Characterizing smartphone capabilities for seismic and structural monitoring

Abstract

As seismic events continue to pose significant threats to urban infrastructure, leveraging smartphones equipped with accelerometers for real-time monitoring has gained prominence. To ascertain the reliability and sensitivity of smartphone-based measurements, an in-depth characterization of their response is essential. This article presents a thorough characterization of the performance of typical accelerometers installed on three distinct smartphone models. For this, a novel experimental apparatus has been developed to conduct a comparative study involving three different smartphones against a reference accelerometer. We determine each accelerometer's transfer functions for Fourier frequencies 0.1-40 Hz, evidencing main differences and demonstrating a higher sensitivity than expected. Possible implementation in future distributed networks of heterogeneous and synchronized sensors, capable of independently generating and validating timely alerts in particular seismic events, are also discussed.

Figure 1

(a) Sketch of the apparatus used to characterize the different smartphone’s accelerometers. From bottom to top: the isolation stage in grey (Minus-K platform), and the actuator (a woofer); on top of it, a breadboard is placed to host all the accelerometers (EpiSensor Es-T for calibration and the smartphones, SP). The z-axis of all the accelerometers is aligned with the vertical direction. The woofer is driven by a sine function generator (arbitrary wave function, AWF), shown on the left side of the panel. The EpiSensor signals (for each axis) are acquired by using an oscilloscope and a computer, meanwhile, the SP signal is sent to the PC thanks to the Matlab and Phyphox cloud. (b) Recorded time traces of the acceleration measured by each smartphone’s sensor along the z-axis (vertical axis), for a typical actuator signal at 40 Hz, violet line: actuator sinusoidal signal,  blue line: Apple iPhone 8 time trace, yellow line: Apple iPhone 13Pro time trace, green line: Mi9T time trace, and red line EpiSensor time trace.

Figure 2

The acquired spectra at four different frequencies with the available smartphones also using the two apps. In the four subplots excitation frequency is equal to 30 Hz, 20 Hz, 10 Hz, and 4 Hz, for (a–d), respectively. Further details are provided in the text.

Figure 3

Dots show the value of the peak amplitude as a function of the measured Fourier frequencies. The mean noise level obtained from background signals within the frequency range 0.1 Hz–40 Hz is represented respectively for each sensor with lines. The observed frequency dependence of the peak amplitude is due to the different responses of the actuator as a function of frequency.

Figure 4

(a) Sensitivity level with different integration times measured in a bandwidth of 50 Hz. (b) Calibration curve of the EpiSensor acceleration on smartphones. (c) Sensor responses (normalized) as a function of the amplitude of the sine wave driving the woofer. (d) Frequency shift ($\mathrm{\Delta }f$) between EpiSensor and smartphone..

Figure 5

Estimated smartphone’s transfer functions normalized to the EpiSensor transfer functions. The lines are the interpolation of the experimental data..

Figure 6

(a) The red line represents the time track of the 2009 L’Aquila earthquake as recorded by a precision accelerometer. Blue, yellow, and green lines depict the signals that would have been observed by the iPhone 8, iPhone 13 Pro, and Mi9T, respectively. (b,c) A zoom of the signals at around 2 s and 5 s. (b) The horizontal light-blue area represents the level under which the smartphones are not sensitive, more details in the text.

Figure 7

Sketch of the cluster of a synchronized network of mobile sensors. Each cluster is independent but it is interconnected to each other and a central station for calibration purposes (image freely modified from www.freepik.com contents).