6 Problems That Can Be Solved with Point Cloud Processing Software
Point cloud processing software is used in a wide range of industries to transform data from LiDAR surveys into digital 3D models. But the software doesn’t just bring data to life; it also solves many of the problems that arise when working with point cloud data.
Here are six of the problems that can be solved simply by using point cloud processing software.
1. Storing Point Cloud Data Is a Struggle
One of the first challenges you’ll need to overcome when working with point cloud data is finding a suitable storage solution and how to access it. Point clouds store a lot of detailed information, so file sizes are usually too large for laptops, desktop computers, and even some external hard drives. Large projects, in particular, can result in huge datasets, as they may require data from multiple scans.
Storing point cloud data can be a struggle — unless you have point cloud processing software that can access your storage facility with ease like TopoDOT, which includes an administrator called TopoCLOUD. This neat little tool smooths out the process from the point cloud software and the storage facility.
2. Difficulties in Collaboration
Sharing large point cloud data files can be even more difficult than storing them, which can interfere with collaboration. Analyzing point cloud data isn’t a one-person task — team members, engineers, architects, and urban planners may also need to assess the data.
Using a point cloud processing software to access, organize, and analyze data means teams can easily collaborate without overriding other team members’ processing work.
Project managers can easily share project data with team members so that users can access, download, and visualize point cloud data. When teams are working on large projects, project managers can delegate the analysis of datasets to these teams or individuals.
3. Concerns about the Accuracy of Data
Before point cloud data can be used to plan construction, architectural, or engineering projects, its data quality needs to be assessed. Point cloud processing software can be used to assess the alignment of pixels between the point cloud data and the images produced.
Multiple point cloud scans of the same area may also overlap, so processing software can also assess the alignment between overlapping point cloud areas.
4. Poor Project Cost Estimates
Before beginning a point cloud survey, some point cloud processing software will include highly automated tools that allow you to plan terrestrial LiDAR scans and even estimate the cost of the survey.
The data gathered during point cloud surveys can help project managers accurately calculate the cost of the overall project. Point cloud processing software can identify buildings, transport corridors, or facilities that need improving, along with the cost of necessary construction work.
By calculating accurate project cost estimates, there’s a reduced risk of projects going over-budget. Unexpected costs cause financial difficulties, which may disrupt projects half-way through completion, delay them, or even prevent their successful completion. With an informed idea of project costs, accurate decisions and predictions can be made regarding the project and its outcome.
5. Processes Aren’t as Productive or Profitable as They Should Be
Working with point cloud data can involve complex analysis that takes time and manpower. Without the right tools, it can be difficult to extract the maximum value from your point cloud data and deliver the products your customers need.
However, with point cloud processing software, you can easily optimize your processes. The need for labor is reduced and point cloud data can be analyzed in a fraction of the time.
By streamlining processes and delivering quality products quickly, you’ll also increase your revenue. You’ll be able to take on more projects and, ultimately, improve your return on investment.
6. The Safety of Survey Teams
Laser scanning technology means surveys can be carried out quickly and efficiently. With point cloud processing software, the data collected during surveys can be analyzed from the safety of an office or laboratory. This means survey teams spend less time in the field, including in potentially dangerous environments like highways and railroads.
