Search Results (1,415)

Accurate stockpile volume estimation is essential for industries that manage bulk materials across various stages of production. Conventional ground-based methods such as walking wheels, total stations, Global Navigation Satellite Systems (GNSSs), and Terrestrial Laser Scanners (TLSs) have been widely used, but often involve significant safety risks, particularly when accessing hard-to-reach or hazardous areas. Unmanned Aerial Systems (UASs) provide a safer and more efficient alternative for surveying irregularly shaped stockpiles. This study evaluates UAS-based methods for estimating the volume of coal stockpiles at a storage facility near Cadiz, Ohio. Two sensor platforms were deployed: a Freefly Alta X quadcopter equipped with a Real-Time Kinematic (RTK) Light Detection and Ranging (LiDAR, active sensor) and a WingtraOne UAS with Post-Processed Kinematic (PPK) multispectral imaging (optical, passive sensor). Three approaches were compared: (1) LiDAR; (2) Structure-from-Motion (SfM) photogrammetry with a Digital Surface Model (DSM) and Digital Terrain Model (DTM) (SfM–DTM); and (3) an SfM-derived DSM combined with a kriging-interpolated DTM (SfM–intDTM). An automated boundary detection workflow was developed, integrating slope thresholding, Near-Infrared (NIR) spectral filtering, and Canny edge detection. Volume estimates from SfM–DTM and SfM–intDTM closely matched LiDAR-based reference estimates, with Root Mean Square Error (RMSE) values of 147.51 m³ and 146.18 m³, respectively. The SfM–intDTM approach achieved a Mean Absolute Percentage Error (MAPE) of ~2%, indicating strong agreement with LiDAR and improved accuracy compared to prior studies. A sensitivity analysis further highlighted the role of spatial resolution in volume estimation. While RMSE values remained consistent (141–162 m³) and the MAPE below 2.5% for resolutions between 0.06 m and 5 m, accuracy declined at coarser resolutions, with the MAPE rising to 11.76% at 10 m. This emphasizes the need to balance the resolution with the study objectives, geographic extent, and computational costs when selecting elevation data for volume estimation. Overall, UAS-based SfM photogrammetry combined with interpolated DTMs and automated boundary extraction offers a scalable, cost-effective, and accurate approach for stockpile volume estimation. The methodology is well-suited for both the high-precision monitoring of individual stockpiles and broader regional-scale assessments and can be readily adapted to other domains such as quarrying, agricultural storage, and forestry operations. Full article

The need for sustainable and long-term environmental monitoring has driven the development of energy-autonomous sensors, which either operate passively or integrate energy harvesting (EH) solutions. In many applications, the energy cost of data transmission is a critical factor in autonomous sensing systems. To address this challenge, optical passive sensors, which exploit changes in reflectivity to monitor physical parameters, offer self-sustained operation without requiring an external power source. Similarly, RF-based passive sensors, both chipless and with minimal circuitry, enable wireless monitoring with low power consumption. When more energy is available, EH techniques can be combined with active optical sensors. Infrared laser-based CO₂ sensors, as well as drone-mounted optical systems, demonstrate how EH can power precise environmental measurements. Beyond optics, other sensing modalities also benefit from EH, further expanding the range of self-powered environmental monitoring technologies. This review discusses the trade-offs between passive and EH-assisted sensing strategies, with a focus on optical implementations. The outlook highlights emerging solutions to enhance sensor autonomy while minimizing the energy cost of data transmission, paving the way for sustainable and scalable environmental monitoring. Full article

The nitrogen-vacancy (NV) center magnetic sensor, leveraging nitrogen-vacancy quantum effects, enables high-sensitivity magnetic field detection via optically detected magnetic resonance (ODMR). However, conventional single-point integrated devices suffer from limitations such as inefficient regional magnetic field detection and challenges in discerning the directional variations of dynamic magnetic fields. To address these issues, this study proposes an array- based architecture that innovatively substitutes the conventional 532 nm laser with quantum-dot light-emitting diodes (QLEDs). Capitalizing on the advantages of QLEDs—including compatibility with micro/nano-fabrication processes, wavelength tunability, and high luminance—a 2 × 2 monolithically integrated magnetometer array was developed. Each sensor unit achieves a magnetic sensitivity of below 26 nT·Hz^−1/2 and a measurable range of ±120 μT within the 1–10 Hz effective bandwidth. Experimental validation confirms the array’s ability to simultaneously resolve multi-regional magnetic fields and track dynamic field orientations while maintaining exceptional device uniformity. This advancement establishes a scalable framework for the design of large-scale magnetic sensing arrays, demonstrating significant potential for applications requiring spatially resolved and directionally sensitive magnetometry. Full article

Building upon recent advances in tactile sensing platforms such as OptoSkin, this research introduces an enhanced multi-touch sensor design that integrates Frustrated Total Internal Reflection (FTIR) technology with embedded Time-of-Flight (ToF) sensors for superior performance. Utilizing a 2 mm thick poly(methyl methacrylate) (PMMA) acrylic light guide with an area of 200 × 300 mm², the system employs the AMS TMF8828 ToF sensor both as the illumination source and the receiver. The selected PMMA, with a refractive index of 1.49, achieves an optical field of view (FoV) of approximately 32 degrees for the ToF receiver and enables signal propagation with minimal optical loss. Remarkably, a single ToF sensor can cover an active area of 195 cm² with a linear resolution of approximately 1 cm and an angular resolution of up to 3.5 degrees. This configuration demonstrates not only the feasibility of direct FTIR–ToF integration without the need for external cameras or electrode arrays but also highlights the potential for precise, scalable, and cost-effective multi-touch sensing over large surfaces. The proposed system offers robust performance even under direct sunlight conditions, setting a new benchmark for advanced tactile interface development across consumer electronics, industrial control, and robotic skin applications. Full article

In mode-locked fiber lasers and optical sensors, in-line filters are essential components. Fiber-core Mach–Zehnder interferometer (MZI) technology has garnered a lot of research interest for the several manufacturing techniques for in-line MZI filters. Although multi-line inscription is frequently needed in existing methods to attain enough waveguide width, this approach adds complexity to production and may result in compromised waveguide quality. In this work, we present an improved single-line direct-writing method that attains similar MZI filtering results to multi-line scan. Additionally, the MZI filter created with the modified single-line direct-writing technique has a smaller insertion loss and requires less direct-writing energy than the previous single-line direct-writing technique. A 516 μm long MZI-based in-line filter was successfully constructed. The results of the characterization showed a central loss dip at 1089.82 nm, a free-spectral range (FSR) of 141.36 nm, an extinction ratio of 19.69 dB, and an insertion loss of 1.122 dB. This method decreased the insertion loss by a factor of 2.7 for an identical extinction ratio and improved the direct-writing efficiency by a factor of 9 for an equivalent FSR with multi-line scan. There was consistency between the experimental and simulation results. We also took measurements of the MZI’s temperature sensitivity. This work shows notable improvements in waveguide quality and ease of manufacture. This accomplishment lays the groundwork for further advancements in integrated mode-locked fiber laser technology. Full article

Underground electrical conductors, both medium-and high-voltage, play a crucial role in energy infrastructure. However, they present a maintenance challenge due to their difficult access. Unlike overhead installations, these cables remain hidden, making it harder to obtain key parameters, such as their temperature or structural condition, in a simple manner. Current temperature measurement methods, including fiber-optic-based systems (DTS and LTS), involve high costs that limit their feasibility in medium-voltage networks, where more economically accessible alternatives are required. This study introduces an alternative system for monitoring the temperature of underground cables using NTC thermistors. Its design allows for reducing the number of connection conductors for sensors to just four regardless of the number of measurement points. The implemented measurement technique is based on the sequential activation of sensors and the integration of the recorded current to achieve an accurate thermal assessment. The tests conducted validate that this proposal represents an efficient, cost-effective, and highly scalable solution for implementation in electrical distribution networks. Full article

Fourier transform-based frequency sweeping interferometry (FT-FSI) is an interferometric technique that enables absolute distance measurement by detecting the beat frequencies from the interference of reflected signals. This method allows robust, simultaneous distance measurements to multiple targets and is largely immune to variations in the reflected optical signal intensity. As a result, FT-FSI maintains accuracy even when measuring reflectors with low reflectance. FT-FSI has recently been integrated into the full remote alignment system (FRAS) developed for the High-Luminosity Large Hadron Collider (HL-LHC) project at CERN. Designed to operate in harsh environments with electromagnetic interference, ionizing radiation and cryogenic temperatures, FRAS employs FT-FSI for the precise monitoring of the alignment of accelerator components. The system includes specialized interferometers and a range of sensors, including inclinometers, distance sensors, and leveling sensors. This paper presents a comprehensive review of the challenges associated with remote measurement and monitoring systems in harsh environments such as those of particle accelerators. It details the development and validation of the FT-FSI-based measurement system, emphasizing its critical role in enabling micrometric alignment accuracy. The developments and results presented in this work can be readily translated to other demanding metrology applications in harsh environments. Full article

Indoor sports facilities face distinctive indoor air quality (IAQ) challenges due to high occupant density, elevated metabolic emissions, and diverse pollutant sources associated with physical activity. This review presents a narrative synthesis of multidisciplinary evidence concerning IAQ in sports environments. It explores major pollutant categories, including carbon dioxide (CO₂), particulate matter (PM), volatile organic compounds (VOCs), and airborne microbial agents, highlighting their sources, behavior during exercise, and associated health risks. Research shows that physical activity can increase PM concentrations by up to 300%, and CO₂ levels frequently exceed 1000 ppm in inadequately ventilated spaces. The presence of semi-volatile organics and bioaerosols further complicates pollutant dynamics, especially in humid and densely occupied areas. Measurement technologies such as optical sensors, chromatographic methods, and molecular techniques are reviewed and compared for their applicability to dynamic indoor settings. Existing IAQ standards across China, the USA, the EU, the UK, and WHO are examined, revealing a lack of activity-specific thresholds and insufficient responsiveness to real-time conditions. Mitigation strategies (e.g., including demand-controlled ventilation, use of low-emission materials, liquid chalk substitutes, and integrated HEPA-UVGI purification systems) are evaluated, many demonstrating pollutant removal efficiencies over 80%. The integration of intelligent building management systems is emphasized for enabling real-time monitoring and adaptive control. This review concludes by identifying research priorities, including the development of activity-sensitive IAQ control frameworks and long-term health impact assessments for athletes and vulnerable users. Full article

This paper introduces a novel sensor fusion approach for the detection of multiple static and mobile targets by autonomous mobile agents. Unlike previous studies that rely on theoretical sensor models, which are considered as independent, the proposed methodology leverages real-world sensor data, which is transformed into sensor-specific probability maps using object detection estimation for optical data and converting averaged point-cloud intensities for LIDAR based on a dedicated deep learning model before being integrated through a large language model (LLM) framework. We introduce a methodology based on LLM transfer learning (LLM-TLFT) to create a robust global probability map enabling efficient swarm management and target detection in challenging environments. The paper focuses on real data obtained from two types of sensors, light detection and ranging (LIDAR) sensors and optical sensors, and it demonstrates significant improvement in performance compared to existing methods (Independent Opinion Pool, CNN, GPT-2 with deep transfer learning) in terms of precision, recall, and computational efficiency, particularly in scenarios with high noise and sensor imperfections. The significant advantage of the proposed approach is the possibility to interpret a dependency between different sensors. In addition, a model compression using knowledge-based distillation was performed (distilled TLFT), which yielded satisfactory results for the deployment of the proposed approach to edge devices. Full article

Against the backdrop of increasing demands for the safety and longevity of the bridge infrastructure, this review synthesizes the recent advances in structural health monitoring (SHM) sensing systems. Carbon nanotube (CNT), piezoelectric, RFID, wireless, fiber optic, and computer-vision-based sensing are thoroughly explored and elucidated in the existing literature survey that distills their working principles, documented deployments, and anticipated research directions. CNT sensors detect minute resistance variations for strain and crack surveillance; piezoelectric devices transduce mechanical stimuli into high-resolution electrical signals; RFID tags combine location tracking with modular sensing and wireless data relay; and wireless sensing technology integrates sensor nodes with microprocessors and communication modules, which can facilitate efficient data processing and autonomous management. Fiber optic sensing technology, known for precision and interference resistance, is ideal for high-precision monitoring under strong electromagnetic interference conditions, and vision-based systems emulate human perception to extract geometric descriptors via image analytics. The comparative analysis reveals complementary strengths that guide practitioners in selecting optimal sensor suites for specific bridge conditions. The findings underscore the transformative role of these technologies in enhancing SHM reliability and suggest that synergistic integration with robotics and emerging materials will further advance future resilient monitoring frameworks. Full article

Agriculture is facing increasing challenges due to labor shortages, rising productivity demands, and the need to operate in unstructured environments. Robotics, particularly soft robotics, offers promising solutions for automating delicate tasks such as fruit harvesting. While numerous soft grippers have been proposed, most focus on grasping and lack the capability to detach fruits with rigid peduncles, which require cutting. This paper presents a novel modular hexagonal soft gripper that integrates soft pneumatic actuators, embedded mechano-optical force sensors for real-time contact monitoring, and a self-centering iris-type cutting mechanism. The entire system is 3D-printed, enabling low-cost fabrication and rapid customization. Experimental validation demonstrates successful harvesting of bell peppers and identifies cutting limitations in tougher crops such as aubergine, primarily due to material constraints in the actuation system. This dual-capability design contributes to the development of multifunctional robotic harvesters capable of adapting to a wide range of fruit types with minimal requirements for perception and mechanical reconfiguration. Full article

The optical force exerted on a dipole particle can be divided into gradient force, scattering force, and spin–curl force, all of which can be derived from Maxwell’s stress tensor with the dipole approximation. Here, we identify an additional spin–curl force for arbitrary objects beyond the dipole approximation, which is named the generalized spin–curl force in this paper. The generalized spin–curl force originates from the Minkowski force density and depends on the imaginary parts of the permittivity, permeability, and chirality of the object. However, it remains imperceptible in conventional optical force calculations due to its exact cancellation by a compensatory surface force during MST surface integration. The study of the generalized spin–curl force provides critical insights into elucidating the mechanisms underlying optical momentum transfer and internal force distribution within complex media. Furthermore, the generalized spin–curl force offers a novel mechanism for enhancing optical sensors, enabling highly sensitive detection of absorptive or chiral perturbations in systems such as microcavities and metasurfaces. Its ability to manipulate internal force distributions also provides new pathways for advancing optical force probes and chirality-selective sensing at the nanoscale. Full article

Enzyme-based biosensors have emerged as a transformative technology, leveraging the specificity and catalytic efficiency of enzymes across various domains, including medical diagnostics, environmental monitoring, food safety, and industrial processes. These biosensors integrate biological recognition elements with advanced transduction mechanisms to provide highly sensitive, selective, and portable solutions for real-time analysis. This review explores the key components, detection mechanisms, applications, and future trends in enzyme-based biosensors. Artificial enzymes, such as nanozymes, play a crucial role in enhancing enzyme-based biosensors by mimicking natural enzyme activity while offering improved stability, cost-effectiveness, and scalability. Their integration can significantly boost sensor performance by increasing the catalytic efficiency and durability. Additionally, lab-on-a-chip and microfluidic devices enable the miniaturization of biosensors, allowing for the development of compact, portable devices that require minimal sample volumes for complex diagnostic tests. The functionality of enzyme-based biosensors is built on three essential components: enzymes as biocatalysts, transducers, and immobilization techniques. Enzymes serve as the biological recognition elements, catalyzing specific reactions with target molecules to produce detectable signals. Transducers, including electrochemical, optical, thermal, and mass-sensitive types, convert these biochemical reactions into measurable outputs. Effective immobilization strategies, such as physical adsorption, covalent bonding, and entrapment, enhance the enzyme stability and reusability, enabling consistent performance. In medical diagnostics, they are widely used for glucose monitoring, cholesterol detection, and biomarker identification. Environmental monitoring benefits from these biosensors by detecting pollutants like pesticides, heavy metals, and nerve agents. The food industry employs them for quality control and contamination monitoring. Their advantages include high sensitivity, rapid response times, cost-effectiveness, and adaptability to field applications. Enzyme-based biosensors face challenges such as enzyme instability, interference from biological matrices, and limited operational lifespans. Addressing these issues involves innovations like the use of synthetic enzymes, advanced immobilization techniques, and the integration of nanomaterials, such as graphene and carbon nanotubes. These advancements enhance the enzyme stability, improve sensitivity, and reduce detection limits, making the technology more robust and scalable. Full article

In the field of high-temperature in situ sensing, highly reflective Fabry–Perot (F-P) cavity mirrors with thermal stress matching are urgently needed. The quartz-based volume Bragg grating (VBG) can replace the dielectric high-reflection film to prepare a high-temperature and high-precision F-P cavity sensitive unit by virtue of the integrated structure of homogeneous materials. The reflectivity of the VBG is a key parameter determining the performance of the F-P cavity, and its accurate measurement is very important for the pre-evaluation of the device’s sensing ability. Based on the reflectivity measurement of quartz-based VBG with a large aspect ratio, a free-space optical path reflective measurement system is proposed. The ZEMAX simulation is used to optimize the optical transmission path and determine the position of each component when the optimal spot size is achieved. After completing the construction of the VBG reflectivity measurement system, the measurement error is calibrated by measuring the optical path loss, and the maximum error is only 1.2%. Finally, the reflectivity of the VBG measured by the calibrated system is 30.84%, which is basically consistent with the multi-physical field simulation results, showing a deviation as low as 0.85%. The experimental results fully verify the availability and high measurement accuracy of the reflectivity measurement system. This research work provides a new method for testing the characteristics of micron-scale grating size VBGs. Additionally, this work combines optical characterization methods to verify the good effect of VBG preparation technology, providing core technical support for the realization of subsequent homogeneous integrated Fabry–Perot cavity sensors. Furthermore, it holds important application value in the field of optical sensing and micro-nano integration. Full article

Star trackers are critical electro-optical devices used for satellite attitude determination, typically tested using Optical Ground Support Equipment (OGSE). Within the POR FESR 2014–2020 program (funded by Regione Toscana), we developed MINISTAR, a compact electro-optical prototype designed to generate synthetic star fields in apparent motion for realistic ground-based testing of star trackers. MINISTAR supports simultaneous testing of up to three units, assessing optical, electronic, and on-board software performance. Its reduced size and weight allow for direct integration on the satellite platform, enabling testing in assembled configurations. The system can simulate bright celestial bodies (Sun, Earth, Moon), user-defined objects, and disturbances such as cosmic rays and stray light. Radiometric and geometric calibrations were successfully validated in laboratory conditions. Under the PR FESR TOSCANA 2021–2027 initiative (also funded by Regione Toscana), the concept was further developed into STARLITE (STAR tracker LIght Test Equipment), a next-generation OGSE with a higher Technology Readiness Level (TRL). Based largely on commercial off-the-shelf (COTS) components, STARLITE targets commercial maturity and enhanced functionality, meeting the increasing demand for compact, high-fidelity OGSE systems for pre-launch verification of attitude sensors. This paper describes the working principles of a generic system, as well as its main characteristics and the early advancements enabling the transition from the initial MINISTAR prototype to the next-generation STARLITE system. Full article