Abstract
Internet of Things (IoT) is enabled by the integration of communication and sensor systems that are used to collect important information from objects around the world. In this article, we proposed the integration of laser-based optical wireless communication (OWC) with a fiber sensor system for IoT applications. OWC can be utilized in a harsh environment to send and receive communication and sensor signals in a wireless means. Moreover, fiber sensors are important to achieve real-time, accurate, and smart monitoring in IoT applications. As compared to mechanical and electrical sensors, optical fiber sensors have numerous benefits, including the tolerance to electromagnetic interference (EMI), small size, lightweight, high bandwidth, low cost, provide distributed sensing, high sensitivity, and electronic devices are not required at the sensor point. Moreover, we proposed a deep variational autoencoder (DVAE) model to estimate the strain changes and peak wavelength of multiple fiber Bragg grating (FBG) sensors using only the spectrum of FBGs obtained from the real experiment. The result showed that our proposed DVAE model can estimate the strain changes and peak wavelength of FBGs with low root mean squared error (RMSE) and high estimation accuracy. Furthermore, the performance of the proposed integration of OWC with the fiber sensor system achieves a clear eye diagram and excellent bit error rate (BER) curve.
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