FOCUS AI

Important results from the project

Through the project, we have been able to confirm that it is technically feasible to use a combination of FMCW LiDAR and AI to detect and classify objects, so-called FOD, on airport aprons. The results of the project show that the system is capable of meeting its primary goal: to reliably identify objects that may pose a risk to aircraft. This results in safer environments for personnel and for the aircrafts, improved punctuality and reduced environmental impact.

Expected long term effects

ADB Safegate expects the results of the project to strengthen the company´s position as a world leader in airport parking automation. For the aviation industry, it is expected to lead to more efficient movements and less environmental impact.

Approach and implementation

The project faced early challenges in the form of staff turnover, which led to initial delays. Another complicating factor was accessibility, as the project was carried out at an active, operational airport and staging area. It was challenging to collect sufficient amounts of data to produce reliable AI models. However, we managed to accelerate the project, including through the use of synthetic data, and ultimately managed to meet most of the goals.