Integrated Sensor-Optics Communication System Using Bidirectional Fiber and FSO Channels and Hybrid Deep Learning Techniques.

This paper introduces a new bidirectional integration approach that combines fiber sensor/free space optics (FSO) communication using an intensity and wavelength division multiplexer (IWDM) techniques-based long-distance fiber Bragg grating (FBG) sensor strain-sensing system. By implementing coarse wavelength division multiplexing (CWDM), the system achieves the simultaneous transmission of optical communication and fiber optical sensor (FOS) sensing signals, resulting in a highly capable, flexible, and cost-effective solution. The proposed FSO transmission technique addresses complex fiber cable installation concerns with topographical limitations. This bidirectional structure ensures the reliability and stability of the long-distance FBG sensor system, supported by extensive research and experimentation. A hybrid stacked gated recurrent units and long short-term memory (SGRU-LSTM) model is proposed to enhance strain measurement accuracy by predicting and measuring the central wavelength of overlapped strain-sensing FBG sensor signals. The results demonstrate the superiority of the proposed model in peak wavelength detection accuracy. The primary benefit of integrating communication and sensing is the significant reduction in construction costs by eliminating the requirement for two individual fiber optic systems, as the integration allows for a single system to fulfill both functions, resulting in more efficient and cost-effective implementation. Overall, this paper contributes to advancing long-distance FBG sensor systems by integrating fiber sensor/FSO communication and deep learning techniques, improving transmission distance, multiplexing capacity, measurement accuracy, system survivability, and cost-effectiveness.