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Prediction for Surface Subsidence of Shield Construction in Water-Rich Sand Egg Stratum Based on Edge Intelligence 1

引用

3rd EAI International Conference on Edge Computing and IoT, EAI ICECI 2022

作者： Gao, Yanxia Liu, Yiwen Mi, Chunqiao Tang, Pengju Shi, Yuanquan School of Computer and Artificial Intelligence Huaihua University Huaihua418000 China Key Laboratory of Wuling-Mountain Health Big Data Intelligent Processing and Application in Hunan Province Universities Huaihua418000 China Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture in Hunan Province Huaihua418000 China

ISBN: (数字)9783031289903

ISBN: (纸本)9783031289897

The refinement and intelligent control of shield tunneling is the development trend of modern tunnel construction technology. In order to better predict and control the surface subsidence caused by shield excavation, this paper takes the shield construction of Luoyang Metro Line 2 from Longmen Station to Longmen Avenue Station as the background, and proposes a method based on edge intelligence for shield construction in water-rich sand egg strata. Methods for predicting land subsidence. First, low latency and faster data processing are achieved by collecting a large amount of data containing dynamic information about geological conditions and surrounding environments during the shield tunneling process;then using the iFogSim simulator to create different configurations;second, establishing support A surface subsidence model based on vector regression was established, and the model was deployed on the edge equipment;finally, the model was evaluated using the monitoring data of surface subsidence of the water-rich sand egg formation in Luoyang area. The research results show that the edge computing-based system has lower latency and higher processing speed than only deploying cloud data centers. After Pearson-related parameter tuning and model comparison training with Linear as the kernel function, the mean square error of the predicted value and the collected value of the surface subsidence is better than the other two kernel functions. The method proposed in this paper can provide real-time prediction service for large-scale surface subsidence prediction caused by shield construction, and is more practical. © 2023, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Soils

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Highly Accurate Dynamic Gesture Recognition Method Based on Edge Intelligence 1

引用

3rd EAI International Conference on Edge Computing and IoT, EAI ICECI 2022

作者： Changkai, Lu Yiwen, Liu Yanxia, Gao Yuanquan, Shi Xiaoning, Peng School of Computer and Artificial Intelligence Huaihua University Huaihua418000 China Key Laboratory of Wuling-Mountain Health Big Data Intelligent Processing and Application in Hunan Province Universities Huaihua418000 China Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture in Hunan Province Huaihua418000 China

ISBN: (数字)9783031289903

ISBN: (纸本)9783031289897

In recent years, gestures have been widely used in many fields. For example, human-computer interaction, virtual reality, gesture translation, etc. The reason for its rapid development is due to the emergence of deep learning and artificial intelligence under today’s society. Due to dynamic gestural interactions, such large intelligent models are often characterized by many parameters, large sample size, frequent parameter updates, and high communication volume. Based on this feature, we propose a cloud-based edge design architecture approach for gesture recognition based on an improved YOLOv5 network model optimization by changing different gestures, background interference, which uses a 21-layer model for the neural network. With the use of edge intelligence, the computational accuracy can be improved by 10.6% over the traditional YOLOv5 with a MAP value of 93.3%. The final recall rate is also improved by 3.6%. The parameter model is only 43.6% of the original one. This shows the practicality and operability of using edge computing as a technique in gesture recognition, as well as the small improvement cost and obvious effect. © 2023, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Gesture recognition

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Research on Highly Secure Metaverse Based on Extended Reality Under Edge Computing 16th

Research on Highly Secure Metaverse Based on Extended Realit...

引用

16th EAI International Conference on Wireless Internet, WiCON 2023

作者： Fu, Jinrong Liu, Yiwen Yan, Haobo Yang, Yahui Peng, Ling Shi, Yuanquan Feng, Tao School of Computer and Artificial Intelligence Huaihua University Huaihua418000 China Key Laboratory of Wuling-Mountain Health Big Data Intelligent Processing and Application in Hunan Province Universities Huaihua418000 China Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture in Hunan Province Huaihua418000 China School of Foreign Languages Huaihua University Huaihua418000 China

ISBN: (纸本)9783031580529

With the explosion of ChatGPT, the development of artificial intelligence technology ushered in another explosion. Similarly, with the rapid development of extended reality technology and Internet of Things technology, Metaverse will also usher in greater breakthroughs. However, in the development of the extended reality metaverse under edge computing, many security issues will arise. This paper focuses on data security, considering that data will be transmitted and processed between multiple devices and nodes instead of being concentrated in the cloud, which may bring To solve data security issues, relying on the integrated architecture of Metaverse educational applications based on edge computing (MEC), it provides an identity verification and access with higher security and scalability, better performance, and service requirements that meet the current environment control mechanism solutions, while analyzing other problems that will arise during the development of the extended reality metaverse. Aiming at the security problem on the edge side, a signature authentication scheme is designed based on Elliptic Curve Cryptography (ECC) integrated blockchain encryption technology and the effectiveness of the method is proved. In order to promote the extended reality metaverse under edge computing, it provides a mirror for the application in the field of education under the condition of ensuring data security. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2024.

关键词： Edge computing

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Edge Intelligence Based Garbage Classification Detection Method 1

引用

3rd EAI International Conference on Edge Computing and IoT, EAI ICECI 2022

作者： Zhu, Ruijia Liu, Yiwen Gao, Yanxia Shi, Yuanquan Peng, Xiaoning School of Computer and Artificial Intelligence Huaihua University Huaihua418000 China Key Laboratory of Wuling-Mountain Health Big Data Intelligent Processing and Application in Hunan Province Universities Huaihua418000 China Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture in Hunan Province Huaihua418000 China

ISBN: (数字)9783031289903

ISBN: (纸本)9783031289897

To address the problem that the classification and cleaning of garbage in city streets is always ineffective nowadays, the paper proposes a garbage detection method based on edge intelligence. The edge intelligence not only reduces the computational load of the cloud and speeds up the data transmission, but also greatly reduces the data transmission cost. First, images of city streets are collected and uploaded to the edge device via mobile devices in various locations in the city. Then, the edge server is used to temporarily store the image information, and the PeleeNet model deployed on it is used to identify and classify various kinds of garbage, and then visualize the information of each street. Finally, the street garbage information is transmitted to the cloud, which provides a detailed picture of the city’s garbage situation and facilitates city management. In this paper, the PeleeNet model is compared with ResNet, DenseNet and MobileNet models. The results show that the edge devices equipped with PeleeNet model not only have the fastest computation speed and the highest accuracy, but also occupy the least memory. It is fully demonstrated that the method studied in the paper can be applied to the problem of litter detection in urban streets. © 2023, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Smart city

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Exploration and Practice of Course Homework Metaverse Based on Extended Reality Under Edge Computing 1

引用

3rd EAI International Conference on Edge Computing and IoT, EAI ICECI 2022

作者： Fu, Jinrong Liu, Yiwen Yan, Haobo Gao, Yanxia Xiao, Jianhua School of Computer and Artificial Intelligence Huaihua University Huaihua418000 China Key Laboratory of Wuling-Mountain Health Big Data Intelligent Processing and Application in Hunan Province Universities Huaihua418000 China Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture in Hunan Province Huaihua418000 China

ISBN: (数字)9783031289903

ISBN: (纸本)9783031289897

The metaverse originated from science fiction at first, but it gradually came into reality with the continuous power of technology. Aiming at the problems of course work in Chinese universities, such as its function is weakened or suppressed, its form is too abstract, and it lacks elaborate design, this paper proposes a design method of course work meta-universe based on extended reality under edge computing. XR technology is used to realize the interactive immersion of the coursework meta-universe, in order to improve students’ learning enthusiasm and ability to solve abstract problems. Based on the international perspective, this paper systematically combs and analyzes the integration architecture, application scenarios and future trends of the meta-universe education application based on Edge computing (MEC). Four key processes are described: teacher-student interaction, data collection, data feedback and comprehensive evaluation. In order to promote the application of the metaverse in the field of education to provide mirror. The validity of the method is illustrated by the data. © 2023, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Edge computing

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intelligent Mobile Power Sharing and Rental System Based on BeiDou Navigation 2

Intelligent Mobile Power Sharing and Rental System Based on ...

引用

2nd International Conference on Electronic Information technology and Smart agriculture, ICEITSA 2022

作者： Hu, Hui Li, Xinhu Wu, Jiaxin Zeng, Qingli Zhang, Renmin College of Communication and Electronic Engineering Jishou University Hunan Jishou416000 China Hunan Provincial Key Lab. of Intelligent Control Technology for Ecological Agriculture in Wuling Mountain Area Huaihua University Hunan Huaihua418000 China

ISBN: (纸本)9781665464017

Aiming at the problems that the mobile power supply in the market cannot output AC voltage and manually adjustable DC voltage at the same time, expensive and cannot be accurately located, an intelligent mobile power sharing and rental system based on BeiDou navigation is designed. The device mainly consists of three major parts: power circuit module, controller module and mobile APP, which solves a series of problems such as location finding, rental use, visual power management and positioning return of shared power by users. The power circuit module converts the battery voltage into 220V AC output and adjustable DC precision output. The controller module realizes the functions of power supply DC output voltage collection, Battery power Detection, Beidou positioning and data uploading to the server. The mobile APP realizes the functions such as displaying the location, voltage, power and other data of multiple power supply units and sharing the rental under the shared rental mode by the APP. The system realized in this paper can greatly promote the development of China's shared energy storage industry and effectively change the current dilemma that people have difficulties in using electricity outdoors. © 2022 IEEE.

关键词： Digital storage

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Design of a Crop Disease and Pest Identification System Based on Deep Learning 3

Design of a Crop Disease and Pest Identification System Base...

引用

3rd International Conference on Electronic Informationtechnology and Smart agriculture, ICEITSA 2023

作者： Zhou, Chengling Zhou, Lingfang Liu, Siyi Deng, Wen Xiao, Jing Hang, Shiyang Zhang, Shunru School of Physics Electronics and Intelligent Manufacturing Huaihua University Hunan Huaihua China Key Lab. of Intelligent Contr. Technol. for Wuling-Mountain Ecological Agriculture in Hunan Province Huaihua University Hunan Huaihua China Huaihua Key Laboratory of Agricultural Ecology Prevention and Control Huaihua University Hunan Huaihua China

ISBN: (纸本)9798400716775

Traditional conventional methods for identifying pests and diseases often rely depended on manual experience, making it difficult to ensure accuracy and low efficiency. Deep learning technology Learning technology deeply can automatically extract useful features from a large amount of image data, classify and recognize them, and improve enhance accuracy and efficiency This approach can help assist farmers detect pests and diseases in a timely manner, thus taking timely prevention and control measures to reduce the spread and loss of pests and diseases taking immediate steps to minimize its diffusion and loss as much as possible. This article in this paper, designs a deep learning based crop pest identification system designing a crop pest and disease recognition system which is based on deep learning, aiming to improve the accuracy and efficiency of crop pest identification. The system uses utilizes three classic convolutional neural networks (CNNs) as training models to achieve recognition of various common crop pest pests and disease types. After system testing and analysis, the results show demonstrate that the system has significant advantages in accuracy, real-time performance, and can meet fulfil practical application requirements. Future research directions Future studies can further optimize models, expand datasets, reduce false fake positives, and provide more accurate and efficient pest identification support for agricultural production. © 2023 ACM.

关键词： Convolutional neural networks

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Data-driven risk assessment and early warning of learning situations 4

Data-driven risk assessment and early warning of learning si...

引用

4th International Conference on Computer Science and Educational Informatization, CSEI 2022

作者： Mi, Chunqiao Deng, Qingyou Zhao, Changhua Huaihua University Hunan Huaihua China Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture in Hunan Province Hunan Huaihua China Key Laboratory of Wuling-Mountain Health Big Data Intelligent Processing and Application in Hunan Province Universities Hunan Huaihua China

ISBN: (数字)9781839537882

ISBN: (纸本)9781839537882

At present, quality governance has become the internal demand of education reform and high-quality education system construction. First, this study analyzed the current research status and existing problems of early warning education in universities and colleges from the aspects of basic data, evaluation index, assessment method, and tool system application. Second, driven by learning situation big data analysis, this study puts forward a complete method system of risk assessment and early warning of learning situations, which consists of basic data collection and processing, index system construction and quantification, model construction and calculation, result expression and visualization, and a prototype information system was also realized by using modern software engineering and visualization technology. Finally, a specific course was taken as an example, and the application practice of learning situation risk assessment and early warning was carried out. The obtained results are very helpful to solve the problems of lagging early warning time, single evaluation factor, outdated technology and so on in traditional early warning education. It has reference significance for improving students' learning quality, teachers' teaching effect and early warning education management efficiency. © 2022 IET Conference Proceedings. All rights reserved.

关键词： Risk assessment

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An Effective and Real-time Time-Slot Power Detection Method 3

An Effective and Real-time Time-Slot Power Detection Method

引用

3rd International Conference on Electronic Informationtechnology and Smart agriculture, ICEITSA 2023

作者： Zhang, Xian Luo, Xinhui Qu, Taiguo Yin, Dong Huaihua University Hunan Huaihua418000 China Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture in Hunan Province Huaihua University Huaihua418000 China Key Laboratory of Wuling-Mountain Health Big Data Intelligent Processing and Application in Hunan Province Universities Huaihua University Hunan Huaihua418000 China Department of Art Design Huaihua Tourism School Hunan Huaihua418000 China

ISBN: (纸本)9798400716775

To efficiently detect the time-slot power of the Time Division Multiple Access (TDMA) communication systems such as repeaters and base stations in real-time. This article designs a signal-sampling hardware circuit based on the Advanced RISC Machine (ARM) platform and proposes a comprehensive method to calculate the time-slot power values. The signal sampling circuit uses the ADC108S052 chip with an 8-channel linked to the ARM via the Serial Peripheral Interface (SPI), and the time-slot power detection approach consists of a signal timing sampling module, sampling data reading module, and sampling data processing module to compute the detected time-slot power comprehensively. We design experiments to evaluate the efficacy of the approach to detect the time-slot power with the system power-on and normality running condition, the detection of the system CPU resource consumption for the time-slot power, the detection of the error value for the time-slot power, etc. The experimental results demonstrate that the approach can be efficient, and real-time detection of the time-slot power of the TDMA system, the system of repeaters and base stations and other systems of signal coverage, optimization and so on is of great significance. © 2023 ACM.

关键词： Signal sampling

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Fault Analysis of Bearings in Various States Based on Continuous Wavelet and Improved Residual Network 2

Fault Analysis of Bearings in Various States Based on Contin...

引用

2nd International Conference on Electronic Information technology and Smart agriculture, ICEITSA 2022

作者： Wang, Qingnan Tu, Jihui School of Intelligent Manufacturing Huaihua University China Key Lab. of Intelligent Control Technology for Wuling Mountain Ecological Agriculture Hunan Province Huaihua China School of Electronic and Information Yangtze University Jingzhou China

ISBN: (纸本)9781665464017

The bearing fault signals are complex and difficult to collect, which leads to a limited number of fault samples, and it is difficult to analyze the changeable bearing faults with conventional methods. In this paper, an automatic signal feature extraction method by improved residual network and wavelet transform is presented, which is suitable for bearing fault analysis in various states. Continuous wavelet transform (CWT) can obtain enough time-frequency images by superposing the original vibration signals. Improve the residual network, increase the attention mechanism and better deal with complex features. Transfer learning is applied to various working states, and the common features of bearing faults concealment are extracted and learned, so as to improve the applicability of diagnosis. The prediction ability of the bearing is tested in various working states, which proves the applicability of our fault analysis method. The problem of low accuracy of small sample identification caused by lack of actual fault data is solved. © 2022 IEEE.

关键词： Wavelet transforms

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