Direction-sensitive smart monitoring of structures using heterogeneous smartphone sensor data and coordinate system transformation

Mobile, heterogeneous, and smart sensor networks produce pervasive structural health monitoring (SHM) information. With various embedded sensors, smartphones have emerged to innovate SHM by empowering citizens to serve as sensors. By default, smartphones meet the fundamental smart sensor criteria, thanks to the built-in processor, memory, wireless communication units and mobile operating system. SHM using smartphones, however, faces technical challenges due to citizen-induced uncertainties, undesired sensor-structure integration, and lack of control over the sensing platform. Previously, the authors presented successful applications of smartphone accelerometers for structural vibration measurement and proposed a monitoring framework under citizen-induced spatiotemporal uncertainties. This study aims at extending the capabilities of smartphone-based SHM with a special focus on the lack of control over the sensor (i.e., the phone) positioning by citizens resulting in unknown sensor orientations. Using smartphone gyroscope, accelerometer, and magnetometer; instantaneous sensor orientation can be obtained with respect to gravitational and magnetic north directions. Using these sensor data, mobile operating system frameworks return processed features such as attitude and heading that can be used to correct misaligned sensor signals. For this purpose, a coordinate transformation procedure is proposed and illustrated on a two-story laboratory structural model and real-scale bridges with various sensor positioning examples. The proposed method corrects the sensor signals by tracking their orientations and improves measurement accuracy. Moreover, knowing structure's coordinate system a priori, even the data from arbitrarily positioned sensors can automatically be transformed to the structural coordinates. In addition, this paper also touches some secondary mobile and heterogeneous data issues including imperfect sampling and geolocation services. The coordinate system transformation methods proposed in this study can be implemented in other non-smartphone-based SHM systems as long as similar instrumentation is available.