Sillan

Transport infrastructure is critical to economic growth, mobility, and public safety. However, bridges and roads deteriorate over time due to aging, environmental conditions, and increasing traffic loads. In Finland alone, 260 million euros are spent annually on bridge maintenance and repairs, yet the maintenance backlog continues to grow as bridges continue to age and repair demand increases.

Traditional infrastructure maintenance methods, such as visual inspections and direct sensing are limited in scalability. Visual inspections are periodic, labor-intensive, and often inefficient, while direct sensor systems, which typically rely on fixed sensors installed on structures, are effective but costly. As a result, they are mainly deployed on long-span or high-priority bridges. This leaves the majority of short- and medium-span bridges, representing most of the infrastructure network, without continuous monitoring. This gap increases the risk of undetected deterioration in critical infrastructure. 

SILLAN introduces a novel solution: a vehicle-based bridge monitoring and damage detection system. By leveraging sensors installed on moving vehicles, the system enables continuous assessment of bridge structural condition without the need for direct sensor installation. This approach offers a cost-effective, scalable, and lightweight alternative, particularly suited for regions with aging infrastructure, such as Finland and across Europe.

The research done at SILLAN focuses on developing a comprehensive framework for vehicle-based Structural Health Management, integrating advanced machine learning techniques to improve the accuracy and automation of damage detection. Our goal is to create a robust and scalable monitoring system that enhances infrastructure safety and resilience, especially in regions with aging bridge networks.