Advancing Pavement Monitoring for Sustainable Airport Infrastructure

In this project we are focusing on real-time monitoring of pavement performance and structural integrity at Stockholm Airport, addressing the unique challenges posed by heavy aircraft and Sweden's rigorous climate.

Traditional methods for monitoring airport pavement conditions have limitations in detecting early signs of damage or structural issues. To overcome these challenges, we have integrated advanced sensors based on optical fibers and self-powered miniaturized electrical sensors into the pavement structure, enabling real-time, data-driven decision-making to improve runway efficiency, sustainability, and safety.

By validating collected data through conventional testing methods and comparing results with sensor measurements, we will develop a framework to analyze pavement behavior and predict performance. This will involve applying mechanical models and developing machine learning methods to create pavement health indicators using both mechanical models and sensor measurements. Ultimately, we will propose a sustainable pavement solution strategy based on the research results. This project offers a unique opportunity to validate research at an airport scale, where sensors must withstand various weather conditions and endure stress over extended periods.