Technology plays a significant role in managing, creating, and maintaining the built environment. While it’s understandable that we tend to focus on rapidly evolving hardware technology and gadgets, we should not underestimate how many relatively unnoticed advances have culminated in significant changes, creating new best practice.
The maturity of reality capture hardware has made it possible for software developments to lead the way. Robust standardisation of hardware capabilities, ranging from stationary LiDAR scanners to GPS-enabled mobile devices, has led to an explosion of data and new software choices.
The real value of reality capture lies in providing information that allows you to make informed decisions and, ultimately, keep projects on-time, on budget, and in specification. Let's look at some of the applications where 3D reality capture is making a real difference within the construction industry.
Suggested reading: If you want to learn more about the software advances that have improved accessibility of reality capture technology, check out our ebook — Point Cloud Processing Has Changed.
The adoption and development of Building Information Modelling (BIM) has increased the ROI of investing in reality capture technologies by improving accessibility to scan data across a construction project.
Scan-to-BIM is typically used on projects where details of an existing building need to be captured, such as renovations. However, it has also proven useful in new build projects to create a record of the existing context and structures, along with simplifying planning in restrictive or hazardous environments — bringing a number of different benefits.
The "to-BIM" part of Scan-to-BIM is important to keep in mind. It transforms disparate point clouds into an intelligent 3D model of the entire project — and creates a platform for building on those scans with additional annotations and details. However, not all BIM is the same. Only database-first BIM Level 3 can deliver improved construction workflows needed to maximise the ROI of scan-to-BIM strategies, and effectively provide access to scan data across your team. For more information on BIM, check out our ebook — The Ultimate Guide to BIM.
Effective and agile deployment of laser scans within a Scan-to-BIM context also requires investing in registration software that can accelerate your workflows and automate the registration process — more on that in the next section.
2. BIM-to-Field
Optimised BIM application requires integrated scanning of the site throughout the whole construction process. This is to ensure the real world is represented in the model and vice versa. BIM-to-Field is the mirror image of Scan-to-BIM. Data is downloaded, validated on-site using scanners, and then fed back into the model. This enables:
BIM-to-Field workflows require a lot of scanning. To effectively deploy reality capture technology to cross-check outputs with planning, you need reality capture solutions that are fast, agile and automated. At Vercator, we’ve developed cloud-enabled point cloud processing software able to significantly accelerate scan registration using a patented vector-based and multi-stage registration algorithm. Start a free trial of Vercator to learn more. However, there are some broader points that you can use to judge the efficacy of any point cloud processing software.
With this context in mind, you then need to create workflows that enable you to capture the information required. This basic process requires you to:
Reality capture is becoming even faster and more accessible, and SLAM (Simultaneous Localisation and Mapping) is an excellent example of this. Primarily, SLAM is quick and easy. Compared to traditional static laser scanners, SLAM-enabled scanners' mobile nature delivers far simpler and accelerated workflows.
A significant benefit of SLAM in 3D reality capture comes from repetition. It’s fast and easy, so it’s possible to use it repeatedly across the lifecycle of a project. The more often an area is mapped, the more current the data is, and the more valuable it is. Wearable scanners are hugely attractive to up the scanning rate, especially if there might be safety, access or security issues to consider. Mobile scanning can even be deployed by autonomous robotics — for example, Doxel.
The challenge with SLAM is accuracy. Mobile scanning introduces an additional variable, and that limits the precision of the scans that can be produced. SLAM is most effectively deployed where rougher scans can be used, and structured measurements don’t need to be taken based on that data.
In order to effectively deploy SLAM (and mobile scanning more generally), you need software that’s able to combine mobile scanning outputs with the outputs of static scanners. Again, this is an area of significant development within the industry, and one that we are pioneering at Vercator.
Suggested reading: If you want to learn more about SLAM, and how it can be used in conjunction with other datasets, check out our ebook — How SLAM Enables the Evolution of Wearable Reality Capture Technologies.
"We tend to overestimate the effect of a technology in the short run and underestimate the effect in the long run" — Roy Amara
The future is nearer than we think. Automation and robotics are already impacting construction, and reality capture sensors are already generating vast quantities of data that can be turned into actionable information.
The key to success in reality capture is figuring out why you need data, what data you need, how best to capture this, and how you plan to use it. By deploying cloud-based software, you have the means to coordinate the complete range of scanning technologies to form a full interpretation of a site or environment. Check out our guide to 3D Laser Scanning Software to learn more.