AURA

INTEGRATED PROCESSING AND VISUALIZATION SOFTWARE

SIMPLIFYING 3D LASER SCANNING WORKFLOWS FROM CAPTURE TO INSIGHT

Emesent Aura allows the processing and visualization of scans in one intuitive platform, streamlining the way Hovermap users process, view, and analyze point clouds for faster insights and improved decision-making.

SLAM-based mapping is known for its speed, ease of use, and ability to capture shadowless, dense point clouds. As use cases grow and point cloud sizes increase, efficiently processing, viewing, and analyzing the data becomes challenging.

STREAMLINED PROCESSING. POWERFUL VISUALIZATION. SIMPLIFIED ANALYSIS

TAKE A CLOSER LOOK

A SINGLE, STREAMLINED APPLICATION WORKFLOW

Don’t waste time switching between applications to process and view your data. Aura consolidates it all in one platform, with the ability to export to widely-used industry file formats and CAD packages.

VISUALIZE EVERY DETAIL - EVEN FOR COMPLEX ASSETS

Multi-Frame Rendering efficiently visualizes your point cloud in the highest detail, no matter how dense the points or complex the asset, giving you deeper insights.

PROCESS, VISUALIZE, AND ANALYZE SIMULTANEOUSLY

Aura gives you the ability to toggle between open point clouds, so you can work on multiple scans at the same time as you are processing, improving efficiencies and saving you time.

RELIABLE, HIGH QUALITY PROCESSING

Processing powered by the world’s leading SLAM algorithm converts your data into highly detailed, accurate point clouds.

INTUITIVE AND RESPONSIVE INTERFACE

Aura’s simple navigation and intuitive workflows make it easy for users of all levels to process, visualize, analyze and export their data.

WHY USE AURA

OPTIMIZED VIEWING OF HOVERMAP’S HIGH DENSITY DATASETS

Aura excels at displaying the dense, detailed point clouds produced by Hovermap, even for extremely large datasets with billions of points. Emesent’s proprietary Multi-Frame Rendering algorithm ensures crucial point cloud details are rapidly displayed in high definition for improved decision-making.

PACKED WITH FEATURES TO SAVE YOU TIME

Emesent Aura makes your workflow seamless and hassle free no matter how large or numerous your datasets, dense your point clouds, or complex your 3D structures. Job queueing allows for set and forget batch processing of files, and customized profiles provides scan processing with minimal configuration.

IMPROVE OUTPUT QUALITY AT THE PUSH OF A BUTTON

Clean your point cloud at the touch of a button with SOR (Statistical Outlier Removal) and DBD (Decimate by Distance) filters. Georeference your point cloud with confidence, thanks to Automated Ground Control alignment (optional) and accuracy reports. Easily export high resolution screenshots for faster stakeholder buy-in.

FASTER TIME TO INSIGHT WITH A SINGLE SYSTEM

Process, view, clean, and edit Hovermap point clouds in a single streamlined application. Take measurements and easily manipulate the point clouds with a range of 3D tools. Automate previously manual and error prone tasks to improve the quality of analysis, remove the risk of error and improve analysis.

AUTOMATED GROUND CONTROL

Aura’s Automated Ground Control is an innovative feature that further increases the accuracy of Hovermap point clouds and enhances the capabilities of its SLAM-based mapping. Automated Ground Control enables new use cases, including long, large, and feature-poor assets such as roads, stadiums, and tunnels – previously a challenge for SLAM-based mapping.

Using machine learning, GCP automatically detects reflective ground control targets and uses these to both georeference the point cloud and improve accuracy. After running Automated Ground Control, you can validate your target alignment with a GCP Accuracy Report.

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COLORIZATION

Aura provides Emesent’s best-in-class colorization for deeper environmental insights. Augmenting point clouds with true color provides additional context, more clarity, and realism to achieve greater insights across a variety of applications, revealing previously hidden details in your critical infrastructure.