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Browse the recommended Neara modules to meet your needs

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processing

Process and classify noisy LiDAR

AutoProcessing

Neara AutoProcessing ingests unclassified and noisy LiDAR and returns a fully classified and denoised dataset.

Runs on the cloud which allows for multiple datasets to be automatically processed in parallel efficiently
Classify data sets the size of Texas within days
The ML model is trained on thousands of datasets and across a variety of features for rapid classification suitable for a variety of industries
Auto classification improves over time with ML accuracy and speed

vectorization

Auto generate a 3D vector model

Vectorization

Neara automatically generates a 3D vector model from a classified point cloud dataset, and intelligently reclassifies LiDAR based on heuristics and relationship to the model.

Cleanly extract pole and cable vectors, even where LiDAR coverage is poor
Use the vectors to also perform automatic LiDAR classification QA, such as reclassifying all false positive conductor and pole points outside of the vectors
Leverage intelligent and customizable algorithms to automate the QA/QC of LiDAR to solve for dataset-specific challenges
Perform QA/QC automatically at-scale, including providing LiDAR coverage/quality metrics to inform future data capture requirements