Fiber Bragg grating (FBG) sensors have emerged as advanced tools for monitoring a wide range of physical parameters in various fields, including structural health, aerospace, biochemical, and environmental applications. This review provides a comprehensive overview of FBG sensor technology, focusing on their operating principles, key advantages such as high sensitivity and immunity to electromagnetic interference, and common challenges like temperature-strain cross-sensitivity and the high cost of interrogation systems. Additionally, this review compares FBG sensors with other sensing technologies and highlights recent innovations in design, packaging, and implementation techniques. Finally, future research directions are discussed to enhance the performance, scalability, and long-term reliability of FBG-based sensing systems.

This review summarizes recent progress and emerging trends in multiparameter optical fiber sensing, emphasizing techniques that enable the simultaneous measurement of temperature, strain, acoustic waves, pressure, and other environmental quantities within a single sensing network. Such capabilities are increasingly important for structural health monitoring, environmental surveillance, industrial diagnostics, and geophysical observation, where multiple stimuli act on the fiber simultaneously. The paper outlines the physical principles and architectures underlying these systems and focuses on strategies for compensating and decoupling cross-sensitivity among measured parameters. Special attention is devoted to advanced distributed sensing schemes based on coherent optical frequency-domain reflectometry (C-OFDR), coherent phase-sensitive time-domain reflectometry (Φ-OTDR), and Brillouin optical time-domain reflectometry (BOTDR). Their theoretical foundations, their signal-processing algorithms, and the design modifications that improve parameter discrimination and accuracy are analyzed and compared. The review also highlights the roles of polarization and mode diversity and the growing application of machine-learning techniques in the interpretation and calibration of data. Finally, current challenges and promising directions for the next generation of fiber-optic multiparameter sensors are outlined, with a view toward high-resolution, low-cost, and field-deployable solutions for real-world monitoring applications.

Measuring pH is a critical parameter in environmental monitoring, biomedical diagnostics, food safety, and industrial processes. Optical fiber sensors have proven highly effective for pH detection due to their exceptional sensitivity, rapid response, and resistance to electromagnetic interference, making them well suited for real-time monitoring. This review offers a comprehensive analysis of recent advances in optical fiber-based pH sensors, covering key techniques such as fluorescence-based, absorbance-based, evanescent wave, and interferometric methods. Innovations in Fiber Bragg Grating and Surface Plasmon Resonance technologies are also examined. The discussion extends to the impact of pH-sensitive coatings—ranging from nanomaterials and polymeric films to graphene-based compounds—on enhancing sensor performance. Recent advancements have also enabled automation in data analysis and improvements in remote sensing capabilities. The review further compares the economic viability of optical fiber sensors with traditional electrochemical methods, while acknowledging persistent issues such as temperature cross-sensitivity, long-term stability, and fabrication costs. Overall, recent developments have broadened the functionality and application scope of these sensors by improving efficiency, accuracy, and scalability. Future research directions are outlined, including advanced optical interrogation techniques, such as Addressed Fiber Bragg Structures (AFBSs), microwave photonic integration, and optimized material selection. These approaches aim to enhance performance, reduce costs, and enable the broader adoption of optical fiber pH sensors.

The paper describes the design and manufacturing process of a fiber optic microphone based on a macro cavity at the end face of an optical fiber. The study explores the step-by-step fabrication of a droplet-shaped macro cavity on the optical fiber’s end surface, derived from the formation of a quasi-periodic array of micro-cavities due to the fuse effect. Immersing the end face of an optical fiber with a macro cavity in liquid leads to the formation of a closed area of gas where interfacial surfaces act as Fabry–Perot mirrors. The study demonstrates that the macro cavity can act as a standard foundational element for diverse fiber optic sensors, using the droplet-shaped end-face cavity as a primary sensor element. An evaluation of the macro cavity interferometer’s sensitivity to length alterations is presented, highlighting its substantial promise for use in precise fiber optic measurements. However, potential limitations and further research directions include investigating the influence of external factors on microphone sensitivity and long-term stability. This approach not only significantly contributes to optical measurement techniques but also underscores the necessity for the continued exploration of the parameters influencing device performance.

In this paper, an application of an artificial neural network algorithm is proposed to enhance the accuracy of temperature measurement using a fiber-optic sensor based on a Fabry–Perot interferometer (FPI). It is assumed that the interrogation of the FPI is carried out using an optical comb generator realizing a microwave photonic approach. Firstly, modelling of the reflection spectrum of a Fabry–Perot interferometer is implemented. Secondly, probing of the obtained spectrum using a comb-generator model is performed. The resulting electrical signal of the photodetector is processed and is used to create a sample for artificial neural network training aimed at temperature detection. It is demonstrated that the artificial neural network implementation can predict temperature variations with an accuracy equal to 0.018 °C in the range from −10 to +10 °C and 0.147 in the range from −15 to +15 °C.

The paper presents a novel pH-sensor architecture based on an addressed fiber Bragg structure (AFBS) with fully-etched segment, designed for reliable operation in thermally unstable industrial environments. The sensor employs a fiber Bragg grating with dual π phase shifts, where one of the segments is fully etched to the core to enhance evanescent field interaction with the environment. This geometric modification significantly increases sensitivity to refractive index variations, which correlate with local pH changes. Numerical simulations confirm a near-linear dependence of the address frequency on pH levels ranging from 11.0 to 13.7, with thermal invariance maintained from −100 °C to +100 °C. The sensor’s dual-resonance spectral profile enables high-resolution microwave photonic interrogation and supports wavelength-division multiplexing for distributed measurements. A simulated multisensor configuration demonstrates clear spectral separation and addressability. Beyond refractive index sensitivity, the design provides electromagnetic immunity, real-time response, and compatibility with remote optical interrogation. These features make the etched AFBS (EAFBS) sensor highly suitable for deployment in industrial environments. Future work will focus on integrating EAFBS into multi-parameter fiber-optic platforms capable of simultaneous monitoring of pH, temperature, and flow rate.