<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>The paper describes a system approach to use LiDAR sensors for capturing dynamic point cloud data in industrial process environments and to interpret the captured scenes with AI based object detection. The object detection is used to distinguish between humans and other mobile objects in safety relevant workspaces. Several AI methods relevant for such application are analysed. One method is applied with annotated test data and evaluated concerning its accuracy.</p>
</abstract>

The paper describes a system approach to use LiDAR sensors for capturing dynamic point cloud data in industrial process environments and to interpret the captured scenes with AI based object detection. The object detection is used to distinguish between humans and other mobile objects in safety relevant workspaces. Several AI methods relevant for such application are analysed. One method is applied with annotated test data and evaluated concerning its accuracy.

Lidar and AI Based Surveillance of Industrial Process Environments

Transport and Telecommunication Journal

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

{"article-title":"Lidar and AI Based Surveillance of Industrial Process Environments"}

The paper describes a system approach to use LiDAR sensors for capturing dynamic point cloud data in industrial process environments and to interpret the...

Lidar and AI Based Surveillance of Industrial Process Environments

Online veröffentlicht: 28. Feb. 2023

Seitenbereich: 13 - 21

DOI: https://doi.org/10.2478/ttj-2023-0002

Schlüsselwörter
LiDAR, dynamic 3D point cloud, object detection, AI, industrial application, synthetic data

© 2023 Maik Groneberg et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Lidar and AI Based Surveillance of Industrial Process Environments

Online veröffentlicht: 28. Feb. 2023

Seitenbereich: 13 - 21

DOI: https://doi.org/10.2478/ttj-2023-0002

SchlüsselwörterLiDAR, dynamic 3D point cloud, object detection, AI, industrial application, synthetic data

© 2023 Maik Groneberg et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Schlüsselwörter
LiDAR, dynamic 3D point cloud, object detection, AI, industrial application, synthetic data