Abstract
Structural health monitoring using the Internet of Things (IoT) is the latest tech-nique employed in the field of structural damage detection. Although conventional systems based on commercial sensors, such as piezoelectric accelerometers, pro-vide high accuracy, their high cost often limits their application. To address this is-sue, one possibility has been the development of strategies using low-cost sen-sors. However, there are several challenges to be addressed, such as the optimiza-tion of the low-cost devices to increase their reliability in reading and processing data, and the development of data storage and data transmission strategies, mainly for dynamic monitoring applications, which requires working with large amounts of data. In this regard, this paper presents the development of a low-cost SHM so-lution, which is able to collect, store, process and transmit vibration data to the cloud from an instrumented aluminum beam. For this purpose, a prototype is de-veloped using an ESP32 board, an MPU6050 triaxial accelerometer and a mi-croSD card. A completely low-cost system is adopted, where the data processing and availability of results to the final user is performed in the free version of ThingSpeak IoT platform from MathWorks. As a result, a fully automatic dynam-ic monitoring strategy able to collect, store and transmit raw vibration data to the cloud is developed. Then, the raw acceleration data is processed and analyzed in the cloud, where the Fast Fourier Transforms (FFT) are computed and visualized in quasi-real time.
Published Version
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