This study addresses the issue of missing data in High-Frequency radar (HFR) measurements, which are crucial for monitoring ocean surface currents and supporting maritime operations and environmental studies. However,...
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This paper proposes a multi-sensor positioning technology for unmanned aerial vehicle (UAV) landing based on inertial navigation system (INS)/Global navigation satellite system (GNSS)/radar integrated guidance system....
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This paper proposes a multi-sensor positioning technology for unmanned aerial vehicle (UAV) landing based on inertial navigation system (INS)/Global navigation satellite system (GNSS)/radar integrated guidance system. In the harsh environment where sensor prior information is unreliable, measurement noise is non-stationary and measurement outliers are frequently generated, an adaptive federated filter based on variational Bayesian is used to achieve high accuracy and robustness of navigation system. Simulation results demonstrate that this guidance technology has a strong ability to adapt to non-stationary noise and frequent outliers, and the fusion accuracy is satisfactory.
Non-vegetated volcanic surfaces are rare on Earth, but are important test beds for preparing an interplanetary mission to Venus, Earth's neighbour, which has a very similar structure and volcanic activity. Both NA...
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5G monitoring holds immense potential for revolutionizing manufacturing processes by enabling real-time data transmission, remote control, enhanced quality control, and increased efficiency. However, it also presents ...
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5G monitoring holds immense potential for revolutionizing manufacturing processes by enabling real-time data transmission, remote control, enhanced quality control, and increased efficiency. However, it also presents challenges related to 5G monitoring infrastructure. To explore 5G's potential for process monitoring, this study introduces a novel 5G-enabled architecture designed to address the challenges, enhancing the process monitoring's efficiency, accuracy, and reliability in the case of milling operation. To investigate the feasibility of this sophisticated 5G network for process monitoring, two testbeds, i.e., the 5G robotic milling testbed and the 5G CNC milling testbed, have been developed. An accelerometer and a laser scanner have been retrofitted with 5G communications capability to capture critical process signals in the testbeds, respectively. It has shown that the sensordata can be upstreamed to a 5G edge server for data analytics and visualization in ultra-low latency. This work highlights the transformative impact of 5G communication on process monitoring for time-critical manufacturing.
Observing topology and communication process in real time is critical for dealing with unexpected situations of Underwater Wireless sensor Networks (UWSNs). However, due to low bandwidth, limited energy, and severe co...
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The proceedings contain 86 papers. The topics discussed include: automatic integration method for multi-source communication data based on graph deep learning;semantic query technology for academic planning service sy...
ISBN:
(纸本)9798350376258
The proceedings contain 86 papers. The topics discussed include: automatic integration method for multi-source communication data based on graph deep learning;semantic query technology for academic planning service system based on comparative learning improvement;research on the construction method and application of personalized learner portraits based on machine learning;discovery of obstacles to fusion of millimeter wave radar and visual sensor;image tampering detection method based on dilated convolution;air quality level detection based on image recognition;depth estimation method for monocular images combined with position estimation;talent recommendation algorithm integrating knowledge GRAP;and method for assisting in the selection of shared bicycle deployment points based on multi-source data optimization.
This study proposes a novel approach for predicting the output behaviors of the Pepperl+Fuchs 3RG6232-3JS00-PF ultrasonic sensor. The sensor, integrated into the Festo MPS-PA Didactic System, serves to monitor the wat...
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ISBN:
(纸本)9783031761966;9783031761973
This study proposes a novel approach for predicting the output behaviors of the Pepperl+Fuchs 3RG6232-3JS00-PF ultrasonic sensor. The sensor, integrated into the Festo MPS-PA Didactic System, serves to monitor the water level in a tank, facilitating water extraction to bottles delivered via a conveyor belt. This modeling approach represents the initial phase in the creation of a digital twin of the physic al sensor, providing the capability for users to observe the sensor's response and forecast its life cycle for maintenance objectives. This study utilizes the FestoMPS-PA Complete Didactic system and Support Vector Regression for data acquisition, preprocessing, model training with hyperparameter optimization. The objective of this modeling approach is to establish a digital framework for Vietnam to transition towards Industry 4.0. It holds the potential for creating a digital counterpart of the entire MPS-PA System when combines the proposed sensor modeling technique with Computer-Aided Design software such as Siemens NX in the future. This would enable users to oversee the entire process in a three-dimensional visualization engine such as Tecnomatix Plant Simulation. This research significantly contributes to the comprehension and application of digital twins in the realm of mechatronics and sensor systems technology. It also underscores the importance of digital twins in enhancing the efficiency and predictability of sensor systems. The method used in this paper involves predicting the rate of change of the water level and then integrating this rate to estimate the actual water level, providing a robust approach for sensordata modeling and digital twin creation. The result shows a promising 6.99% error percentage.
For automotive radar-based extended object tracking (EOT), the Doppler velocity is not always fully exploited. Strong nonlinearities may exist due to the relative angle (or spatial position) between a scattering cente...
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The traffic incident detection system is a vital tool for highway tunnel managers to monitor real-time traffic conditions inside the tunnel. Traditional traffic incident detection systems rely on a single data source,...
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Vehicle detection is an area of active development aimed at enhancing driving safety and ensuring compliance with traffic regulations. Despite ongoing efforts, accidents and traffic violations continue to pose signifi...
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ISBN:
(纸本)9798350389937;9798350389920
Vehicle detection is an area of active development aimed at enhancing driving safety and ensuring compliance with traffic regulations. Despite ongoing efforts, accidents and traffic violations continue to pose significant challenges, leading to disruptions in driving. In response to these issues, the author aims to develop a more efficient traffic management system to improve driver organization and driving behavior. To achieve this, the author proposes using YOLO-LIO as the neural network of choice for the Traffic System. The effectiveness of YOLO-LIO was evaluated using three datasets: the Montevideo Audio and Video dataset (MAVD), the GARM Road-Traffic Monitoring dataset (GRAM-RTM), and a custom dataset created by the author. The results highlight the superior performance of YOLO-LIO in vehicle detection tasks, achieving accuracy rates of 99.02% on the MAVD dataset, 99.55% on the GRAM-RTM dataset, and 99.32% on the custom dataset. This demonstrates the model's high effectiveness across various datasets. Additionally, the author conducted experiments incorporating OCR technology with the YOLO-LIO algorithm in the Traffic System. The system achieved an accuracy of 80.21% in vehicle number detection, demonstrating its effectiveness. This result reflects the overall performance of the entire system process, from data input to the final detection output, ensuring a comprehensive and accurate detection mechanism. Compared to other algorithms such as YOLOv3 + OCR, YOLOv4, and Faster R-CNN, YOLO-LIO + OCR, they have exhibited significantly better performance. These promising results highlight the potential of YOLO-LIO in creating a robust Traffic System that can significantly enhance road safety and traffic regulation compliance.
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