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Turning Fiber into a Sensing System: The Magic of Fiber Optics Sensing

IEEE CTN
Written By:

Luyao Huang and Dezhi Zhang

Published: 5 Aug 2025

network

CTN Issue: July 2025

A note from the editor:

Imagine a world where the Internet doesn’t just connect but senses—detecting earthquakes, monitoring battery health, or safeguarding critical infrastructure. This is the power of fiber optic sensing, a technology that transforms ordinary optical fibers into the digital world’s sensory network. In 2023, researchers turned submarine cables into earthquake warning systems and gave electric vehicles “optical nerves” to prevent battery failures. From energy and transportation to agriculture and cybersecurity, fiber sensing is quietly revolutionizing industries with applications once thought impossible. In this article, the authors explore the principles behind this invisible yet transformative technology and its growing impact on our future.

Yuanqiu Luo, CTN Guest Editor

Fiber Sensing Technologies: From Invisible Antennae to the Perceptual Revolution of the Internet of Everything

Luyao Huang

Luyao Huang
China Telecom Research Institute, State Key Laboratory of Optical Fiber and Cable Manufacture Technology, Beijing, China

Dezhi Zhang

Dezhi Zhang
China Telecom Research Institute, State Key Laboratory of Optical Fiber and Cable Manufacture Technology, Beijing, China

I. Introduction

If 5G is the neural conduction of the digital age and AI the super brain, fiber sensing serves as the quietly growing peripheral nerves. In 2023, a group from California Institute of Technology, collaborating with Google, achieved the world’s first commercial submarine cable-based second-level earthquake warning system [1], transforming trans-Pacific communication cables into a "stethoscope for Earth." Concurrently, researchers resolved the problem of temperature-pressure signal crosstalk in fiber sensing [2], equipping power batteries with "optical neural" warning systems and elevating the safety of new energy vehicles.

The technological roots of this revolution trace back 400 years to the birth of optics. Scientists including Snell, Newton, Fermat, Huygens, Fresnel, Maxwell, and Einstein explored light’s fundamental nature from diverse perspectives. The historical development is shown in Fig. 1. Furthermore, In the 1960s, Charles Kao proposed the idea of using light instead of electric currents and optical fibers instead of metal wires to transmit signals. This innovation gave birth to optical fiber, accelerating optical communication. The initial research focus of optical fiber sensing was directed toward the monitoring of optical fiber parameters. Subsequent investigations, however, revealed its capability to detect ambient environmental conditions, thereby enabling significantly broader application domains. Fiber sensing technology emerged in the 1970s. In 1976, the first fiber optic gyroscope (FOG) for angular velocity measurement, exploiting the Sagnac effect, was realized [3]. The following year, optical time-domain reflectometry (OTDR) based on Rayleigh backscattering achieved the initial localization of fiber breaks [4]. The discovery of fiber gratings, capitalizing on the photosensitivity of optical fibers in 1978 [5], and the invention of the fiber Fabry-Pérot (FP) interferometer in 1981 [6], established the basis for point sensing. Subsequently, the proposal of Raman optical time-domain reflectometry (ROTDR) for temperature measurement in 1985 [7] and the introduction of Brillouin optical time-domain reflectometry (BOTDR) sensing in 1993 [8], facilitated the progressive maturation of distributed fiber optic sensing technology.

Fig. 1: Historical development of fiber optic sensing fundamentals
Fig. 1: Historical development of fiber optic sensing fundamentals

The ongoing perception revolution based on fiber sensing technology is expanding at an accelerated pace: Wuhan University of Technology has achieved precise integration of hundreds of thousands of sensors on a single optical fiber [9], constructing an 'intelligent neural network' that monitors urban underground pipe networks. Addressing the critical incompatibility between traditional distributed fiber optic sensing (DFOS) systems and large mechanical strains in stretchable electronics, Cornell University researchers have developed a stretchable, joint-embeddable distributed flexible fiber optic sensor [10], endowing humanoid robots with tactile acuity approaching that of human skin. Empirical data indicates the global fiber sensing market reached US$3.61 billion in 2024 and is projected to grow to US$6.76 billion by 2031 [11]. This exponential growth fundamentally embodies fiber’s revolutionary transition from a mere 'data conduit' to a dual role in both data transmission and sensory perception. As every scattering and refraction event of an optical pulse becomes a signature for decoding the physical world, are we on the cusp of witnessing a scientific paradigm shift?

II. Fundamental Principles of Fiber Sensing

Understanding this revolution requires grasping fiber sensing’s principles: External physical parameters (temperature, pressure, strain, etc.) interact with light signals in optical fibers, altering intensity, phase, wavelength, or polarization. Key technologies include interference, diffraction and scattering effects (Rayleigh, Raman, Brillouin).

Sensing technologies can be classified into point and distributed schemes according to the configuration of sensing elements.

1. Point Sensing Technology

The effects employed are interference and diffraction. Representative optical devices for interference include interferometers, while fiber Bragg gratings (FBG) serve as the characteristic devices for diffraction.

  • Interferometry: Fabry-Pérot interferometers (FPI) measure pressure and displacement via micro-cavity interference.
  • FBG: Periodic refractive index modulations in fiber cores create wavelength-selective reflectors. FBG achieves sub-micron deformation or 0.1℃ temperature precision through reflection wavelength shifts.

2. Distributed Sensing Technology

Distributed sensing relies principally on three fundamental scattering phenomena: Rayleigh, Brillouin, and Raman scattering. Representative techniques based on Rayleigh scattering include OTDR and phase-sensitive OTDR (φ-OTDR), collectively termed distributed acoustic sensing (DAS). Brillouin scattering-based technologies encompass BOTDR and Brillouin optical time-domain analysis (BOTDA). ROTDR constitutes the principal technique employing Raman scattering.

OTDR: During light propagation through optical fiber, elastic collisions occur with microscopic density fluctuations in the core material, resulting in omnidirectional light scattering. The backscattered Rayleigh light serves as the fundamental signal source for OTDR. Measurement of its intensity attenuation enables calculation of the fiber's loss coefficient (dB/km) and localization of discrete anomalies. At interfaces between media with differing refractive indices (e.g., fiber fractures, connector end-faces), partial light reflects. Detection of Fresnel reflection peak positions and amplitudes permits precise localization of fiber breakpoints, connector faults, or mechanical splice losses. OTDR thus utilizes Rayleigh scattering and reflections for fiber monitoring.

BOTDR: This technique enables long-range continuous monitoring of temperature and strain by detecting Brillouin frequency shifts and scattered light intensity from optical pulses in fibers. The Brillouin frequency shift arises from interactions between incident photons and acoustic phonons, with the frequency offset being proportional to ambient temperature and strain. The spatial location of measurement events is determined through time-of-flight analysis of the scattered light.

ROTDR: As a temperature monitoring technology based on Raman scattering, ROTDR operates through inelastic collisions between propagating optical pulses and molecular vibrations. This interaction generates two characteristic scattered light components: Stokes and anti-Stokes radiation. The temperature-dependent intensity ratio between these components provides the quantitative basis for thermal measurements.

The classification of these technologies as shown in Table 1 is based on key optical devices, which function as information acquisition units. Each technique incorporates extensive signal processing algorithms to derive measured physical quantities from sensing physical quantities. However, such measurements typically yield only numerical outputs (e.g., vibration amplitudes, attenuation coefficients), wherein event identification traditionally relies on empirical expertise or remains unattainable. Artificial intelligence (AI) methodologies bridge this critical gap by enabling pattern recognition within measured physical quantities—distinguishing between human footsteps, bicycles, and vehicular traffic from vibrational signatures. Furthermore, large language models facilitate multi-sensor data integration, performing multimodal data fusion and semantic parsing to achieve contextual comprehension and predictive state forecasting.

Table 1: The classification of fiber sensing technology
Sensing Unit DesignEffectDeviceTechnologyMeasuredSensed
PointInterferenceInterferometerMZ/
Micro-ring		PhaseTemp/
Strain/
Vibration
DiffractionFBGFBGWavelengthTemp/
Strain
Fiber transmission (Total Reflection)Optical Fiber (Conventional Fiber, Specialty Fiber)Comm. receiver DSPPhase/
SOP		Vibration
DistributedFresnel ReflectionOTDRIntensityBreakpoints/
connectors/
end-face position
Rayleigh ScatteringOTDRIntensityFiber
length/
loss/
vibration
φ-OTDRPhasevibration
OFDRfrequencyTemp/
Strain
POTDRpolarizationvibration
Brillouin ScatteringBOTDR/
BOTDA		wavelengthTemp/
Strain
Raman ScatteringROTDRIntensityTemp
AI-assisted：Event recognition/multimodal fusion

 

III. Cutting-edge Applications of Fiber Sensing Technologies

Industry-specific technical implementations will be presented across five domains: energy, transportation, medicine, agriculture, and security shown in Fig. 2.

Fig. 2: Fiber sensing applications
Fig. 2: Fiber sensing applications

1. Energy

Fiber sensing is emerging as a critical enabler of infrastructure intelligence. In the wind power industry, DAS facilitates real-time monitoring of turbine tower vibrations, stress distribution, and structural deformation, enabling predictive maintenance. For instance, Optasense's industrial-grade DAS system achieves network monitoring of multiple turbines via a single optical fiber. By detecting changes in strain and natural frequency signatures across 10-km spans, it successfully identifies bolt loosening and local material yielding [12].

Within the petroleum industry, Sonatrach (Africa's largest oil producer) and Huawei collaboratively developed an intelligent pipeline integrity inspection solution, shown in Fig. 3. To address the challenges of difficult manual inspection and slow risk identification, a 32-dimensional vibration waveform analysis algorithm is employed. This technology achieves a 97% intrusion detection accuracy rate within a 2-meter range surrounding buried pipelines. It successfully identifies 100% fiber break events, manual excavation activities, and mechanical excavation activities. The system exhibits a low false alarm rate of only 0.012 events per kilometer per day (0.012/km/day) and an alarm localization error of less than 10 meters. This advancement significantly promotes the smartization process within the petroleum industry [13].

Fig. 3: Schematic diagram of pipeline integrity inspection [13]
Fig. 3: Schematic diagram of pipeline integrity inspection [13]

2. Transportation

Huabei Traffic Investment Technology Co., Ltd., in collaboration with Wuhan University of Technology, deploys a network of 16,000 FBG sensors along a 13-kilometer section of the Huahu International Airport Expressway in China. This network achieves a dense sensing grid with 5-meter intervals. Integrated with video surveillance and radar technologies, the system creates a comprehensive "tactile-visual-detection" multi-mode perception network spanning the entire roadway. This integrated infrastructure enables the command center to visualize real-time data concerning structural health, pavement operating conditions, vehicle speed/distance, and driving behavior, facilitating comprehensive, all-weather, real-time monitoring and management [14]. In the domain of bridge health monitoring, the Wuhan Shuangliu Yangtze River Bridge incorporates strain, temperature, and humidity sensing cables into three of its cable strands to establish a smart main cable system. This system provides continuous real-time monitoring and enables regulation of stress levels and temperature/humidity conditions within the main cables [15].

Subsea, FiberSense partneres with Southern Cross Cable Network to deploy its Digital Marine monitoring system on shore-end infrastructure for submarine cables in New Zealand [16]. Furthermore, submarine cables demonstrate potential for natural disaster early warning. The UK's National Physical Laboratory (NPL) and Measurement Standards Laboratory of New Zealand (MSL) are collaborating on utilizing the 3,876-kilometer (2,408-mile) "Southern Cross NEXT" submarine cable traversing the Tasman Sea between New Zealand and Australia. By applying ultra-sensitive optical measurement techniques, they detect seismic activity and ocean current signals within the Pacific Ocean.[17].

In the aerospace sector, NASA's Fiber Optic Sensing System (FOSS), initially developed for monitoring structural stress and deformation in test aircraft, employs a single, hair-thin optical fiber up to 40 feet in length to deliver up to 2000 data points. The system processes information every quarter inch along the fiber at a rate of 100 times per second, enabling precise measurement of strain, shape deformation, temperature, liquid levels, and operational loads shown in Fig. 4. FOSS replaces bulky traditional wired sensors, substantially reducing the weight and complexity of aerospace systems. It has been implemented on platforms like the Ikhana UAV and for X-56A flexible wing flutter testing. Concurrently, NASA's Armstrong Flight Research Center continues to develop new FOSS applications. These include monitoring launch loads on rockets, the health of spacecraft thermal protection systems, structural integrity monitoring for satellites and Mars rover wheels, and measuring liquid propellant levels and temperature in spaceflight fuel tanks. FOSS holds significant potential for diverse applications in projects such as Artemis, Mars missions, and satellite operations [18-19].

Fig. 4: Fiber Optic Sensing Technology for Aircraft [19]
Fig. 4: Fiber Optic Sensing Technology for Aircraft [19]

3. Medicine

Researchers at Jinan University pioneered an optical fiber-based drug delivery system featuring photo-triggered release for targeted transport to deep-seated lesions, integrating FBG sensors for real-time temperature monitoring and reflective multimode-singlemode fiber Mach-Zehnder interferometric (MZI) refractive index sensors for continuous drug concentration quantification, thereby enabling comprehensive real-time surveillance during photothermal therapy [20]. Concurrently, sub-100 nm particles pose significant health hazards due to their pulmonary penetration depth and adsorption capacity for toxic organic compounds; Eindhoven University of Technology addressed this challenge through a photonic crystal cavity fiber-tip sensor achieving real-time detection of individual 50-nm ultrafine particles, leveraging its compact architecture, simplified readout, small mode volume (0.03 μm³), narrow linewidth (<20 pm), and large modulation depth (32 dB) to enable nanoscale perturbation detection near the fiber tip, with findings published in Optica [21].

4. Agriculture

Research by the California Institute of Technology established a novel DAS methodology for monitoring spatiotemporal soil moisture dynamics in arid-region vadose zones [22], utilizing existing fiber-optic cables as seismic sensors in California's Ridgecrest area to successfully capture seasonal variations, drought-induced depletion, and precipitation recharge cycles, demonstrating significant potential for regional-scale hydrological monitoring as a climate resiliency tool. Simultaneously, Nanjing University leveraged optical frequency domain reflectometry (OFDR) to achieve millimeter-level spatiotemporal resolution in desiccation cracking processes—precisely locating crack initiation while implementing a finite element method (FEM)-based strain field reconstruction technique that enhanced monitoring coverage by 38% without additional sensors [23]. Concurrently, Zhejiang University and Rice University integrated DAS with geophysical algorithms and data-driven modeling to quantify permafrost degradation mechanisms, revealing through controlled Alaskan heating experiments a 15% shear-wave velocity reduction at 15m depth and 2-meter interfacial subsidence after bi-monthly thaw, providing the first in situ seismic characterization of active layer detachment [24].

5. Security

Researchers at the USTC demonstrated an integrated quantum-fiber sensing system achieving concurrent twin-field quantum key distribution (TF-QKD) and 658-km long-range vibration sensing with ±1 km spatial resolution—surpassing the conventional 100-km limitation of optical vibration detection—through quantum-enhanced phase-sensitive signal processing [25].

IV. Conclusion

Fiber sensing technologies are reconfiguring perceptual dimensions through imperceptible sensory filaments. These systems achieve omnidirectional precision sensing of temperature, stress, and vibration by detecting subtle parameter changes from interference, diffraction, Rayleigh, Brillouin, and Raman scattering effect. From the detection of nanoscale particles in the human body to precise tumor drug delivery, from structural health monitoring in bridges and tunnels to leakage early warning in oil pipelines, from real-time navigation information dissemination on highways to environmental exploration in the abyssal depths of over 10,000 meters, and from soil moisture monitoring to permafrost observation, these fiber-optic networks embedded in infrastructure function as digital nerve endings. With their unique advantages—such as electromagnetic interference resistance, corrosion resistance, high precision, and long-distance coverage—they transcend the physical limitations of traditional sensors. Despite persistent challenges in precision-cost optimization and computational bottlenecks for exabyte datasets, convergence with optical communication systems, photonic ICs, IoT architectures, and deep learning frameworks is enabling cross-domain penetration (energy/transportation/life sciences/agriculture); their millisecond-scale temporal resolution and petabyte-grade data capacity establish a hypersensitive substrate for the Internet of Everything, propelling human society toward an era of digitized perception characterized by micrometer-scale spatial resolution.

Reference

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