sharing immediately” will become the standard for field-driven DX. Introducing solutions like LRTK lets organizations with few specialists—such as municipalities and field teams—handle centimeter-precision survey data easily. The result is improved accuracy of inspection and repair planning, operational efficiency, and enhanced on-site safety.

Of course, photogrammetry and traditional techniques will remain suitable for detailed wide-area surveys in many cases, but smartphone RTK will be a powerful assistant in numerous infrastructure maintenance situations. By wisely adopting the latest technologies, why not realize inspection and surveying that combine ease of use and high precision? Lightweight surveying with LRTK that can be completed with a single smartphone will transform field workflows and open new possibilities in infrastructure management.