Solving Point Cloud OBJ Upload Issues! Improve Work Efficiency with Cloud Usage

Table of Contents

• Introduction

• What are point cloud data and the OBJ format

• Challenges when uploading point cloud OBJ files

• Solutions using the cloud

• Benefits of improved work efficiency through cloud usage

• Point cloud utilization and simple surveying supported by the latest technologies

• Simple surveying with LRTK

• Conclusion

• FAQ

Introduction

In recent years, digitalization of operations has advanced across various industries including construction and civil engineering, and "point cloud data," a high-precision three-dimensional measurement dataset, has been attracting attention. Point cloud data acquired by laser scanners or photogrammetry are digital copies that accurately record real-world space as countless points. By leveraging this faithful on-site information, many benefits can be obtained such as improved design and construction accuracy and faster consensus building. However, point cloud data files are extremely large, and if they are not shared and managed properly, their value cannot be fully realized.

The key to this is cloud usage. If point cloud data (and in some cases 3D models in OBJ format) are uploaded to the cloud and shared, all stakeholders can view the same up-to-date 3D information regardless of location. For example, if you share point clouds of a construction site via the cloud with the owner or designers, you can prevent rework caused by misunderstandings like "this is not what I expected," thereby reducing unnecessary redo work.

This article explains the challenges associated with uploading point cloud OBJs and how using the cloud can solve those challenges and greatly improve work efficiency.

What are point cloud data and the OBJ format

Point cloud data are three-dimensional datasets that record real-world spaces such as buildings and terrain as a collection of many points. Each point contains X, Y, Z coordinates (and sometimes attribute information such as color or reflectance intensity), and the aggregation of points precisely reproduces real-world shapes. Point cloud data measured by laser scanners can capture the current state with millimeter-level accuracy, so they are used across a wide range of fields including construction, civil engineering, surveying, and manufacturing.

On the other hand, the OBJ format is one of the general-purpose file formats for storing 3D models. It is text-based and can include geometry-centric data such as vertex coordinates, polygon (face) information, and textures. Because of its simple and easy-to-handle structure, it is supported by many 3D modeling software and CAD tools, making model data exchange between different platforms straightforward. It is, in a sense, one of the de facto standard formats in the 3D field and is also used for visualization and sharing of BIM data and point cloud data.

There is a close relationship between point cloud data and the OBJ format. Acquired point clouds are often stored in specialized formats such as LAS or PLY, but if a point cloud is converted into a polygon mesh and exported as an OBJ 3D model, it becomes easier to handle in general viewers and game engines. For example, if you generate a surface model from point clouds obtained by laser scanning and write out an OBJ file, you can view the site’s three-dimensional form in common 3D software or a browser without specialized CAD software. However, the OBJ format cannot retain the fine attribute information of point clouds (such as per-point color, reflectance intensity, timestamps), and forcefully meshing very dense data can drastically increase file size and processing load. Therefore, depending on the use case, it may be necessary to use point-cloud-specific formats or to appropriately simplify and compress models.

Challenges when uploading point cloud OBJs

The first issue encountered when handling point cloud data is the problem of file size. Dense point clouds can contain millions to hundreds of millions of points, and raw data file sizes can grow from hundreds of MB to several GB or more. Uploading or downloading such massive files over an internal network takes time and may be interrupted or fail depending on the network environment. Traditionally, data had to be shared by copying to USB drives or external HDDs and physically handing them from the site to the office, and sending point cloud OBJ files as email attachments was not even realistic.

Even if you somehow manage to share point clouds or OBJ files online, there are high barriers to subsequent viewing and utilization. Recipients must first save the large data to their own PCs, which consumes storage. Moreover, opening point cloud data often requires dedicated viewer software or a high-performance PC, making it difficult for non-specialists. For example, handing a multi-GB OBJ model to an owner or sales representative could result in problems like “I don’t have the software to open it” or “my computer freezes and won’t run it.” Consequently, valuable 3D data may not be widely shared, and teams may revert to traditional methods such as using still image captures or 2D plans for explanations.

Additionally, exchanging files among multiple members introduces the problem of complex version control. When files are transferred or copied individually, it becomes hard to know who has which version, leading to mistakes such as “design changes weren’t reflected because someone had an old model.” Also, each person keeping their own copy of large datasets wastes storage and increases the risk of data leakage. Thus, attempting to share point cloud data by conventional methods (individual PCs or physical media) raises many obstacles to effective data utilization.

Solutions using the cloud

An effective way to resolve the above challenges is using the cloud. If point cloud data or OBJ models are uploaded to an internet cloud platform instead of an internal server, data can be centralized and managed in one place. Stakeholders can access the latest data on the cloud at any time without physically distributing files. If point clouds captured on-site are uploaded to the cloud, members in remote offices can immediately view that 3D information. There is no need to mail hard drives or send personnel on site, dramatically speeding up data sharing.

Cloud services provide large-capacity storage and high-performance server environments, so users can handle 3D data directly online without downloading huge files. Many services offer browser-based viewers that allow people without specialized software to display point clouds, so non-technical stakeholders such as owners or sales staff can intuitively check the as-built model simply by opening a URL. Because heavy processing is handled on the cloud side rather than depending on the PC’s performance, it is becoming more common to smoothly manipulate detailed 3D data from ordinary laptops or tablets.

Centralized data management on the cloud also means the team can always refer to “a single latest version.” When someone updates point cloud data, it is immediately reflected on the cloud, preventing mistakes from continuing to use outdated files. Team members no longer need to hold duplicate copies, reducing wasted storage and the risk of information leakage.

By utilizing the cloud in this way, large and rich point cloud data that were previously difficult to handle can be made available on a shared platform "in a form that anyone can use." This maximizes the value of point cloud data and creates an environment where truly visualized site information can be shared and used across the organization.

Benefits of improved work efficiency through cloud usage

• Immediate site verification from remote locations: If point cloud data captured on-site are uploaded to the cloud, designers and managers in distant offices can check the data instantly. For example, if a surveyor scans the site in the morning and shares it via the cloud, the head office design team may begin drawing revisions or quantity calculations that same afternoon. Being able to proceed to the next process without waiting for travel or shipping time is a major efficiency improvement.

• Intuitive information sharing for non-technical users: With a browser-based 3D viewer, owners or members from other departments without specialized knowledge can rotate 360 degrees and freely zoom in and out with a mouse to intuitively understand the current state and plans. Because they can virtually experience their building as if in a game, mismatches like “the post-completion image was different” can be prevented. If necessary, a responsible person can share their screen while explaining, making consensus building with non-experts smoother.

• Always share the latest data: Centralized cloud management ensures the whole team always has access to the latest information. When someone updates a model, it is immediately reflected and shared on the cloud, preventing miscommunications like “I had an outdated file.” This avoids scenarios where drawings and point cloud files are scattered via email or USB, and eliminates confusion over which version is current.

• Simultaneous use by multiple members: Point cloud data on the cloud can be viewed and operated by multiple people at once. Real-time collaboration becomes easy—for example, a field representative and a designer in different locations can discuss over the phone or in an online meeting while checking the same 3D model. Decisions can be made online without everyone gathering on-site, greatly speeding up coordination tasks.

• Reduction of re-surveys and rework: By leveraging point cloud data on the cloud, additional dimension checks or clash checks can be performed from the desk, significantly reducing cases of “we need to re-measure on site.” Fully utilizing the once-captured digital data minimizes onsite verification trips, reducing personnel movement effort and costs. Early detection of clashes during construction and pre-alignment of finishing expectations also lowers the risk of later rework.

• Long-term use of data assets: Point cloud data stored in the cloud become future assets. If you save historical as-built data, it can be compared during remodeling or expansion planning several years later, and it is easy to use as reference material for similar projects. Accumulating precise point cloud records as in-house knowledge contributes to long-term improvements in operational efficiency and quality.

Point cloud utilization and simple surveying supported by the latest technologies

No matter how valuable point cloud data are, some may hesitate to adopt them thinking “we can’t handle it without expensive equipment or specialized skills.” However, recent technological advances have produced many user-friendly simple surveying tools that make 3D surveying accessible to anyone.

For example, some modern smartphones are equipped with compact LiDAR sensors, enabling 3D scanning in familiar spaces without using a dedicated laser scanner costing hundreds of thousands of yen. Solutions that automatically generate point cloud models in the cloud from drone-captured photos are also becoming practical. Combined with high-precision GNSS (satellite positioning), it is not unrealistic for anyone to acquire point clouds with survey-grade accuracy in a short time.

Thus, the era is arriving when 3D measurement, once a specialized field, can be performed with readily available tools. The conventional notion that “our company is too small” or “it requires special skills” is being overturned, and by using affordable simple surveying devices, each employee can benefit from point cloud data.

Simple surveying with LRTK

A representative example of the smartphone-based surveying solutions mentioned above is LRTK (L-R-T-K). LRTK is a device in which a high-precision GNSS receiver is attached to a smartphone or tablet; it is a revolutionary tool that enables surveying and point cloud measurement—previously requiring dedicated instruments—to be performed with “one smartphone per person.”

By adopting simple surveying with LRTK, cloud sharing of point cloud data becomes even more accessible. Without relying on expensive laser scanners or artisanal skills, site reality can be easily digitized and shared on the cloud, maximizing the aforementioned benefits of improved efficiency and reduced rework. If you are unsure where to start your company’s on-site DX, consider trying practical, easy-to-use tools like LRTK.

Conclusion

We have seen that various challenges in sharing point cloud OBJ data can be resolved by using the cloud. Centralized management of point cloud data on the cloud can drastically reduce the effort involved in data transfer and viewing, and dramatically improve the speed and accuracy of information transmission among stakeholders. As a result, on-site rework can be reduced and overall work efficiency improved, contributing to greater project productivity and quality.

Furthermore, combining the cloud with the latest simple surveying tools (such as LRTK) can make the process from data acquisition to sharing even smoother. Rapidly gathering high-precision 3D data and uploading it to the cloud will make the site digitalization and visualization that were previously difficult a normal workflow.

Cloud sharing of point cloud data and the introduction of simple surveying technologies will revolutionize business processes not only in construction but across many fields. Take this opportunity to incorporate these solutions into your operations and promote efficiency and DX (digital transformation).

FAQ

Q: Do I need special software to share point cloud data on the cloud? A: It is not always necessary to purchase expensive dedicated software. Browser-based point cloud viewers and cloud services have become abundant, and you can allow stakeholders to view uploaded point cloud data simply by sharing a URL. Cloud platforms that do not require building your own servers are available, so you can adopt them easily even without a specialized IT department.

Q: Do I need to convert point cloud data to OBJ format to share it? A: It is not necessary to always convert to OBJ for cloud sharing. Many cloud point cloud services allow direct uploading and viewing of standard point cloud formats such as LAS or E57, and some services automatically generate 3D models from photos. When handing over data in person, preparing a polygonized OBJ model may be advantageous because it is easier to display in general 3D software. However, OBJ can lose attribute information and lead to larger files, so leaving the conversion to the platform’s standard format on the cloud is often more efficient.

Q: Is it difficult for non-technical users (such as owners) to view point cloud data? A: Point cloud data itself is technical, but owners can be given intuitive access via dedicated viewers. For example, if you provide an interface that allows free viewpoint control with a mouse for a virtual experience of the building, it becomes easier for owners to understand a post-completion image that drawings alone may not convey. If necessary, a responsible person can share their screen while explaining, making it easy to communicate the current state and plans to non-experts.

Q: Is it a problem to upload very large point cloud data to the cloud? A: Point cloud data can indeed be large, but many cloud services provide virtually unlimited storage and high-performance server environments, so you can use them without worrying too much about capacity or processing speed. Placing data on the cloud also avoids burdening local PCs, allowing even very large point clouds to be viewed smoothly. However, basic precautions such as being mindful of data usage when viewing over mobile networks are still necessary.

Q: Can non-experts handle 3D scanning and point cloud sharing? A: Yes. The latest simple surveying tools are designed to be user-friendly for beginners. Devices that work with smartphone apps allow anyone to perform point cloud measurement and cloud sharing simply by following on-screen instructions. Many complex settings and adjustments are automated, so even junior staff with limited expertise can effectively use them on site. Digital-native employees often learn quickly and actively drive on-site DX efforts.

Q: I’m worried about the cost of adopting new technologies. Can I try implementing them on a small scale first? A: It is recommended to pilot on a small scale or within a single team. For example, try using a simple surveying tool like LRTK in one department to perform point cloud scanning and cloud sharing and evaluate the results. This lets you verify usefulness on site while keeping initial investment low and makes it easier to gain internal buy-in. Recent tools are less expensive than traditional equipment and may be available for rental or demo use, so consider starting within a manageable scope.