Important results from the project
The project´s objective was to use AI to analyze 3D lidar data to detect and classify vehicles and people at entrances. Initially, AI methods were tested, but these offered no clear advantage over numerical methods that performed equally well, sometimes better, for low-level analysis and object classification, while requiring less computational resources. However, AI is very valuable at a higher level – for example, to interpret patterns, detect anomalies or draw conclusions over time.
Expected long term effects
This project has been an excellent example of how from a single input and a single sensor you can increase security while monitoring quality parameters. These areas are often completely separate today. Now we can provide increased control and awareness of what is happening on a site in an integrity-friendly way.
Approach and implementation
The project was carried out with the participants Flasheye and Mobilaris Industrial Solutions.
Flasheye was responsible for the part of analyzing data from 3D sensors while Mobilaris Industrial solution was responsible for the part of how to present and analyze events at entrances. At the end of the project, we had a joint demo that shows all the information that was previously not available that contributes to increased safety and control at entrances.
External links
The project description has been provided by the project members themselves and the text has not been looked at by our editors.
