Persistent Ventures Inc.

Published purpose

The Modelar 3D mapping system uses inexpensive mobile devices (iPhones and iPads) with LiDAR sensors to quickly scan areas and create 3D point clouds and triangulated meshes in real-time. It can then upload the resulting information to a cloud management system to manage, organize, and visualize the collected data. The 3D point clouds and meshes that Modelar now collects are inherently useful, but augmenting them with spatially referenced annotations, high-resolution imagery, video and audio would make them more valuable for inspection workflows. We propose to enhance Modelar so that it can collect this data in the field, manage it in the cloud, and extract meaningful content from it using machine learning.