Integrated Automated Reality Capture and Progress Tracking

Progress monitoring in construction sites is a highly manual process. With the large number of stakeholders involved in a project – developers, sub-contractors, suppliers, and engineers – challenges in collecting data and tracking processes not only result in unnecessary delays and costs, but also difficulties tracking errors in works. That can in turn lead to deviations from planned designs.

In greenfield construction, the project design is developed using a Building Information Modelling (BIM) model, which sub-contractors adhere to when carrying out works. While 3D LiDAR scanners can be used to facilitate progress tracking, the post-processing and report generation stage remains a manual process. 

For brownfield projects, challenges arise due to missing or inaccurate 2D drawings, especially for older structures. When this happens, engineers resort to multiple site walks to verify equipment and devices on site. While reality capture technology can automate this process, there is currently no way to convert the collected point cloud data into detailed 2D floor plans. 

Most commercially available tracking solutions focus on specific tasks or stages in the process, without offering users a seamless experience end-to-end, from data capture to report generation. A fully integrated platform for automated reality capture, data processing, and reporting can streamline project management, save resources, and empower all stakeholders.

Exyte Singapore is looking for an integrated, automated, fast, end-to-end system for reality capture and progress tracking in factory construction sites.

The integrated solution should encompass data capture, point cloud stitching, post-processing, deviation identification, clash prediction, and report generation. The solution should: 

• Seamlessly integrate with various scanning robots such as wheeled or legged robot (e.g., Boston Dynamic, AgileX Scout 2.0) ensuring compatibility and adaptability across different robotic platforms.
• Enable robots to autonomously navigate in a factory environment using predefined way-points;
• Enable efficient and accurate automated post-processing of 3D point cloud data obtained from the scans such as auto registration and auto denoising (people removal, temporary works removal if have reference BIM model, outliers noise interference) of point cloud data;

For greenfield projects:

• Calculate deviation differences between planned and actual elements and perform a thorough analysis of variations between planned and actual elements within a BIM mesh and point cloud, ensuring a minimum 5-millimetre precision. Include calculation of variances, incorporate a difference feature for each point, and deliver a comprehensive deviation analysis in a PDF report; and 
•  Identify potential clashes based on current deviations, considering the original clash-free model, in other words highlighting how deviated as-built elements will impact elements that have yet to be built.

For brownfield projects:

• Automatically generate a 3D BIM model based on the collected point cloud data, with the option to generate 2D floor plans based on this 3D BIM model;
• Automatically identify general components, such as fire extinguishers and other equipment, based on point cloud data; and
• Precisely measure the distances between individual components and represent them accurately on the generated floor plans.

Please download a document (PDF) containing details of detailed requirements of data capture and point cloud stitching, post-processing and deviation identification, clash prediction, and report generation.

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Exyte Construction has identified a testbed site at an existing pharmaceutical facility construction site (around 7,900 sqm in Gross Floor Area).  

Exyte will also provide the necessary expertise and manpower support for the project.