Machine Learning Applications in Optical Fiber Sensing: A Research Agenda.

The constant monitoring and control of various health, infrastructure, and natural factors have led to the design and development of technological devices in a wide range of fields. This has resulted in the creation of different types of sensors that can be used to monitor and control different environments, such as fire, water, temperature, and movement, among others. These sensors detect anomalies in the input data to the system, allowing alerts to be generated for early risk detection. The advancement of artificial intelligence has led to improved sensor systems and networks, resulting in devices with better performance and more precise results by incorporating various features. The aim of this work is to conduct a bibliometric analysis using the PRISMA 2020 set to identify research trends in the development of machine learning applications in fiber optic sensors. This methodology facilitates the analysis of a dataset comprised of documents obtained from Scopus and Web of Science databases. It enables the evaluation of both the quantity and quality of publications in the study area based on specific criteria, such as trends, key concepts, and advances in concepts over time. The study found that deep learning techniques and fiber Bragg gratings have been extensively researched in infrastructure, with a focus on using fiber optic sensors for structural health monitoring in future research. One of the main limitations is the lack of research on the use of novel materials, such as graphite, for designing fiber optic sensors. One of the main limitations is the lack of research on the use of novel materials, such as graphite, for designing fiber optic sensors. This presents an opportunity for future studies.

High Sensitivity Refractive Index Sensor Based on the Excitation of Long-Range Surface Plasmon Polaritons in H-Shaped Optical Fiber.

In this paper, we propose and numerically analyze a novel design for a high sensitivity refractive index (RI) sensor based on long-range surface plasmon resonance in H-shaped microstructured optical fiber with symmetrical dielectric-metal-dielectric waveguide (DMDW). The influences of geometrical and optical characteristics of the DMDW on the sensor performance are investigated theoretically. A large RI analyte range from 1.33 to 1.39 is evaluated to study the sensing characteristics of the proposed structure. The obtained results show that the DMDW improves the coupling between the fiber core mode and the plasmonic mode. The best configuration shows 27 nm of full width at half maximum with a resolution close to 1.3 × 10 - 5 nm, a high sensitivity of 7540 nm/RIU and a figure of merit of 280 RIU - 1 . Additionally, the proposed device has potential for multi-analyte sensing and self-reference when dissimilar DMDWs are deposited on the inner walls of the side holes. The proposed sensor structure is simple and presents very competitive sensing parameters, which demonstrates that this device is a promising alternative and could be used in a wide range of application areas.

Tunable Whispering Gallery Mode Photonic Device Based on Microstructured Optical Fiber with Internal Electrodes.

We propose and experimentally demonstrate the first tunable whispering gallery mode (WGM) photonic device based on side-hole microstructured optical fiber (SH-MOF) with internal electrodes, in which the WGM quality factors do not decrease significantly during the tuning process. The resonant modes are redshifted simply by increasing the temperature. A description of the thermal tuning properties of the WGMs in SH-MOF with internal electrodes is performed by using a two-stage computational methodology, where the effects of metal filling process are considered. SH-MOF devices with internal electrodes are tested and the experimental results show excellent agreement with the theory. A linear relationship between the shift rate of the WGM modes and temperature is observed. The tunable SH-MOF microresonator with internal electrodes is anticipated to find potential applications in optical filtering, optical switching, and highly integrated tunable photonic devices.

A Submersible Printed Sensor Based on a Monopole-Coupled Split Ring Resonator for Permittivity Characterization.

This work presents a non-invasive, reusable and submersible permittivity sensor that uses a microwave technique for the dielectric characterization of liquid materials. The proposed device consists of a compact split ring resonator excited by two integrated monopole antennas. The sensing principle is based on the notch introduced by the resonators in the transmission coefficient, which is affected due to the introduction of the sensor in a new liquid material. Then, a frequency shift of the notch and the Q-factor of the proposed sensor are related with the changes in the surrounding medium. By means of a particular experimental procedure, commercial liquids are employed to obtain the calibration curve. Thus, a mathematical equation is obtained to extract the dielectric permittivity of liquid materials with unknown dielectric properties. A good match between simulated and experimental results is obtained, as well as a high Q-factor, compact size, good sensitivity and high repeatability for use in sensing applications. Sensors like the one here presented could lead to promising solutions for characterizing materials, particularly in determining material properties and quality in the food industry, bio-sensing and other applications.

Highly sensitive temperature sensor using a Sagnac loop interferometer based on a side-hole photonic crystal fiber filled with metal.

A highly sensitive temperature sensor based on an all-fiber Sagnac loop interferometer combined with metal-filled side-hole photonic crystal fiber (PCF) is proposed and demonstrated. PCFs containing two side holes filled with metal offer a structure that can be modified to create a change in the birefringence of the fiber by the expansion of the filler metal. Bismuth and indium were used to examine the effect of filler metal on the temperature sensitivity of the fiber-optic temperature sensor. It was found from measurements that a very high temperature sensitivity of -9.0 nm/°C could be achieved with the indium-filled side-hole PCF. The experimental results are compared to numerical simulations with good agreement. It is shown that the high temperature sensitivity of the sensor is attributed to the fiber microstructure, which has a significant influence on the modulation of the birefringence caused by the expansion of the metal-filled holes.

Two-core transversally chirped microstructured optical fiber refractive index sensor.

We present a sensing architecture consisting of a two-core chirped microstructured optical fiber (MOF) for refractive index sensing of fluids. We show that by introducing a chirp in the hole size, the MOF can be a structure with decoupled cores, forming a Mach-Zehnder interferometer in which the analyte directly modulates the device transmittance by its differential influence on the effective refractive index of each core mode. We show that by filling all fiber holes with analyte, the sensing structure achieves high sensitivity (transmittance changes of 300 per RIU at 1.42) and has the potential for use over a wide range of analyte refractive index.