Search Results (7,800)

To monitor health risks associated with vaping, we introduce a multi-spectral optical sensor powered by machine learning for real-time characterization of electronic cigarette aerosols. The sensor can accurately measure the mass of particulate matter (PM) in specific particle size channels, providing essential information for estimating lung deposition of vaping aerosols. For the sensor’s input, wavelength-specific optical attenuation signals are acquired for three separate wavelengths in the ultraviolet, red, and near-infrared range, and the inhalation pressure is collected from a pressure sensor. The sensor’s outputs are PM mass in three size bins, specified as 100–300 nm, 300–600 nm, and 600–1000 nm. Reference measurements of electronic cigarette aerosols, obtained using a custom vaping machine and a scanning mobility particle sizer, provided the ground truth for size-binned PM mass. A lightweight two-layer feedforward neural network was trained using datasets acquired from a wide range of puffing conditions. The performance of the neural network was tested using unseen data collected using new combinations of puffing conditions. The model-predicted values matched closely with the ground truth, and the accuracy reached 81–87% for PM mass in three size bins. Given the sensor’s straightforward optical configuration and the direct collection of signals from undiluted vaping aerosols, the achieved accuracy is notably significant and sufficiently reliable for point-of-interest sensing of vaping aerosols. To the best of our knowledge, this work represents the first instance where machine learning has been applied to directly characterize high-concentration undiluted electronic cigarette aerosols. Our sensor holds great promise in tracking electronic cigarette users’ puff topography with quantification of size-binned PM mass, to support long-term personalized health and wellness. Full article

In this work, a novel optical–chemical sensor for the detection of per- and polyfluorinated substances (PFASs) in a real scenario is presented. The proposed sensing approach exploits the multimode characteristics of plastic optical fibers (POFs) to achieve unconventional sensors via surface plasmon resonance (SPR) phenomena. The sensor is realized by the coupling of an SPR-POF platform with a novel chemical chip based on different polymeric nanolayers over the core of a D-shaped POF, one made up of an optical adhesive and one of a molecularly imprinted polymer (MIP) for PFAS. The chemical chip is used to launch the light into the SPR D-shaped POF platform, so the interaction between the analyte and the MIP’s sites can be used to modulate the propagated light in the POFs and the SPR phenomena. Selectivity tests and dose–response curves by standard PFOA water solutions were carried out to characterize the detection range sensor response, obtaining a wide PFAS response range, from 1 ppt to 1000 ppt. Then, tests performed on river water samples collected from the Bormida river paved the way for the applicability of the proposed approach to a real scenario. Full article

The optical remote sensors carried by the Jilin-1 KF02 series satellites have an imaging resolution better than 0.5 m and a width of 150 km. There are radiometric problems, such as stripe noise, vignetting, and inter-slice chromatic aberration, in their raw images. In this paper, a relative radiometric correction method based on temperature normalization is proposed for the response characteristics of sensors and the structural characteristics of optical splicing of Jilin-1 KF02 series satellites cameras. Firstly, a model of temperature effect on sensor output is established to correct the variation of sensor response output digital number (DN) caused by temperature variation during imaging process, and the image is normalized to a uniform temperature reference. Then, the horizontal stripe noise of the image is eliminated by using the sensor scan line and dark pixel information, and the vertical stripe noise of the image is eliminated by using the method of on-orbit histogram statistics. Finally, the method of superposition compensation is used to correct the vignetting area at the edge of the image due to the lack of energy information received by the sensor so as to ensure the consistency of the image in color and image quality. The proposed method is verified by Jilin-1 KF02A on-orbit images. Experimental results show that the image response is uniform, the color is consistent, the average Streak Metrics (SM) is better than 0.1%, Root-Mean-Square Deviation of the Mean Line (RA) and Generalized Noise (GN) are better than 2%, Relative Average Spectral Error (RASE) and Relative Average Spectral Error (ERGAS) are greatly improved, which are better than 5% and 13, respectively, and the relative radiation quality is obviously improved after relative radiation correction. Full article

In the post-pandemic era, human demand for a healthy lifestyle and a smart society has surged, leading to vibrant growth in the field of flexible electronic sensor technology for health monitoring. Flexible polymer humidity sensors are not only capable of the real-time monitoring of human respiration and skin moisture information but also serve as a non-contact human–machine interaction method. In addition, the development of moist-electric generation technology is expected to break free from the traditional reliance of flexible electronic devices on power equipment, which is of significant importance for the miniaturization, reliability, and environmentally friendly development of flexible devices. Currently, flexible polymer humidity sensors are playing a significant role in the field of wearable electronic devices and thus have attracted considerable attention. This review begins by introducing the structural types and working principles of various humidity sensors, including the types of capacitive, impedance/resistive, frequency-based, fiber optic, and voltage-based sensors. It mainly focuses on the latest research advancements in flexible polymer humidity sensors, particularly in the modification of humidity-sensitive materials, sensor fabrication, and hygrosensitivity mechanisms. Studies on material composites including different types of polymers, polymers combined with porous nanostructured materials, polymers combined with metal oxides, and two-dimensional materials are reviewed, along with a comparative summary of the fabrication and performance mechanisms of related devices. This paper concludes with a discussion on the current challenges and opportunities faced by flexible polymer humidity sensors, providing new research perspectives for their future development. Full article

Mercury, a toxic heavy metal produced through both natural and anthropogenic processes, is found in all of Earth’s major systems. Mercury’s bioaccumulation characteristics in the human body have a significant impact on the liver, kidneys, brain, and muscles. In order to detect Hg²⁺ ions, a highly sensitive and specific fluorescent biosensor has been developed using a novel, modified seven amino acid peptide, FY7. The tyrosine ring in the FY7 peptide sequence forms a 2:1 complex with Hg²⁺ ions that are present in the water-based sample. As a result, the peptide’s fluorescence emission decreases with higher concentrations of Hg²⁺. The FY7 peptide’s performance was tested in the presence of Hg²⁺ ions and other metal ions, revealing its sensitivity and stability despite high concentrations. Conformational changes to the FY7 structure were confirmed by FTIR studies. Simultaneously, we designed a miniaturized setup to support an in-house-developed micro-volume capillary container for volume fluorometry measurements. We compared and verified the results from the micro-volume system with those from the commercial setup. The micro-volume capillary system accommodated only 2.9 µL of sample volume, allowing for rapid, sensitive, and selective detection of toxic mercury (II) ions as low as 0.02 µM. Full article

In the past few decades, there has been a notable technological advancement in geophysical sensors. In the case of magnetometry, several sensors were used, having the common feature of being miniaturized and lightweight, thus idoneous to be carried by UAVs in drone-borne magnetometric surveys. A common feature is that their sensitivity ranges from 0.1 to about 200 nT, thus not comparable to that of optically pumped, standard fluxgate or even proton magnetometers. However, their low cost, volume and weight remain very interesting features of these sensors. In fact, such sensors have the common feature of being very inexpensive, so new ways of making surveys using many of these sensors could be devised, in addition to the possibility, even with limited resources, of creating gradiometers by combining two or more of them. In this paper, we explore the range of applicability of small tri-axial magnetometers commonly used for attitude determination in several devices. We compare the results of surveys performed with standard professional geophysical instruments with those obtained using these sensors and find that in the presence of strongly magnetized sources, they succeeded in identifying the main anomalies. Full article

Ground source heat pump (GSHP) systems have been widely used in the field of shallow geothermal heating and cooling because of their high thermal efficiency and environmental friendliness. A borehole heat exchanger (BHE) is the key part of a ground source heat pump system, and its performance and investment cost have a direct and significant impact on the performance and cost of the whole system. The ground temperature gradient, air temperature, seepage flow rate, and injection flow rate affect the heat exchange performance of BHEs, but most of the research on BHEs lacks field test verification. Therefore, this study relied on the results of a field thermal response test (TRT) based on a distributed optical fiber temperature sensor (DOFTS) and site hydrological, geological, and geothermal data to establish a corrected numerical model of buried pipe heat transfer and carry out the heat transfer performance analysis of a buried pipe in the heating season. The results showed that the ground temperature gradient of the test site was about 3.0 °C/100 m, and the temperature of the constant-temperature layer was about 9.17 °C. Increasing the air temperature could improve the heat transfer performance. The temperature of the surrounding rock and soil mass of the single pipe spread uniformly, and the closer it was to the buried pipe, the lower the temperature. When there is groundwater seepage, the seepage carries the cold energy generated by a buried pipe’s heat transfer through heat convection to form a plume zone, which can effectively alleviate the phenomenon of cold accumulation. With an increase in seepage velocity, the heat transfer of the buried pipe increases nonlinearly. The heat transfer performance can be improved by appropriately reducing the temperature and velocity of the injected fluid. Selecting a backfill material with higher thermal conductivity than the ground body can improve the heat transfer performance. These research results can provide support for the optimization of the heat transfer performance of a buried tube heat exchanger. Full article

Strong mine pressure often emerges when the working face of the lower coal seam in a closely spaced coal seam system passes through the remaining coal pillar in the overlying goaf. This study investigates the law of overburden movement and the manifestation of mine pressure during mining under the remaining coal pillar. A physical model measuring 2.5 × 0.2 × 1.503 m is constructed. Fiber Bragg grating sensing technology (FBG) and Brillouin optical time domain analysis technology (BOTDA) are employed in the physical model experiment to monitor the internal strain of the overlying rock as the working face advances. This study determines the laws of overlying rock fracture and working face pressure while mining coal seams beneath the remaining coal pillar. It analyzes the relationship between the pressure at the working face and the strain characteristics of the horizontally distributed optical fiber. A fiber grating characterization method is established for the stress evolution law of overlying rock while passing the remaining coal pillar. The experimental results indicated that the fracture angle of overlying rock gradually decreases during the mining stage through and after the coal pillar. In the mining stage through the coal pillar, the cycle pressure step distance of the working face is reduced by 33.3% compared to the stage after mining through the coal pillar. Initially, the strain pattern of the horizontal optical fiber is unimodal when pressure is first applied to the working face, and it transitions from unimodal to bimodal during periodic pressure. The peak value of fiber Bragg grating compressive strain and the range of influence of advanced support pressure are 3.6 times and 4.8 times, respectively, before passing through the remaining coal pillar. Finally, the accuracy of the FBG characterization method is verified by comparing it to the monitoring curve of the coal seam floor pressure sensor. The research results contribute to applying fiber optic sensing technology in mining physical model experiments. Full article

Sentinel-2/MSI and Landsat-8/OLI sensors enable the mapping of ocean color-related bio-optical parameters of surface coastal and inland waters. While many algorithms have been developed to estimate the Chlorophyll-a concentration, Chl-a, and the suspended particulate matter, SPM, from OLI and MSI data, the absorption by colored dissolved organic matter, a_cdom, a key parameter to monitor the concentration of dissolved organic matter, has received less attention. Herein we present an inverse model (hereafter referred to as AquaCDOM) for estimating a_cdom at the wavelength 412 nm (a_cdom (412)), within the surface layer of coastal waters, from measurements of ocean remote sensing reflectance, R_rs (λ), for these two high spatial resolution (around 20 m) sensors. Combined with a water class-based approach, several empirical algorithms were tested on a mixed dataset of synthetic and in situ data collected from global coastal waters. The selection of the final algorithms was performed with an independent validation dataset, using in situ, synthetic, and satellite R_rs (λ) measurements, but also by testing their respective sensitivity to typical noise introduced by atmospheric correction algorithms. It was found that the proposed algorithms could estimate a_cdom (412) with a median absolute percentage difference of ~30% and a median bias of 0.002 m⁻¹ from the in situ and synthetic datasets. While similar performances have been shown with two other algorithms based on different methodological developments, we have shown that AquaCDOM is much less sensitive to atmospheric correction uncertainties, mainly due to the use of band ratios in its formulation. After the application of the top-of-atmosphere gains and of the same atmospheric correction algorithm, excellent agreement has been found between the OLI- and MSI-derived a_cdom (412) values for various coastal areas, enabling the application of these algorithms for time series analysis. An example application of our algorithms for the time series analysis of a_cdom (412) is provided for a coastal transect in the south of Vietnam. Full article

During recent years, the optical-fiber-based simultaneous sensing of strain and temperature has attracted increased interest for different applications, e.g., in medicine, architecture, and aerospace. Specialized fiber layouts further enlarge the field of applications at much lower costs and with easier handling. Today, the performance of many sensors fabricated from conventional fibers suffers from cross-sensitivity (temperature and strain) and relatively high interrogation costs. In contrast, customized fiber architectures would make it possible to circumvent such sensor drawbacks. Here, we report on the development of a high-quality coupled-core fiber and its performance for sensors—from the initial fiber layout via elaboration of the preform and fiber up to the sensor evaluation. A compact, high-speed, and cost-effective interrogation unit using such a specialized coupled-core fiber has been designed to monitor reflectivity changes while even being able to distinguish the direction of the force or impact. Several fiber core material techniques and approaches were investigated, which made it possible to obtain a sufficient volume of material for the required fiber core number and a specialized fiber core geometry in terms of core distances and radial refractive index profile, whilst handling the non-symmetrical fiber architectures of such modeled, complex structures and balancing resources and efforts. Full article

Industrial microwave-heating systems are pivotal in various sectors, including food processing and materials manufacturing, where precise temperature control and safety are critical. Conventional systems often struggle with uneven heat distribution and high fire risks due to the intrinsic properties of microwave heating. In this work, a fiber-optic-sensor-assisted monitoring system is presented to tackle the pressing challenges associated with uneven heating and fire hazards in industrial microwave systems. The core innovation lies in the development of a sophisticated fiber-optic 2D temperature distribution sensor and a dedicated fire detector, both designed to significantly mitigate risks and optimize the heating process. Experimental results set the stage for future innovations that could transform the landscape of industrial heating technologies toward better process quality. Full article

In this work, we demonstrate the use of a chromatic confocal sensor for long-distance measurements. The sensor increases the working distance of state-of-the-art confocal sensors by a factor of 10, reaching a working distance of 620 mm. The chromatic aberration exhibited by a lens was utilized to establish the working range. The chromatic dispersion of the optics led to images of the different wavelength components at different longitudinal points along the optical axis. The sensor employs a robust algorithm to measure relative displacements of the sample’s motion. The calibration process simplifies data analysis and improves the accuracy of displacement measurements in experimental setups. To facilitate the design process, a simulator was developed specifically for this purpose. The calibration data obtained in both the experimental and the simulated data show that the simulator was able to predict the sensitivity with an error of 5%. We also describe the effect on the sensitivity of oversampling the spectrum. In addition, the superiority of low-pass filtering over Gaussian fitting over the detected spectrum is shown. Full article

A new-type vibration sensor based on a fiber Bragg grating combined with a special structure-packaged design is proposed for monitoring the mechanical vibration signals. Three different sensing structures, including the film squeeze type, new film squeeze type, and elastic tape squeeze type are proposed for measuring the vibration signals with the frequency range from tens to thousands of Hz. In the comparison to experimental results, the new film squeeze structure has a nice sensing performance in the range from 100 to 1000 Hz with a sensitivity of 0.302 mV/g. For the elastic tape squeeze structure, the elastic tape is designed to encapsulate the optical fiber with a good frequency response from 1100 to 3100 Hz. In addition, by using the new film squeeze structure to measure the steady-state and non-steady-state vibration signals, the spectral components of sensing signals are analyzed by using the wavelet transformation for confirming the testing signals. These vibration fiber sensors can be applied in the measurement of high-end manufacture-facility vibration or earthquake vibrations etc. Full article

Waste material classification is critical for efficient recycling and waste management. This study proposes a novel, low-cost material classification system based on a single, voltage-tunable Ge-on-Si photodetector operating across the visible and short-wave infrared (SWIR) spectral regions. Thanks to its tunability, the sensor is able to extract spectral information, and the system effectively distinguishes between seven different materials, including plastics, aluminum, glass, and paper. The system operates with a broadband illuminator, and material identification is obtained through the processing of the photocurrent signal at different bias voltages with classification algorithms. Here, we demonstrate the basic system functionality and near real-time classification of different waste materials. Full article

The main purpose of this study was to create a prototype of an unmanned aerial system equipped with intelligent hardware and software technologies necessary for surveillance and monitoring the health and growth of crops from orchards with vines and fruit trees. Using low-cost sensors that accurately measure ultraviolet solar radiation was an important objective. The device, which needed to be attached to the commercial DJI Mini 4 Pro drone, had to be small, portable, and have low energy consumption. For this purpose, the widely used Vishay VEML6075 digital optical sensor was selected and implemented in a prototype, alongside a Raspberry Pi Zero 2 W minicomputer. To collect data from these sensors, a program written in Python was used, containing specific blocks for data acquisition from each sensor, to facilitate the monitoring of ultraviolet (UV) radiation, or battery current. By analyzing the data obtained from the sensors, several important conclusions were drawn that may provide valuable pathways for the further development of mobile or modular equipment. Furthermore, the plantation state analysis results with proposed models in the geographic information system (GIS) environment are also presented. The visualization of maps indicating variations in vegetation conditions led to identifying problems such as hydric stress. Full article