This study focuses on a comprehensive analysis of the common methods for road infrastructure monitoring, as well as the perspective of various fiber-optic sensor (FOS) realization solutions in road monitoring applications. Fiber-optic sensors are a topical technology that ensures multiple advantages such as passive nature, immunity to electromagnetic interference, multiplexing capabilities, high sensitivity, and spatial resolution, as well as remote operation and multiple physical parameter monitoring, hence offering embedment potential within the road pavement structure for needed smart road solutions. The main key factors that affect FOS-based road monitoring scenarios and configurations are analyzed within this review. One such factor is technology used for optical sensing—fiber Bragg grating (FBG), Brillouin, Rayleigh, or Raman-based sensing. A descriptive comparison is made comparing typical sensitivity, spatial resolution, measurement distance, and applications. Technological approaches for monitoring physical parameters, such as strain, temperature, vibration, humidity, and pressure, as a means of assessing road infrastructure integrity and smart application integration, are also evaluated. Another critical aspect concerns spatial positioning, focusing on the point, quasi-distributed, and distributed methodologies. Lastly, the main topical FOS-based application areas are discussed, analyzed, and evaluated.

The rapid evolution of smart transportation systems necessitates the integration of advanced sensing technologies capable of supporting the real-time, reliable, and cost-effective monitoring of road infrastructure. Fiber-optic sensor (FOS) technologies, given their high sensitivity, immunity to electromagnetic interference, and suitability for harsh environments, have emerged as promising tools for enabling intelligent transportation infrastructure. This review critically examines the current landscape of classical mechanical and electrical sensor realization in monitoring solutions. Focus is also given to fiber-optic-sensor-based solutions for smart road applications, encompassing both well-established techniques such as Fiber Bragg Grating (FBG) sensors and distributed sensing systems, as well as emerging hybrid sensor networks. The article examines the most topical physical parameters that can be measured by FOSs in road infrastructure monitoring to support traffic monitoring, structural health assessment, weigh-in-motion (WIM) system development, pavement condition evaluation, and vehicle classification. In addition, strategies for FOS integration with digital twins, machine learning, artificial intelligence, quantum sensing, and Internet of Things (IoT) platforms are analyzed to highlight their potential for data-driven infrastructure management. Limitations related to deployment, scalability, long-term reliability, and standardization are also discussed. The review concludes by identifying key technological gaps and proposing future research directions to accelerate the adoption of FOS technologies in next-generation road transportation systems.

Fiber optical sensors (FOS) have been widely used to ensure physical parameter monitoring such as strain, temperature, vibration, etc. Fiber Bragg grating (FBG) sensors are of interest mainly as they offer relatively easy integration, multiplexing capabilities, and other advantages. A topical area of investigation for FOS integration is structural health monitoring (SHM) and perimeter-security monitoring. Different objects and infrastructures have certain needs, such as long-distance (40+ km) placement and monitoring solutions, lack of active power supply availability on the site, etc. It is vital to study and develop specific FBG profiles to ensure optimal operation of FBG in security, perimeter, and SHM solutions. In this research, we have evaluated the areas and categories in which such FOS and FBGs, in particular, have been used regarding SHM and perimeter monitoring solutions. Authors have also studied, simulated, and experimentally tested various FBGs that can be implemented for the perimeter—security applications and in SHM solutions.