## 1 Introduction  
The mechanical properties of structures change over the course of their lifetime. Changes related to deterioration such as damage may be safety-relevant and need to be detected. Modern sensor-based methods to determine the behavior of the structure and to assess its condition are the subject of structural health monitoring (SHM). Typical SHM processes implement a damage detection strategy that involves the monitoring of a structure over a period of time with a suitably selected measurement system and identifying damage indicators or damage-sensitive features. A common non-destructive approach to monitor damage is through vibration-based measurements using acceleration sensors. Signal processing and system identification techniques can be used to compute global properties such as natural frequencies and structural mode shapes from the transient data, and model-basedcalibration methods allow for the detection of changes in mechanical characteristics from changes in these. The quality of the identified structural properties and as such the capability of detecting system changes such as damage are directly associated with the characteristics of the measurement system. Compared with traditional wire-based strategies for monitoring civil structures, wireless mobile mesh network systems (wireless sensor networks (WSNs)) have proven themselves as a time- and cost-efficient solution, as they aim for a faster and more adaptive examination process. Many studies are published that focus on the development of WSNs including the aspect of reliable data transport, the compression of data, data synchronization, and distributed computing [1; 2] as well as their application to different types of structures such as bridges and towers [3; 4]. However, the different WSNs developed [4] are not designed for mobile usage, which would also allow flexible integration of different types of sensor nodes. In contrast to permanent installations of sensor networks on structures, there is a growing need for flexible and mobile hardware solutions. This demand can be addressed by the use of microcomputer hardware. Considering the SHM context, only a few studies are focused on measuring acceleration by only using microcomputer and external microelectromechanical system (MEMS)-based sensors. So far, mass market microcomputers and microcontrollers have been used as control platforms, which are accessed via WiFi from a computer, and Raspberry Pi (RPi) microcomputers have been connected to ADXL345 sensors [5] and directly to MPU-6050 accelerometers [6] or via Arduino Mega microcontroller [7]. Besides the application for vibration measurements, other wireless monitoring systems employing cost-effective microcomputers and microcontrollers in combination with specific piezoelectric sensors (PZTs) have been developed to identify local damage in reinforced concrete elements. These systems are based on the electromechanical impedance (EMI) concept and integrate Raspberry Pi [8] and ATmega microcontrollers [9]. Mobile measurement systems, i.e., smartphone and tablet devices, have been applied to monitor infrastructures, such as bridges. Internal MEMS-based accelerometers are typically utilized to record structural vibrations in order to extract dynamic properties. Sensing properties vary drastically between the available smartphones since different software systems and hardware components are integrated. Therefore, different devices will offer different measurement quality, and the imposed limitations can solely be expressed as smartphone-dependent. Characteristics such as the maximum sampling rate, the range, and the resolution have been investigated in various studies [6; 10; 11; 12], where maximum sampling rates of 225 Hz and resolvable accelerations down to 1 mm/s\({}^{2}\) were found. However, the latest smartphone models are not covered. In these studies, the cable-force estimation of stay cables [13] or suspension bridge hangers [14] of long-span bridges has been a major application.