In modern infrastructure construction, quality control of reinforced concrete structures remains one of the most labour-intensive processes.
Inspection of reinforcement cages and preparation of as-built documentation traditionally require significant time and human resources, including field measurements, photographic documentation, data processing, and report preparation.
Our Swiss partner Pix4D, which specialises in mapping and photogrammetry software, presented a practical case study in which reinforcement inspection was carried out using a smartphone and PIX4Dcatch.
The solution was integrated with Modely, a specialised platform for 3D reinforcement inspection. This workflow enabled the project team to replace conventional photo-based inspections and manual measurements with a digital process based on point cloud data.
Read the original Pix4D case study here.
The project was implemented as part of the modernisation of the Kansai Main Line, an important railway route connecting Osaka and Nagoya.
Project challenges
Many smartphone-based 3D measurement solutions tested during the project did not meet professional inspection requirements.
The most common issues included:
- Gaps in the generated point clouds.
- Inaccurate reproduction of thin reinforcement bars.
- Results that varied depending on the operator.
- Insufficient data quality for automated structural analysis.
In contrast, PIX4Dcatch produced stable and detailed results by combining photogrammetry with smartphone LiDAR data. This hybrid workflow made it possible to capture even thin reinforcement bars with fewer gaps and less data loss.
Another important advantage was the ability to complete measurements without ground control points.
On active construction sites, reinforcement cages are assembled quickly, and placing physical markers can interrupt the workflow or become impractical.
With PIX4Dcatch, the operator simply walks around the reinforcement cage with a smartphone to generate a dense point cloud without stopping ongoing construction activities.
Point cloud data captured with PIX4Dcatch using a combination of photogrammetry and smartphone LiDAR.
Project workflow
The implemented workflow consisted of four main stages:
- Data capture: The operator scanned the reinforcement cage using PIX4Dcatch on an iPhone Pro.
- Processing: A point cloud was generated automatically in PIX4Dcloud.
- Model cleaning: Unnecessary points, background objects, and noise were removed from the dataset.
- Analysis: The cleaned model was imported into Modely for automated reinforcement recognition, geometry verification, and report generation.
This approach enabled a rapid transition from field data collection to engineering analysis and structural quality control.
Automated detection of rebar hoops.
Detection of the main reinforcement bars within the reinforcement cage.
Project scale
The digital inspection workflow was used to control 129 reinforcement cages for bored piles forming the foundation of a railway viaduct.
Conceptual visualisation of the railway viaduct foundation with 129 cast-in-place piles inspected during the project.
Reduction in photographic documentation
The digital workflow significantly reduced the number of photographs required for each reinforcement cage.
- Before implementation: 81 photographs per cage × 129 cages, for a total of 10,449 photographs.
- After implementation: 39 photographs per cage × 129 cages, for a total of 5,031 photographs.
This reduction simplified data management, image sorting, documentation, and report preparation.
Time savings
- 56% reduction in inspection time per reinforcement cage.
- Approximately 850 working hours saved across the project.
- This was equivalent to approximately 106 person-days.
By reducing manual operations such as photographing, measuring, sorting images, and preparing reports, the digital workflow significantly lowered the workload of engineering personnel.
Advantages of the digital workflow
The combination of PIX4Dcatch and Modely created a workflow that provides:
- Consistent measurement accuracy.
- Reproducible inspection results.
- Fast data capture using a standard smartphone.
- Point cloud generation without complex surveying equipment.
- Automated recognition of reinforcement elements.
- Geometry verification based on a digital model.
- Faster preparation of inspection reports.
- Reduced dependence on manual measurements and photo sorting.
- Minimal disruption to construction work on site.
Conclusion
The implementation of 3D reinforcement inspection using PIX4Dcatch demonstrated that mobile photogrammetry can become an effective part of digital transformation in the construction industry.
The combination of PIX4Dcatch and Modely provides a practical workflow for collecting, processing, and analysing reinforcement data with less manual work and more consistent results.
This approach is particularly effective for structures with standardised reinforcement layouts, such as bored piles, and has the potential to be expanded to more complex infrastructure projects.
Futurology is an official distributor of Pix4D software. Pix4D products are available through the Futurology dealer network in the United States. For more information, please contact info@futurology.tech.
