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

Abstract

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.

Structural Reliability Estimation with Participatory Sensing and Mobile Cyber-Physical Structural Health Monitoring Systems

“…Previously, it has been shown that actual crowdsourcing results (results from uncontrolled citizens) matched well with the reference identification results [32]. These uncertainties are extensively studied in [48] including spatiotemporal variation of a citizen sensor [33], phone orientation which is subjected to change before, during, and after the measurements [34], and biomechanical distortions caused by human nature [50]. Therefore, in this paper, the main focus is on uncertainties induced by ground motions and FE model parameters.…”

“…The authors' previous works present the first vibration-based SHM system (CS4SHM) using crowdsourcing power [32] and offer multisensory solutions to citizen-induced errors by considering spatiotemporal [33] and directional [34] uncertainties. Without any prior engineering education and background, citizens as uncontrolled SHM device operators can provide a central server system with ubiquitous vibration data.…”

Biomechanically influenced mobile and participatory pedestrian data for bridge monitoring

“…31,32 Likewise, in smartphone-based SHM systems, it is expected that the monitoring results are significantly affected by the uncontrollable sensing environment due to crowdsourcing initiatives. 27 These initiatives can result from pedestrian identity (height, weight, age, gender, etc.…”

“…26,27,31,32 Potential pedestrian postures and activities on a civil infrastructure are unlimited; therefore, only few common scenarios are tested in this study which include the following: smartphone (1) directly attached to the bridge deck surface, (2) resting in a bag on the deck, (3) in a pedestrian's pocket, and (4) in a backpack carried by a pedestrian. Table 1 summarizes the variation sources in structural vibration data extracted from pedestrians, sources of uncertainties, positive and negative extremes in sensing conditions.…”

“…Nevertheless, the modal identification results even under extreme sensor mobility match the reference operational modal analysis studies of the bridge conducted repetitively in the past. 27,31,32 The basic principle in the proposed platform is that modal parameters are sensitive to structural damage.…”