Trimble Business Center (TBC) is Trimble’s CAD software for turning various types of spatial field data into information and client deliverables. The latest version of Trimble Business Center, Version 2023.10, introduced a new AI-based feature extraction technique that lets users train their own region classes, allowing for highly accurate and customizable feature extraction. This feature combines algorithmic rulesets with AI-based deep learning.
Completing laser scanning projects faster
A recently published blog post on the website of Trimble Geospatial describes how these features add value to collected data. The integration of AI in TBC is another industry example where “smart” software is able to perform repetitive and tedious tasks normally executed by humans. In this case, the software is able to perform point cloud classification and feature extraction by itself, so humans don’t have to.
Point cloud classification is a process where individual points are labeled into different categories such as ground, vegetation and buildings. Feature extraction identifying and extracting essential information from point cloud data, such as shapes, objects, and patterns. The new automated classification and feature extraction workflows in TBC are based on a combination of AI techniques, including 3D and 2D deep learning, and provide high-quality data.
More on-site productivity through AI
The blog entry further describes how one of Canada’s most established land surveying and geomatics firm, Geoverra, uses TBC with AI capabilities is the standard software to perform feature extraction from point clouds/imagery collected with mobile mapping, systems, scanners and drones. It is also their software of choice to create deliverables such as CAD and 3D files, pavement assessments, databases and GIS. The blog entry also explains how Severino Trucking, an earthworks site contractor based in New Hampshire, uses TBC for site modeling and quantifying stockpiles on construction sites.
In yet another Trimble blog, Technical Product Manager for 3D laser scanning software Jeff Turgeon explains how on-site productivity for laser scanning products is optimized further through multiple technological advancements, including AI-assisted segmentation and the new Deep Learning Point Cloud Classification tool. He states that the latest edition of Trimble Dimensions showcased several advancements in areas of artificial intelligence (AI), cloud- based environments and inter-software connections, and that new technical advancements will further reduce the time required to complete laser scanning projects while unlocking more of the data collected.
