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Optical fibre sensors are an essential subset of optical fibre technology, designed specifically for sensing and measuring several physical parameters. These sensors offer unique advantages over traditional sensors, making them gradually more valuable in a wide range of applications. They can detect extremely small variations in the physical parameters they are designed to measure, such as analytes in the case of biosensing. This high sensitivity allows them to detect subtle variations in temperature, pressure, strain, the refractive index of analytes, vibration, and other environmental factors with exceptional accuracy. Moreover, these sensors enable remote sensing capabilities. Since light signals are used to carry information, the sensing elements can be placed at distant or inaccessible sites and still communicate the data back to the central monitoring system without signal degradation. In recent times, different attractive configurations and approaches have been proposed to enhance the sensitivity of the optical fibre-based sensor and are briefly explained in this review. However, we believe that the choice of optical fibre sensor configuration should be designated based on the specific application. As these sensors continue to evolve and improve, they will play an increasingly vital role in critical monitoring and control applications across various industries.

Optical fiber sensors present several advantages in relation to other types of sensors. These advantages are essentially related to the optical fiber properties, i.e., small, lightweight, resistant to high temperatures and pressure, electromagnetically passive, among others. Sensing is achieved by exploring the properties of light to obtain measurements of parameters, such as temperature, strain, or angular velocity. In addition, optical fiber sensors can be used to form an Optical Fiber Sensing Network (OFSN) allowing manufacturers to create versatile monitoring solutions with several applications, e.g., periodic monitoring along extensive distances (kilometers), in extreme or hazardous environments, inside structures and engines, in clothes, and for health monitoring and assistance. Most of the literature available on this subject focuses on a specific field of optical sensing applications and details their principles of operation. This paper presents a more broad overview, providing the reader with a literature review that describes the main principles of optical sensing and highlights the versatility, advantages, and different real-world applications of optical sensing. Moreover, it includes an overview and discussion of a less common architecture, where optical sensing and Wireless Sensor Networks (WSNs) are integrated to harness the benefits of both worlds.

Tailored, specialty optical fibres, made of complex glasses, called collectively as a non-telecommunications or instrumentation family, serve for various optical wave transformations for particular functional purposes and optical signal processing, rather than for long distance lossless and dispersionless, undistorted transmission. Research work on these fibres started during the late seventies of the last century in ITME/Warsaw and in Białystok University of Technology at the Faculty of Electrical Engineering. The initiator of this research at Glass Works Białystok [39] and Białystok University of Technology [4] was, then a very young engineer, Jan Dorosz. Over 35 years of development of the technological team, under his skilful management, resulted in a top laboratory which today does research at the cutting edge of the photonics science. The Białystok Optical Fibre Technology Laboratory (OFTL) is now a pearl in the crown of his Alma Mater. The paper opens this special issue of the PAS Bulletin on Technical Sciences, devoted to professor Jan Dorosz, and shows some of the developments in the area of optical fibre photonics, which were carried out at his active laboratory.

A range of optical fibre-based sensors for the measurement of ethanol, primarily in aqueous solution, have been developed and are reviewed here. The sensing approaches can be classified into four groups according to the measurement techniques used, namely absorption (or absorbance), external interferometric, internal fibre grating and plasmonic sensing. The sensors within these groupings can be compared in terms of their characteristic performance indicators, which include sensitivity, resolution and measurement range. Here, particular attention is paid to the potential application areas of these sensors as ethanol production is globally viewed as an important industrial activity. Potential industrial applications are highlighted in the context of the emergence of the internet of things (IoT), which is driving widespread utilization of these sensors in the commercially significant industrial and medical sectors. The review concludes with a summary of the current status and future prospects of optical fibre ethanol sensors for industrial use.

Solitons are waves that retain their form through obstacle and distance. Solitons can be found in hydrodynamics, nonlinear optics, plasma physics, and biology. Optical solitons are solitary light waves that hold their form over an expansive interval. Conservation of this form creates an effective model for long distance voice and data transmission.The application of this principle is essential to the technology of wired communications. Optical solitons produce crystal clear phone calls cross-country and internationally. It is because of these that someone on the other end of the phone sounds 'in the next room.' It is also pertinent to high-speed network information transmittal.Mollenauer and Gordon have written the only text that an engineer or graduate student will need to understand this foundation subject in optics. *Written by Linn Mollenauer and James Gordon who are celebrated for applying optical solitons to telecommnications*Combines mathematical developments with well-chosen practical examples and design formulas*Extensive material on the basic physics of fiber optic transmission and its practical applications

A flexible weight sensor based on optical fibre macrobending loss, using 1550 nm wavelength light and small fibre bending path lengths is presented. An applied load depresses an impactor layer of cylindrical protrusions into a soft mat covered with optical fibre, causing the optical loss of the fibre to increase. An experimental study of two fibre types, two impactor materials, two impactor designs and a range of protrusion bend radii from 3 mm to 10 mm is shown. For weights greater than 2 kg, a linear response in optical loss (dB) is observed for an applied weight load in kg. The proportionality constant between loss and load, and thus the total amount of optical loss for up to 10 kg of weight load, can be tuned by changing the sensor physical parameters, shown here in ranges from 0.5 dB up to 25 dB.

Advances in medicine and improvements in life quality has led to an increase in the life expectancy of the general population. An ageing world population have placed demands on the use of assistive technology and, in particular, towards novel healthcare devices and sensors. Besides the electromagnetic field immunity, polymer optical fiber (POF) sensors have additional advantages due to their material features such as high flexibility, lower Young’s modulus (enabling high sensitivity for mechanical parameters), higher elastic limits, and impact resistance. Such advantages are well-aligned with the instrumentation requirements of many healthcare devices and in movement analysis. Aiming at these advantages, this review paper presents the state-of-the-art developments of POF sensors for healthcare applications. A plethora of healthcare applications are discussed, which include movement analysis, physiological parameters monitoring, instrumented insoles, as well as instrumentation of healthcare robotic devices such as exoskeletons, smart walkers, actuators, prostheses, and orthosis. This review paper shows the feasibility of using POF sensors in healthcare applications and, due to the aforementioned advantages, it is possible to envisage a further widespread use of such sensors in this research field in the next few years.

Internet data traffic capadty is rapidly reaching limits imposed by optical fiber nonlinear effects. Having almost exhausted available degrees of freedom to orthogonally multiplex data, the possibility is now being explored of using spatial modes of fibers to enhance data capadty. We demonstrate the viability of using the orbital angular momentum (OAM) of light to create orthogonal, spatially distinct streams of data-transmitting channels that are multiplexed in a single fiber. Over 1.1 kilometers of a specially designed optical fiber that minimizes mode coupling, we achieved 400-gigabits-per-second data transmission using four angular momentum modes at a single wavelength, and 1.6 terabits per second using two OAM modes over 10 wavelengths. These demonstrations suggest that OAM could provide an additional degree of freedom for data multiplexing in future fiber networks.

Oil and gas (O&G) explorations moving into deeper zones for enhanced oil and gas recovery are causing serious safety concerns across the world. The sensing of critical multiple parameters like high pressure, high temperature (HPHT), chemicals, etc., are required at longer distances in real-time. Traditional electrical sensors operate less effectively under these extreme environmental conditions and are susceptible to electromagnetic interference (EMI). Hence, there is a growing demand for improved sensors with enhanced measurement capabilities and also sensors that generates reliable data for enhanced oil and gas production. In addition to enhanced oil and gas recovery, the sensing technology should also be capable of monitoring the well bore integrity and safety. The sensing requirements of the O&G industry for improved sensing in deeper zones include increased transmission length, improved spatial coverage and integration of multiple sensors with multimodal sensing capability. This imposes problems like signal attenuation, crosstalks and cross sensitivities. Optical fibre-based sensors are expected to provide superior sensing capabilities compared to electrical sensors. This review paper covers a detailed review of different fibre-optic sensing technologies to identify a feasible sensing solution for the O&G industry.

Distributed acoustic sensing (DAS) with preexisting telecommunication optical fibers (dark fibers) has shown its ability to record rain‐induced seismic noise with unprecedented high spatiotemporal resolution. This rain‐induced noise exhibits strong correlations with rainfall intensity and rainwater discharge in pipeline sewers, highlighting its potential to infer rainwater flow characteristics. While raindrop impact models exist, a physical model linking stormwater discharge processes to DAS‐recorded signals is still lacking. In this study, we introduce a data‐driven method, deep embedded clustering (DEC), to automatically detect and classify rain‐induced noise from massive DAS data, predicting the presence of moderate to heavy rain and the duration of stormwater discharge. We analyze continuous DAS recordings from 2019 to 2021 from a 4.2 km‐long underground fiber‐optic array in State College, PA. During training, the DEC model employs an autoencoder to learn the latent features from preprocessed spectrograms and then clusters these latent features into four clusters. Distinct features from spectrograms within each cluster reveal that four clusters correspond to background noise, rain‐induced noise of varying rain intensities and stormwater discharge in sewers. Tests on unseen data sets in 2019 and 2021 demonstrate DEC's ability to not only predict rainfall rate levels but also indicate post‐rain discharge durations. Furthermore, the model‐derived post‐rain discharge durations align with synthetic hydrograph estimates, yielding a drainage system time of concentration as 21 min in this region. Finally, we apply this workflow to two more locations to show the potential of spatial monitoring. Our results show that the combination of machine learning and fiber‐optic sensing offers a scalable solution for improving stormwater management in urban environments.