3LC has announced a strategic partnership with Norwegian robotics firm Roboxi to develop AI-powered runway inspection systems designed to improve airport safety and operational efficiency.
The collaboration will focus on automating runway inspections and maintenance workflows using artificial intelligence and computer vision technology, allowing airports to identify potential hazards more quickly and accurately.
The partnership follows a successful proof-of-concept project centred on autonomous runway light detection, an area considered critical for airfield safety operations.
AI tools improve inspection accuracy
During the pilot programme, 3LC worked with Roboxi to enhance the performance of its autonomous inspection model by improving the quality of training data used by the system.
According to the companies, the project demonstrated how data-centric AI workflows could strengthen real-world inspection systems used in critical airport infrastructure.
Using 3LC’s analysis and labelling platform, engineers identified issues including missing labels, incorrect bounding boxes and inconsistent annotations within the dataset used to train the runway inspection model.
The companies said more than 2,000 missing bounding boxes were corrected during the process, while class-labelling inconsistencies were also resolved through active learning techniques.
As a result, the runway light detection model’s performance improved by more than 50% in under a week.
Growing use of automation in aviation
Autonomous inspection systems are increasingly being explored across the aviation industry as airports seek to improve safety standards while reducing manual workloads and operational disruption.
Runway inspections are traditionally labour-intensive and require regular checks for lighting faults, foreign object debris and surface damage.
By combining robotics with AI-driven image recognition, companies hope to enable continuous monitoring and faster identification of potential risks.
3LC said the partnership would allow Roboxi to continue refining its inspection systems through ongoing model and data improvements.
The companies added that the technology could eventually support broader airport maintenance and operational functions as demand for automation grows across the aviation sector.
