Harnessing AI for Predictive Pavement and Marking Maintenance at Airports

Abstract: Airports face constant pressure to maintain safe and efficient operations, and the condition of their pavements—runways, taxiways, and access roads—is critical to ensuring both safety and operational continuity. Traditional methods of inspecting pavement surfaces and maintaining runway and taxiway markings involve manual inspections, which are costly, time-consuming, and prone to delays. With increasing traffic, airports need faster, more reliable methods to monitor infrastructure health.
By leveraging artificial intelligence (AI) and real-time visual data from existing camera systems and high-resolution dash cameras, airports can revolutionize the way they maintain critical pavement and marking infrastructure. Blyncsy’s AI-driven platform enables airport operators to monitor runway conditions, detect cracks, potholes, and fading paint lines across large areas without the need for manual inspections. This not only reduces the risks associated with on-site inspections but also allows for predictive maintenance planning that ensures runway conditions meet strict safety standards.
The ability to detect and respond to pavement issues in real-time leads to safer operations, fewer runway closures, and significant cost savings for airports. Furthermore, the technology allows for seamless integration with existing airport workflows, delivering actionable insights directly to operations teams in minutes. This ensures timely interventions before issues escalate, ultimately reducing the likelihood of expensive repairs and downtime.
As AI and computer vision technologies advance, airports can now automate what was once a reactive process, significantly enhancing their safety and operational efficiency. With the predictive power of AI, airports can improve the longevity of their pavements and markings, reduce overall maintenance costs, and optimize safety for travelers and airport personnel alike.
This presentation will demonstrate how airports can integrate AI-powered pavement monitoring to manage and prioritize maintenance tasks, ensuring safe and smooth operations while saving time and resources.