Vision-Based System Identification of the Fatih Sultan Mehmet Suspension Bridge

An academic research project successfully applying computer vision-based system identification to a major suspension bridge from a remote observation point. Modal parameters were identified using video recordings captured approximately 1 kilometer from the structure, demonstrating the feasibility of extracting structural dynamic properties without physical sensor installation. 

The project tested novel measurement methodologies under real-world conditions on a structure where traditional monitoring would be complex and costly. This work advanced understanding of vision-based monitoring capabilities and limitations for large-scale infrastructure, including the practical constraints of measurement distance, environmental factors, and equipment requirements.