The integration of multiple sensors is a crucial and emerging trend in the development of autonomous driving technology. The depth image obtained by stereo matching of the binocular camera is easily influenced by envi...
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The integration of multiple sensors is a crucial and emerging trend in the development of autonomous driving technology. The depth image obtained by stereo matching of the binocular camera is easily influenced by environment and distance. The point cloud of LiDAR has strong penetrability. However, it is much sparser than binocular images. LiDAR-stereo fusion can neutralize the advantages of the two sensors and maximize the acquisition of reliable three-dimensional information to improve the safety of automatic driving. Cross-sensor fusion is a key issue in the development of autonomous driving technology. This study proposed a real-time LiDAR-stereo depth completion network without 3D convolution to fuse point clouds and binocular images using injection guidance. At the same time, a kernel-connected spatial propagation network was utilized to refine the depth. The output of dense 3D information is more accurate for autonomous driving. Experimental results on the KITTI dataset showed that our method used real-time techniques effectively. Further, we demonstrated our solution's ability to address sensor defects and challenging environmental conditions using the p-KITTI dataset.
The article introduces a novel method that utilizes a single Fibre Bragg Grating (FBG) sensor to measure a variety of environmental factors that are crucial for the detection of marine catastrophes. The system employs...
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ISBN:
(数字)9798350364699
ISBN:
(纸本)9798350364705
The article introduces a novel method that utilizes a single Fibre Bragg Grating (FBG) sensor to measure a variety of environmental factors that are crucial for the detection of marine catastrophes. The system employs FBG sensor to monitor wave parameters, including temperature, load, force, and vibration, in order to detect tsunamis, tropical cyclones, and other marine occurrences. The proposed approach is suitable for coastal regions that are susceptible to disasters and require rapid and reliable data to facilitate prevention. This type of sensing technique enhance environmental monitoring by incorporating a variety of sensing capabilities into a single FBG sensor, thereby enhancing the reliability and integration of oceanic catastrophe detection. Durability and cost-effective real-time monitoring under severe marine conditions are guaranteed by the multi-parameter sensing system, which is specifically engineered for maritime environments.
Resilience of power systems requires mutualistically supported survivability characteristics of their cyber, physical, and cyber-physical networks. These networks of electrical and communication exchange, and their su...
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PMMA polymer optical fibers embedded in semi-structural polyurethane adhesive bonds serve as economical load sensor for structural health monitoring by evaluating load-dependent optical transmission as well as modal d...
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The increasing attention to environmental quality, food safety, and medical diagnosis requires miniaturized chemical sensors with high sensitivity, selectivity, stability, and low power consumption. Innovations in sen...
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The increasing attention to environmental quality, food safety, and medical diagnosis requires miniaturized chemical sensors with high sensitivity, selectivity, stability, and low power consumption. Innovations in sensory materials promise to empower new generations of chemical sensor technologies. Porous metal-organic frameworks (MOFs), formed from organic linkers and metal nodes, offer advantages in sensitive and selective analyte recognition through precisely tuned pore environments and molecular sieving. The promising properties promote research on implementing MOFs as an integral part of chemical sensors. This review highlights the integration of MOFs into chemical sensors, including thin-film deposition and patterning methods, signal transductions, typical sensor architectures, and device fabrications. We also discuss the sensing mechanisms in connection to the sensing performances, such as adsorption/diffusion in MOFs and MOF-analyte interactions. Critical directions for future research are proposed to stimulate the next steps to realize the practical application of MOF-based chemical sensors.
Our laboratory reported important three factors such as receptor function, transducer function and utility factor, for the material designs and their integration in 2003 and 2006, respectively. Based on the integratio...
Our laboratory reported important three factors such as receptor function, transducer function and utility factor, for the material designs and their integration in 2003 and 2006, respectively. Based on the integration of such factors, the gas sensor using Pd-loaded SnO 2 nanoclusters prepared by hydrothermal treatment could successfully detect toluene in ppb level. To enhance the sensor response more, we investigated the combination of such materials integration and pulse-heating of MEMS device, and found that such MEMS-type gas sensor has the lower detection limit for toluene gas to below 10 ppt. In addition, the Ultra-High-Sensitive detection for aliphatic compounds such as alcohol was also investigated.
In recent years, 3D printing has undergone a transformational journey - from prototyping technology, limited to laboratories, to a production method used in industry - becoming a powerful tool for creating functional ...
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In recent years, 3D printing has undergone a transformational journey - from prototyping technology, limited to laboratories, to a production method used in industry - becoming a powerful tool for creating functional objects. Despite this progress, 3D printing faces ongoing challenges related to defect detection and print quality control. We present an innovative, non-contact, fast and cheap microwave sensor for detecting defects in printed components, related to both mechanical errors and conductivity inhomogeneities. We discuss in detail the methodology of the microwave surface mapping technique and the results obtained for several samples printed with popular filaments. Tests show the ability to detect faults with millimetre precision. The simple design of the entire quality control module allows for easy integration with various types of 3D printers, from popular ones used by hobbyists to professional, highly specialised ones.
In this increasingly interconnected world, the reliance on devices for daily activities is ubiquitous. This paper presents a novel system aimed at enhancing driver safety through the integration of two critical sensor...
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ISBN:
(数字)9798350379990
ISBN:
(纸本)9798350391558
In this increasingly interconnected world, the reliance on devices for daily activities is ubiquitous. This paper presents a novel system aimed at enhancing driver safety through the integration of two critical sensors: an alcohol sensor and a heartbeat sensor. The system is meticulously designed to monitor the seriousness and physical well-being of drivers, thereby mitigating the risks associated with impaired or unhealthy individuals behind the wheel. The alcohol sensor detects the presence of alcohol in a driver's breadth, ensuring they are not under the influence—a primary contributor to road accidents. These techniques leverage sophisticated sensor technologies and real-time data analysis to enhance road safety. Despite its potential, several challenges obstruct the system's effectiveness and widespread adoption. Current systems often face high false-positive rates, privacy concerns, and issues with integrating heterogeneous sensor data. Additionally, real-time processing requirements and maintaining accuracy under varying environmental conditions pose significant hurdles. The proposed system addresses these issues by using the ThingSpeak web platform to present sensor data and take immediate action as necessary. This system offers a promising solution to modern road safety concerns, providing a robust approach to monitoring and ensuring driver fitness.
The data fusion strategy is critical in intelligent sensor mobile connected devices, however it has an issue with erroneous performance positioning. The typical ant colony algorithm is unable to address the solving st...
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ISBN:
(数字)9798350361155
ISBN:
(纸本)9798350361162
The data fusion strategy is critical in intelligent sensor mobile connected devices, however it has an issue with erroneous performance positioning. The typical ant colony algorithm is unable to address the solving strategy research issue in intelligent sensor mobile connected devices, and the result is insufficient. As a result, a Deep learning algorithms-based research on data fusion strategy of smart sensors is provided, and the research on data fusion strategy of smart sensors is assessed. To begin, the gradient descent theory is used to discover the influencing elements, and the indicators are split based on the data fusion strategy's needs to decrease interference factors in the data fusion strategy. The gradient descent theory is then used to create a Deep learning algorithms data fusion strategy scheme, and the outcomes of the data fusion strategy are thoroughly examined. The MATLAB simulation results reveal that, under particular evaluation conditions, the Deep learning algorithms outperforms the standard ant colony algorithm in terms of data fusion strategy accuracy and time of influencing variables.
Flexible power point tracking (FPPT) algorithms are proposed to make the PV inverter more friendly to the grid. However, the existing FPPT algorithm is realized based on both voltage and current sensors on the PV side...
Flexible power point tracking (FPPT) algorithms are proposed to make the PV inverter more friendly to the grid. However, the existing FPPT algorithm is realized based on both voltage and current sensors on the PV side. On the one hand, the cost is added by adopting both current and voltage sensors at the same time. On the other hand, the calculation burden is increased by calculating the PV power. Single-sensor-based MPPT algorithms have been proposed a lot in the past year, where the power of the PV is only calculated by PV current or voltage. Because the output voltage of the boost converter can be regarded as a constant in the two-stage PV inverter. It gives the opportunity to realize the single current sensor-based FPPT algorithm. So, in this paper, a single sensor-based FPPT algorithm with the maximum power point tracking (MPPT) operation and constant power generation (CPG) operation is proposed. As a result, the proposed algorithm shows advantages as high tracking performance and low hardware cost. The experimental results show the advantages of the proposed algorithm.
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