Editorial for the Special Issue “Optical Sensing Technologies, Devices and Their Data Applications”

1. Introduction

Optical sensing technologies represent a pivotal advancement in contemporary science and engineering, leveraging the unique properties of light to probe and analyze phenomena ranging from microscopic molecular interactions to large-scale atmospheric processes. As the Guest Editor of this Special Issue, I am pleased to introduce a comprehensive collection of 11 original research articles that push the boundaries of optical sensor design, device innovation, and data-centric applications. This Special Issue, now consolidated into a book format, highlights the interdisciplinary fusion of photonics, materials science, signal processing, and artificial intelligence, drawing from diverse contributions from researchers across Asia, Europe, and North America.

The overarching theme of this Special Issue, “Optical Sensing Technologies, Devices and Their Data Applications,” was ways to tackle emerging challenges in areas such as environmental monitoring, biomedical imaging, industrial quality control, and atmospheric analysis. Techniques encompassing lidar, spectroscopy, fiber-optics, adaptive optics, and optofluidics provide exceptional sensitivity, non-contact operation, and resilience under demanding conditions. However, the full potential of these technologies is realized through sophisticated data handling, including machine learning algorithms and enhanced signal processing, which transform raw sensor outputs into meaningful intelligence. Manuscripts were solicited on topics like novel sensor architectures, hybrid opto-acoustic systems, AI-driven analytics, and waveguide innovations, with foci on gas detection, turbulence compensation, and biometric applications.

The 11 articles featured here form a cohesive narrative of theoretical insights, experimental breakthroughs, and practical deployments. They address critical issues such as noise reduction, polarization maintenance, and real-time data acquisition, while demonstrating applications from trace gas sensing to defect detection. As this Special Issue evolves into a dedicated book, it can serve as an essential resource for scholars and practitioners, fostering the integration of optical hardware with advanced computational frameworks. In the ensuing sections, I outline the articles, organized thematically to illuminate their synergistic contributions.

2. Advances in Optical Sensor Design and Gas Detection

Fundamental progress in optical sensing hinges on refined device configurations and methodologies that elevate detection precision and efficiency. This Special Issue showcases several works in this vein, emphasizing viscosity assessment, trace gas monitoring, and spectroscopic enhancements.

Contribution 1 presents a novel “viscosity–diffusion coupling” system employing a liquid-core cylindrical lens (LCL) for swift, concentration-dependent viscosity measurements. By imaging focal planes and numerically resolving Fick’s second law alongside the Stokes–Einstein relation, the authors enable continuous viscosity profiling across 0–50% glycerol solutions at varying temperatures, aligning closely with established data and streamlining fluid analysis in industrial contexts.

In the area of atmospheric sensing, Contribution 2 advances a dual-wavelength lidar fusion approach at 355 nm and 532 nm for accurate atmospheric boundary layer (ABL) height determination. Weighting polarized signals by their signal-to-noise ratios and validating against radiosonde and ERA5 datasets, this method suppresses aerosol noise, delivering reliable ABL estimates in urban environments like Beijing, thereby supporting air quality and meteorological modeling.

Contribution 4 introduces a cost-efficient cavity ring-down spectroscopy (CRDS) system for ppb-level hydrogen sulfide (H2S) detection, featuring a digital locking circuit that boosts frequency precision 140-fold to 0.07 MHz uncertainty. With a 2 ppb detection threshold (3σ) and sub-ppb sensitivity per Allan variance, this analyzer fulfills industrial safety and environmental needs.

Complementing this theme, Contribution 7 enhances tunable diode laser absorption spectroscopy (TDLAS) for methane via Savitzky–Golay filtering in a 29.37 m path-length cell. Elevating the signal-to-noise ratio by 1.84 times, it achieves 0.53 ppm accuracy at 92 ppm levels, advancing high-precision monitoring for atmospheric and industrial uses.

These contributions collectively propel optical sensors toward greater sensitivity and applicability in gas and fluid detection.

3. Adaptive Optics and Turbulence Management

Turbulence poses a persistent obstacle in optical systems, impairing resolution and energy focus. This section highlights innovations in adaptive optics for simulation and correction, facilitating transitions from lab to real-world scenarios.

Contribution 3 describes a 500 Hz adaptive optical setup with dual bimorph deformable mirrors and tip-tilt correctors, integrated with a Shack–Hartmann sensor. It reconstructs turbulence aberrations, reducing them from 2.6 μm to 0.3 μm and minimizing focal spot jitter by 2–3 times, proving invaluable for astronomical and laser applications.

This focus on dynamic wavefront control bolsters data fidelity in turbulent settings, aligning with broader sensing reliability goals.

4. Optofluidics, Waveguides, and Fiber-Optic Innovations

The intersection of optics and microfluidics yields compact, versatile platforms for sensing and integration. The contributions to this theme explore waveguide arrays, polarized fibers, and tunable interferometers.

Contribution 5 unveils a broadband RGB fluorescent waveguide array using water-soluble CdSe/ZnS quantum dots (QDs) in an optofluidic chip. Analyzing propagation losses and optimizing concentrations, it extends to a 3 × 3 PDMS-based display, ideal for on-chip spectroscopy and biochemical sensing.

Contribution 10 models a fully polarized optical fiber with a prism head for plane wave compression, maintaining linear polarization via FDTD simulations. This design enhances the intensity for photonic integrated circuits and sensors, offering a simplified fabrication route.

Contribution 9 proposes an angle-tunable technique to optimize rear reflectance in Fabry–Pérot interferometers for fiber-optic ultrasound sensing. By modulating stress and adhesives to symmetrize transmittance curves, it minimizes errors and detects ultrasound signals at slope extrema, reducing costs for medical and structural monitoring.

These advancements underscore the potential of integrated optical structures in diverse sensing paradigms.

5. Data Acquisition and AI-Enhanced Processing Applications

The influx of optical data necessitates robust acquisition and AI tools for pattern extraction and decision-making. This Special Issue concludes with works integrating spectroscopy, deep learning, and vision for greenhouse gas monitoring, biometrics, and quality inspection.

Contribution 6 develops a dual-channel ADC method for interferogram acquisition in ground-based FTIR spectrometers, capturing high- and low-gain signals to boost the dynamic range. Applied to CO₂ retrieval, it doubles measurement accuracy, enhancing climate surveillance.

Contribution 8 introduces a dual-stream deep network with attention mechanisms for age estimation from transmission near-infrared dorsal hand vein images. On a 300-subject dataset, it leverages a CNN and residuals to focus on vein textures, outperforming baselines in biometric accuracy.

Finally, Contribution 11 optimizes YOLOv5 for cork disk quality detection in badminton manufacturing. Incorporating GAN-based defect synthesis, attention modules, and refined anchor strategies, it achieves a 95.1% F1 score and 178.5 FPS, surpassing originals in efficiency and precision for industrial vision.

These AI-infused methods not only amplify detection capabilities but also tackle practical challenges in data integrity and automation.

6. Conclusions

This Special Issue, now immortalized in book form, captures a transformative era in optical sensing, where device ingenuity converges with data analytics to address pressing global issues in environment, health, industry, and beyond. The 11 articles—from lidar fusion for atmospheric profiling to AI-optimized defect detection—exemplify strides in sensitivity, integration, and intelligence. They embody the collaborative ethos of our authors, whose varied perspectives have enriched this Special Issue.

As the Guest Editor, I express my profound thanks to all authors, reviewers, and the Photonics editorial staff for their dedication. This volume not only documents current achievements but also beckons future pursuits in quantum sensing, sustainable optics, and AI synergies. It is my hope that it ignites innovation among emerging photonics experts to unveil new horizons.