Shared micromobility-driven modal identification of urban bridges

Recent research in Indirect Structural Health Monitoring (ISHM) uses the dynamic response of instrumented vehicles to carry out “drive-by” monitoring of bridges. These vehicles are generally cars or trucks instrumented with different types of sensors. However, some urban bridges are inaccessible to regular vehicles. Also, cars and trucks have non-negligible weight and suspension systems that may affect the collected vibration data. Stiff, light, and standardized shared micromobility vehicles, such as bicycles and electric kick scooters, have never been explored for ISHM purposes. This paper proposes an innovative and automatic ISHM strategy based on the data collected by smartphones temporarily installed on shared micromobility vehicles. An identification procedure suitable for cloud computing is proposed to extract the dynamic parameters of bridges without needing any sensor deployment, becoming particularly appealing for monitoring a densely built environment at a territorial scale. The methodology is applied to a real footbridge in Bologna (Italy). •Crowdsourcing from human-powered vehicles is first employed for bridge monitoring.•Cloud-based platforms can gather and process crowdsourced data automatically.•The Kalman filter is used to fuse smartphone data and identify modal parameters.•A smartphone deployed on a city bike is employed to collect IMU and GPS data.•The first natural frequency and absolute mode shape of a footbridge are identified.