At the intersection of artificial intelligence (AI) and LiDAR (Light Detection and Ranging) lies a transformative technology that is reshaping how industries capture, process, and analyze geometric data. With our state-of-the-art AI algorithms, we’ve enhanced the extraction of features from point cloud data, delivering unparalleled accuracy and efficiency.
LiDAR is a remote sensing method that uses laser light to capture precise 3D information about the environment. LiDAR sensors emit laser pulses and measure the time it takes for them to return after hitting a surface. The result is a vast point cloud dataset (consisting of millions of survey points) that provides detailed representations of the surrounding environment.
While LiDAR provides rich datasets, extracting information from point cloud data can be daunting due to its size and complexity. Traditional methods of feature extraction often involve labor-intensive manual processes and can lead to inconsistencies, inaccuracies, and delays in project timelines. Off-the-shelf tools are not robust enough.
At Reflektar, we have developed cutting-edge AI algorithms specifically designed to automate the extraction of features from point cloud data.
Our algorithms have been trained using deep learning technology to learn complex patterns and relationships with the different data classes. The algorithms explore every point in the hundreds of thousands of points collected by the LiDAR system and classify the point into a specific road or roadside feature. These models can be used for noise removal and full classification of point cloud into road features.
Unlock the potential of AI and LiDAR for your projects with Reflektar. Our industry-leading algorithms and innovative solutions empower you to make informed decisions, improve operational efficiency, and drive successful outcomes.
