Convergence of Multidimensional Sensing: A Review of AI-Enhanced
The integration of SDM and AI represents a paradigm shift, creating intelligent, high-dimensional sensing networks. AI is crucial for overcoming SDM limitations and realizing the full
This paper presents a comprehensive review of AI-enhanced OFS technologies, encompassing both localized sensors such as fiber Bragg gratings (FBG), Fabry–Perot (FP) interferometers, and Mach–Zehnder interferometers (MZI), and distributed sensing systems ba...
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The integration of SDM and AI represents a paradigm shift, creating intelligent, high-dimensional sensing networks. AI is crucial for overcoming SDM limitations and realizing the full
Fiber optic sensor technologies hold great promise to form the backbone for next-generation intelligent sensing platforms that offer long-distance, high-accuracy, distributed
In recent years, with the increasing demand for intelligent society, intelligent photonics has developed rapidly. Machine learning (ML), as a subset of artificial intelligence (AI), has played an
Machine learning (ML), as a subset of artificial intelligence (AI), has played an important role in the intelligent evolution of optical fiber sensors. Its impact extends beyond enhancing sensor
In the last few decades, sensing mechanisms by employing the fiber optics has achieved huge attention owing to their unique characteristics. The machine learning (ML) approach has
Multidimensional force sensors are key devices capable of simultaneously perceiving and analyzing force in multiple directions (normally triaxial forces). They are designed to provide
However, high-dimensional optical fiber systems, usually necessity bulk-optics approaches for launching different orthogonal fiber modes into the optical fiber, and multiple-input
Fiber optic sensing has emerged as a powerful sensing technology for a wide range of energy infrastructure applications, with numerous advantages as follows: (1) elimination of electrical
This work proposes an all-optical fiber sensing architecture with in-sensor computing that achieves <3 ns demodulation latency, sub-nano strain resolution, and multi-parameter sensing
Fiber optic shape sensors are optical Multicore Fibers (MCF) or multi-fiber cables (with a similar section geometry to MCFs, but larger core spacing) capable of sensing multidimensional
This review argues that the synergistic convergence of space-division multiplexing (SDM) and artificial intelligence (AI) represents a paradigm shift, enabling a new generation of intelligent, high
Imagine a world where the Internet doesn''t just connect but senses —detecting earthquakes, monitoring battery health, or safeguarding critical
This chapter covers the way AI has brought about change in the application of fiber optic sensors and also gives insight on its impact on the sensing network in industrial applications.
RQ6: What topics are relevant for designing a research agenda on machine learning applications in fiber optic sensors? For this purpose, the document is structured as follows; the methodology section
Here, we demonstrate an integrated real-time multidimensional optical sensing system, enabled by a sensitizer and a nonlinear optical neural
As optical materials, optical fiber power transmission, and intelligent signal processing technologies continue to evolve, and the accuracy, stability, and application scope of optical fiber
Benefiting from the development of novel smart materials, nanoprocessing technologies, and optical spectra analysis techniques, many intelligent and high-performance optical waveguide
In recent years, the convergence of artificial intelligence and optical fiber sensor networks has revolutionized sensor technology, significantly enhancing performance, reliability, and efficiency.
This review summarizes recent progress and emerging trends in multiparameter optical fiber sensing, emphasizing techniques that enable the simultaneous measurement of temperature,
ML has demonstrated its effectiveness by mitigating the crosstalk issue to a higher degree and thereby enhancing the sensing performance. This unique technology has affirmed its potential in
The integration of artificial intelligence (AI) with optical fiber sensing (OFS) is transforming the capabilities of modern sensing systems, enabling smarter, more adaptive, and higher
The performance of the intelligent fiber optic integrated sensing system is compared with other POF bend sensing systems as shown in Table 2. The system realizes intelligent detection of
Here, we propose an all-optical fiber sensing architecture with in-sensor computing (AOFS-IC) that achieves fully optical-domain sensing signal demodulation at the speed of light.
Current fiber-optic distributed acoustic sensor (DAS) target recognition technologies continue to prioritize updating the feature learning tools while neglecting varying contributions of information from different
The 3-D ACNN enabled smart fiber-optic DAS (sDAS) represents a significant breakthrough, enabling fast and accurate multi-dimensional collaborative recognition. This advancement is expected to have
In essence, AI–SDM fusion transforms fiber-optic sensing from static signal demodu-lation to intelligent, adaptive, and predictive sensing systems capable of self-calibration, environmental adaptation, and
This review highlights the advancement of multidimensional detection in 2D materials. It encompasses six novel dimensionalities and hybrid-dimensional photodetectors, offering guidance for