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[IEEE 2018 IEEE International Conference on Intelligent Transportation Systems (ITSC) - Maui, HI, USA (2018.11.4-2018.11.7)] 2018 21st International Conference on Intelligent Transportation Systems (ITSC) - Automotive LiDAR performance verification in fog and rain
摘要： This article focuses on testing and investigating further development needs for LiDARs in self-driving cars in adverse weather. The article compares two different LiDARs (Ibeo Lux and Velodyne PUCK), which both use the 905 nm wavelengths, which are used in more than 95 % of currently available LiDARs. The performance was tested and estimated in stabilized fog conditions at Cerema fog chamber facilities. This provides a good basis for repeating the same validation procedure multiple times and ensuring the right development decisions. However, performance of the LiDARs suffers when the weather conditions become adverse and visibility range decreases. A 50 % reduction in target detection performance was observed over the exhaustive tests. Therefore, changing to higher wavelengths (1550 nm) was considered using redesigned “pre-prototype LiDAR”. The preliminary results indicate that there is no reason to not use 1550 nm wavelength, which due to eye safety regulations gives an opportunity to use 20 times more power compared to the traditional 905 nm. In order to clarify the expected benefits, additional feasibility studies are still needed.
关键词： self-driving cars,LiDAR,sensor performance,1550 nm,905 nm,adverse weather,rain,fog
更新于2025-09-04 15:30:14
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[IEEE 2018 IEEE International Conference on Intelligent Transportation Systems (ITSC) - Maui, HI, USA (2018.11.4-2018.11.7)] 2018 21st International Conference on Intelligent Transportation Systems (ITSC) - Multimodal CNN Pedestrian Classification: A Study on Combining LIDAR and Camera Data
摘要： This paper presents a study on pedestrian classification based on deep learning using data from a monocular camera and a 3D LIDAR sensor, separately and in combination. Early and late multi-modal sensor fusion approaches are revisited and compared in terms of classification performance. The problem of pedestrian classification finds applications in advanced driver assistance system (ADAS) and autonomous driving, and it has regained particular attention recently because, among other reasons, safety involving self-driving vehicles. Convolutional Neural Networks (CNN) is used in this work as classifier in distinct situations: having a single sensor data as input, and by combining data from both sensors in the CNN input layer. Range (distance) and intensity (reflectance) data from LIDAR are considered as separate channels, where data from the LIDAR sensor is feed to the CNN in the form of dense maps, as the result of sensor coordinate transformation and spatial filtering; this allows a direct implementation of the same CNN-based approach on both sensors data. In terms of late-fusion, the outputs from individual CNNs are combined by means of learning and non-learning approaches. Pedestrian classification is evaluated on a 'binary classification' dataset created from the KITTI Vision Benchmark Suite, and results are shown for each sensor-modality individually, and for the fusion strategies.
关键词： pedestrian classification,camera,deep learning,sensor fusion,LIDAR,CNN
更新于2025-09-04 15:30:14
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Demodulation of a Hydroacoustic Sensor Array of Fiber Interferometers Based on Ultra-weak Fiber Bragg Grating Reflectors Using a Self-referencing Signal
摘要： We report on current theoretical and experimental results of hydroacoustic sensing array based on ultra-weak Fiber Bragg Gratings (FBG), using a modified phase generated carrier (PGC) demodulation method with a self-referencing signal. The self-referencing signal is obtained by a sensor isolated from acoustic signals and other environmental disturbances. We report improvements over the conventional PGC methods. Using our demodulation method and with non-sensitized bare fiber (reference sensor0) keeping separate from water, experiment testing demonstrates a minimum detectable hydroacoustic pressure of 2239 μPa/√Hz. The properties of our demodulation method are also compared with those of the conventional PGC algorithms. Both simulation and experiments indicate that our demodulation method is immune to the drifts of modulation depth C and of carrier frequency, and the detectable frequency range can be increased by 5 times compared to using conventional PGC methods with the same carrier frequency. The sensor array exhibits a particularly large response in the very low frequency (VLF) region, which is of great importance for underwater seismic detection and submarine applications.
关键词： FBG,hydroacoustic sensor,vibrating liquid,self-referencing,acoustic pressure column of sensitivity
更新于2025-09-04 15:30:14
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Pixels and 3-D Points Alignment Method for the Fusion of Camera and LiDAR Data
摘要： The fusion of light detection and ranging (LiDAR) and camera data is a promising approach to improve the environmental perception and recognition for intelligent vehicles because of the combination of depth and color information. One of the dif?culties in achieving the fusion is the accurate alignment of the 3-D points with the image pixels. Current methods of data alignment involve the steps of estimating the camera intrinsic parameters and developing a transformation matrix between the camera and LiDAR frame. The drawback of these methods is the accumulation of errors during the calculation of the camera intrinsic parameters and the transformation matrix. In order to improve the data alignment accuracy, we propose a novel algorithm that directly calculates the alignment between the 3-D points and the pixels without the need for camera parameters and calibration of the coordinate transformation matrix. We call the proposed method the pixel and 3-D point alignment (PPA) method. The alignment procedure is achieved by using the extracted corresponding points. First, we calculate a linear alignment matrix without considering the image distortion; and second, we optimize the parameters using the maximum likelihood estimation to consider the camera distortion. Simulation and experimental results indicate that the PPA method is able to align the 3-D points in LiDAR frame with the pixels in image frame with higher accuracy and increased robustness against noise in calibration process than comparable state-of-the-art methods.
关键词： intelligent vehicle,sensor fusion.,calibration,camera and light detection and ranging (LiDAR),Autonomous driving
更新于2025-09-04 15:30:14
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Noncontact Electrical Probe for Monitoring Cellular Processes in Primary Retinal Explants
摘要： Quantitative assessment involving noncontact electrical methods without the need for microscopy can enable a remote user to monitor the cell growth and development at different stages. In this line of pursuit, the utility of ultrahigh impedance, air-suspended capacitively coupled electric potential sensors to monitor electrically active cells is examined. Standard cell lines and chick retinal explants on a variety of optoelectronically active polymer substrates are utilized to demonstrate the utility of this sensor placed in proximity without physical contact. Burst firing in developing chick retina in the early stage when photoreceptors are not developed can be observed via the photoexcitation of optoelectronic substrates using this noncontact sensing method.
关键词： noncontact sensor,burst firing,optoelectronic polymers
更新于2025-09-04 15:30:14
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A liquid crystal based method for detection of urease activity and heavy metal ions by using stimulus-responsive surfactant-encapsulated phosphotungstate clusters
摘要： A liquid crystal (LC) based method is described for the sensitive determination of the activity of urease and of heavy metal ions which acts as inhibitors. Stimulus-responsive surfactant-encapsulated phosphotungstate clusters (SECs) were fabricated and deposited onto octadecyltrichlorosilane-coated glass. A copper TEM grid filled with LCs was placed on the substrate to construct the LC optical cell. Upon addition of water to the LC interface, the optical appearance of LCs on the glass undergoes a bright-to-dark shift due to an orientational transition of the LCs from a planar to a homeotropic state. However, the LCs display a bright appearance if they are pretreated with an aqueous solution containing urea and urease. This is caused by the disassemby of the SECs from the glass surface due to an increase of the pH value that is induced by the enzymatic hydrolysis of urea by urease. The method is highly sensitive and can detect urease activities as low as 0.03 mU/mL. It can also be applied to the determination of heavy metal ions which exert an inhibitory effect on the activity of urease. For example, Cu(II) can be quantified via urease inhibition in 1 nM concentration.
关键词： Ionic liquid,Stimulus-responsive material,Surfactant,Sensor layer,Polyoxometalates,Urease,Nanocomposites,Ionic self-assembly,Liquid crystal
更新于2025-09-04 15:30:14
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Assessing the Reliability of Thermal and Optical Imaging Techniques for Detecting Crop Water Status under Different Nitrogen Levels
摘要： Efficient management of irrigation water is fundamental in agriculture to reduce the environmental impacts and to increase the sustainability of crop production. The availability of adequate tools and methodologies to easily identify the crop water status in operating conditions is therefore crucial. This work aimed to assess the reliability of indices derived from imaging techniques—thermal indices (Ig (stomatal conductance index) and CWSI (Crop Water Stress Index)) and optical indices (NDVI (Normalized Difference Vegetation Index) and PRI (Photochemical Reflectance Index))—as operational tools to detect the crop water status, regardless the eventual presence of nitrogen stress. In particular, two separate experiments were carried out in a greenhouse, on two spinach varieties (Verdi F1 and SV2157VB), with different microclimatic conditions and under different levels of water and nitrogen application. Statistical analysis based on ANOVA test was carried out to assess the independence of thermal and optical indices from the crop nitrogen status. These imaging indices were successively compared through correlation analysis with reference destructive and non-destructive measurements of crop water status (stomatal conductance, chlorophyll a fluorescence, and leaf and soil water content), and linear regression models of thermal and optical indices versus reference measurements were calibrated. All models were significant (Fisher p-value lower than 0.05), and the highest R2 values (greater than 0.6) were found for the regression models between CWSI and the soil water content, NDVI and the leaf water content, and PRI and the stomatal conductance. Further analysis showed that imaging indices acquired by thermal cameras (especially CWSI) can be used as operational tools to detect the crop water status, since no dependence on plant nitrogen conditions was observed, even when the soil water depletion was very limited. Our results confirmed that imaging indices such as CWSI, NDVI and PRI can be used as operational tools to predict soil water status and to detect drought stress under different soil nitrogen conditions.
关键词： crop water status,crop water stress prediction,optical imaging sensor,thermal camera,spectral imaging index
更新于2025-09-04 15:30:14
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High‐Performance, Transparent Thin Film Hydrogen Gas Sensor Using 2D Electron Gas at Interface of Oxide Thin Film Heterostructure Grown by Atomic Layer Deposition
摘要： A high-performance, transparent, and extremely thin (<15 nm) hydrogen (H2) gas sensor is developed using 2D electron gas (2DEG) at the interface of an Al2O3/TiO2 thin film heterostructure grown by atomic layer deposition (ALD), without using an epitaxial layer or a single crystalline substrate. Palladium nanoparticles (≈2 nm in thickness) are used on the surface of the Al2O3/TiO2 thin film heterostructure to detect H2. This extremely thin gas sensor can be fabricated on general substrates such as a quartz, enabling its practical application. Interestingly, the electron density of the Al2O3/TiO2 thin film heterostructure can be tailored using ALD process temperature in contrast to 2DEG at the epitaxial interfaces of the oxide heterostructures such as LaAlO3/SrTiO3. This tunability provides the optimal electron density for H2 detection. The Pd/Al2O3/TiO2 sensor detects H2 gas quickly with a short response time of <30 s at 300 K which outperforms conventional H2 gas sensors, indicating that heating modules are not required for the rapid detection of H2. A wide bandgap (>3.2 eV) with the extremely thin film thickness allows for a transparent sensor (transmittance of 83% in the visible spectrum) and this fabrication scheme enables the development of flexible gas sensors.
关键词： gas sensor,oxide heterostructure,thin film,atomic layer deposition,hydrogen
更新于2025-09-04 15:30:14
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Pipeline leakage identification and localization based on the fiber Bragg grating hoop strain measurements and particle swarm optimization and support vector machine
摘要： A pipeline's safe usage is of critical concern. In our previous work, a fiber Bragg grating hoop strain sensor was developed to measure the hoop strain variation in a pressurized pipeline. In this paper, a support vector machine (SVM) learning method is applied to identify pipeline leakage accidents from different hoop strain signals and then further locate the leakage points along a pipeline. For leakage identification, time domain features and wavelet packet vectors are extracted as the input features for the SVM model. For leakage localization, a series of terminal hoop strain variations are extracted as the input variables for a support vector regression (SVR) analysis to locate the leakage point. The parameters of the SVM/SVR kernel function are optimized by means of a particle swarm optimization (PSO) algorithm to obtain the highest identification and localization accuracy. The results show that when the RBF kernel with optimized C and γ values is applied, the classification accuracy for leakage identification reaches 97.5% (117/120). The mean square error value for leakage localization can reach as low as 0.002 when the appropriate parameter combination is chosen for a noise‐free situation. The anti‐noise capability of the optimized SVR model for leakage localization is evaluated by superimposing Gaussian white noise at different levels. The simulation study shows that the average localization error is still acceptable (≈500 m) with 5% noise. The results demonstrate the feasibility and robustness of the PSO–SVM approach for pipeline leakage identification and localization.
关键词： pipeline leakage localization,method of characteristics (MOC),FBG hoop strain sensor,support vector regression (SVR),particle swarm optimization (PSO) algorithm,support vector machine (SVM)
更新于2025-09-04 15:30:14
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Construction of Ce-MOF@COF hybrid nanostructure: Label-free aptasensor for the ultrasensitive detection of oxytetracycline residues in aqueous solution environments
摘要： Porous organic framework (COF) nanomaterials have drawn increasing attention and showed promising potential in the applications of various fields. Nevertheless, its applications in biosensing or biomedical fields are still in the early stage. In this work, we designed and synthesized a series of nanohybrids of COF and Ce-based metal organic framework (Ce-MOF) for the first time as label-free bioplatforms for a sensitive electrochemical aptasensor to detect oxytetracycline (OTC). A novel kinds of Ce-MOF@COF hybrids were prepared by adding different dosages of COF, into the preparation system of Ce-MOF, for which COF was synthesized using melamine and cyanutic acidmonomers through polycondensation (represented by MCA). Basic characterizations revealed that Ce-MOF@MCA nanohybrids not only remained their orignal crystal and chemical structure and features, such as different Ce species containing in Ce-MOF (Ce3+ and Ce4+), various functional amino-groups of MCA, and individual frameworks, but also showed a large specific surface area and interpenetrated morphologies. As a result, the Ce-MOF@MCA hybrid with high content of MCA exhibited high bioaffinity toward the OTC-targeted aptamer, further leading to the incremental detection effect for OTC detection. Among different hybrid-based aptasensors, the Ce-MOF@MCA-based one with an MCA dosage of 500 mg exhibited the lowest limit of detection at 17.4 fg?mL-1 within a wider linearity of the OTC concentration within 0.1–0.5 ng?mL-1. Additionally, the fabricated aptasensor displayed excellent analytical performance with great reproducibility, high selectivity and stability, and acceptable applicability for detecting OTC in various aqueous solutions, including milk, wastewater, and urine samples. This new Ce-MOF@MCA hybrid will become an excellent aptasensors platform for detecting various analytes, such as antibiotics, heavy metal ions, or cancer markers, and it have shown the promissing application potentials in the fields of biomedicine, food safety and environmental monitoring.
关键词： Ce-based metal organic frameworks,Aptamer sensor,Detection of oxytetracycline,Electrochemical impedance spectroscopy,Covalent organic frameworks
更新于2025-09-04 15:30:14