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检索条件"机构=Beijing Engineering Research Center for LoT Software and Systems"

共 230 条记录，以下是1-10 订阅

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Improved YOLOv8 for Complex Environmental Fish Detection 7

Improved YOLOv8 for Complex Environmental Fish Detection

引用

7th IEEE Advanced Information Technology, Electronic and Automation Control Conference, IAEAC 2024

作者： Cheng, Tonglin Li, Juan Luo, Jintao Li, Zhihui Beijing University of Technology Faculty of Information Technology China Beijing Engineering Research Center for LoT Software and Systems China

ISBN: (纸本)9798350339161

With the rapid development of computer vision and deep learning technologies, object detection plays a crucial role in various fields. Due to the complexity and diversity of underwater environments, underwater vision tasks face great challenges. In this paper, we improved the YOLOv8 detection model for the fish detection task in complex environments. Specifically, we proposed a multi-scale feature fusion method (MFANet) that combines multiscale weighted feature fusion with multiscale attention to efficiently capture multilevel features of fishes in complex environments. We designed a multiscale weighted feature fusion module that combines feature maps at different scales to enhance the model's representation of the target. By introducing a multi-scale attention mechanism, the model is able to pay more attention to important feature regions. We conducted experiments on real underwater complex environment datasets. The results show that our proposed improved method significantly enhances the performance of the YOLOv8 model in fish detection tasks and lays a good foundation for subsequent underwater detection tasks. © 2024 IEEE.

关键词： Fish

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MQTT Subscription Tree Optimization and Performance Analysis 7

MQTT Subscription Tree Optimization and Performance Analysis

引用

7th IEEE Advanced Information Technology, Electronic and Automation Control Conference, IAEAC 2024

作者： Li, Aodong Beijing University of Technology Beijing Engineering Research Center for IoT Software and Systems Beijing China

ISBN: (纸本)9798350339161

With the continuous development of the Internet of Things (IoT) technology, the large number of messages generated by the increasing number of IoT devices has brought new challenges to MQTT servers. Due to the need for timely forwarding of MQTT messages, the latency of message reception and forwarding will also increase when there are too many clients connected to the server and message publishing and subscription activities are too frequent. In response to this issue, this paper proposes an MQTT subscription tree optimization method that combines hash tables and trie trees. Then, this method is used to implement the subscription tree module of a simple MQTT server, and its performance is compared and analyzed with several other subscription tree implementation methods. The final experimental results show that when a large number of clients connect to the server and frequently publish messages or subscribe to topics, the method proposed in this paper can reduce message forwarding latency, achieve fast message routing, and improve the efficiency of server message forwarding. © 2024 IEEE.

关键词： Data structures

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Joint data augmentation and attention mechanism for occluded human pose estimation 7

Joint data augmentation and attention mechanism for occluded...

引用

7th IEEE Advanced Information Technology, Electronic and Automation Control Conference, IAEAC 2024

作者： Pan, Xuelun Li, Da Huang, Zhangqin Yang, Huapeng Beijing University of Technology Beijing Engineering Research Center for IoT Software and Systems Beijing China

ISBN: (纸本)9798350339161

Human pose estimation technology has important applications in many fields. Existing research mainly focuses on precise localization of human key points in unobstructed situations but neglects the common occlusion problem in daily environments. Occlusion can disrupt the correlation between key points in the human body, causing a decrease in model accuracy. In response to the above issues, this article proposes a joint data augmentation and attention mechanism for occluded human pose estimation. This article focuses on training human key points in images, generating a specific number and size of occluded areas to simulate scenarios where human key points are occluded. To further enhance the model's ability to extract feature information, this method considers the global context of feature and integrates the GC Block attention mechanism into the human pose network structure, enabling the network to focus on the human body regions in the image. This method has been experimentally validated on the OCHuman dataset, and the results show that it can effectively improve the accuracy of joint localization in human pose estimation. © 2024 IEEE.

关键词： Image enhancement

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Energy-efficient and Latency-optimal Task Offloading Strategies for Multi-user in Edge Computing 7

Energy-efficient and Latency-optimal Task Offloading Strateg...

引用

7th IEEE Advanced Information Technology, Electronic and Automation Control Conference, IAEAC 2024

作者： Zhang, Xiaobo Huang, Zhangqin Yang, Huapeng Huang, Ling Beijing University of Technology Beijing Engineering Research Center for IoT Software and Systems Beijing China

ISBN: (纸本)9798350339161

Compute-intensive and latency-sensitive applications place stringent demands on mobile devices in terms of computational power and task latency. Edge computing is a promising technique to alleviate the computational constraints of mobile terminals and reduce their energy consumption through computation offloading. This paper proposes a two-tier task offloading framework for multi-user multi-server edge IoT scenarios, comprehensively considering factors such as task offloading decision, network channel allocation, edge server computational resources, device transmission power, and the size of the task offloading data volume, and constructing a multi-user task offloading Optimization problem model. In the process of solving the optimization problem, a Combining GA and PSO Computation offloading Algorithm (CGPCA) is proposed for solving the model. Finally, the convergence of the algorithm is verified through simulation experiments, and the experimental results show that the proposed algorithm in this study can effectively reduce the task offloading delay and energy consumption, and improve the quality of end-user service compared with other existing algorithms. © 2024 IEEE.

关键词： Energy utilization

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research on intelligent roadside parking system based on multi-dimensional feature visualization technology 7

Research on intelligent roadside parking system based on mul...

引用

7th IEEE Advanced Information Technology, Electronic and Automation Control Conference, IAEAC 2024

作者： Ju, Min Zhang, Xiaobo Huang, Zhangqin Beijing University of Technology Beijing Engineering Research Center for IoT Software and Systems Beijing China

ISBN: (纸本)9798350339161

With the rapid advancement of urban modernization and the sustainable development of economy, the problems of driving difficulty and parking difficulty are increasingly prominent in large, medium and small cities. In order to alleviate the contradiction between urban space and vehicle growth rate and improve the utilization efficiency of parking resources, based on the roadside parking data of Nanshan District in Shenzhen City, this paper combines the time series data visualization method and geospatial data visualization method in multi-dimensional data visualization, and adopts the mode of view collaborative interaction to design the intelligent roadside parking collaborative interactive visualization system. The system integrates multisource data, displays roadside parking data information in an all-round way, supports exploratory analysis of roadside parking data characteristics and laws, and helps to understand parking demand and parking distribution at different times and regions. It provides decision support for optimizing parking resource allocation and roadside parking management. © 2024 IEEE.

关键词： Data visualization

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Facial expression recognition method based on dual-branch fusion network with noisy labels 7

Facial expression recognition method based on dual-branch fu...

引用

7th IEEE Advanced Information Technology, Electronic and Automation Control Conference, IAEAC 2024

作者： Lv, Zhenhuai Beijing University of Technology Beijing Engineering Research Center for IoT Software and Systems Beijing China

ISBN: (纸本)9798350339161

As an important problem in the field of computer vision, facial expression recognition has been widely used in many fields such as human-computer interaction and emotion recognition. This paper proposes a dual-branch parallel facial expression recognition network that integrates Convolutional Neural Network (CNN) and Transformer. By consolidating local and global information obtained from the dual branches, the network effectively combines subtle local variations and overall contextual features of facial expressions. The fused feature representation demonstrates enhanced representativeness and discriminative power, leading to a notable improvement in facial expression recognition accuracy. In addressing the challenges posed by inter-class similarity and annotation ambiguity, the Erasing Attention Consistency (EAC) mechanism is employed. This mechanism effectively prevents the model from memorizing noisy samples, thereby enhancing robustness against noisy labels. Additionally, the focal loss function is utilized to rectify imbalances within data samples. Experiments conducted on RAF-DB datasets with labels containing noise reveal that the proposed methodology achieves accuracies of 87.65% and 86.05% at 10% and 20% noise rate, respectively. This substantiates the effectiveness of the proposed approach. © 2024 IEEE.

关键词： Emotion Recognition

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Edge Computing-enabled Network Architecture Design for Space-Air-Ground Integrated Network 7

Edge Computing-enabled Network Architecture Design for Space...

引用

7th IEEE Advanced Information Technology, Electronic and Automation Control Conference, IAEAC 2024

作者： Zhang, Xiaobo Huang, Zhangqin Huang, Ling Yang, Huapeng Beijing University of Technology Beijing Engineering Research Center for IoT Software and Systems Beijing China

ISBN: (纸本)9798350339161

The space-air-ground integrated network (SAGIN) has become important research content for the next generation of 6G communication networks. Considering the difficulties in network resource management, complex network service configuration, network collaboration and security sharing pressure in network construction. A novel edge computing-enabled network architecture is proposed. On this basis, key technologies such as software defined network (SDN), network slicing and blockchain are used to solve the difficulties in network system construction. Then, the proposed architecture is designed and described in detail. Furthermore, the key technical challenges in the practical application and implementation of the proposed architecture are further explored, providing a fundamental reference for further in-depth research. Finally, simulation experiments verify that the proposed architecture achieves significant improvements in terminal devices' task processing energy consumption and latency compared to network architecture with other studies. © 2024 IEEE.

关键词： Blockchain

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Multilayer Perceptron (MLP)-based Path Loss Prediction Modeling for LoRa Signals 4

Multilayer Perceptron (MLP)-based Path Loss Prediction Model...

引用

4th International Conference on Artificial Intelligence, Robotics, and Communication, ICAIRC 2024

作者： Jiang, Fan Huang, Zhangqin Huang, Ling Yan, Huangyi Beijing University of Technology Beijing Engineering Research Center for IoT Software and Systems Beijing China

ISBN: (纸本)9798331531225

With the rapid development of Internet of Things (IoT) technology, Low Power Wide Area Network (LPWAN) has become a key enabler for connecting large-scale devices. LoRa technology plays a pivotal role in IoT due to its excellent anti-interference ability and long-range transmission capabilities. However, environmental factors, terrain, and building occlusion significantly impact the propagation and loss of path of LoRa signals, which in turn affect network coverage and communication quality. Therefore, accurately predicting the path loss of LoRa signals is crucial for effective network optimization and troubleshooting. In this study, we propose a path loss prediction model based on a multilayer perceptron (MLP), integrating the Okumura model path loss as a reference feature and comparing it with traditional empirical models. The experimental results demonstrate that the MLP model effectively learns complex nonlinear relationships, improving the accuracy of prediction. Through 10-fold cross-validation and testing various neuron configurations, it is found that the MLP model with 20 neurons (MLP20) performs best, yielding the lowest root mean square error (RMSE). Compared to the traditional Okumura Hata model, the MLP model shows significant advantages in prediction accuracy and stability. This study not only takes advantage of the theoretical strengths of the Okumura model but also enhances the adaptability to complex environmental factors through MLP, providing a new solution for LoRa network optimization. © 2024 IEEE.

关键词： Mean square error

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Multidimensional data processing and estimation algorithm for pipeline settlement measurement 4

Multidimensional data processing and estimation algorithm fo...

引用

4th International Conference on Artificial Intelligence, Robotics, and Communication, ICAIRC 2024

作者： Zhang, Xialu Huang, Zhangqin Beijing University of Technology Beijing Engineering Research Center for IoT Software and Systems Beijing China

ISBN: (纸本)9798331531225

With the rapid development of our country's economy, the density of urban pipe network has increased continuously. These pipeline lines operate in the environment of long transportation distance, large span and complex geological conditions. Due to the complexity of the environment, they are easily affected by geological disasters, and the settlement or even damage of pipelines may lead to direct and indirect secondary disasters, which will bring great impact on society and economy. The application of RFID based IoT sensing system in underground pipeline management realizes real-time monitoring of pipeline settlement displacement by burying devices carrying RFID tags underground, preventing economic losses and social disasters. Combined with BeiDou positioning technology, the system provides high-precision positioning and deformation monitoring, making positive contributions to the safe operation of urban infrastructure. The technology is expected to become an important tool for underground pipeline management and promote social stability and sustainable development. © 2024 IEEE.

关键词： Urban transportation

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Resource Allocation Strategies for Cloud-Edge-End Collaboration in Heterogeneous Edge Computing 7

Resource Allocation Strategies for Cloud-Edge-End Collaborat...

引用

7th World Conference on Computing and Communication Technologies, WCCCT 2024

作者： Zhang, Xiaobo Huang, Zhangqin Huang, Ling Yang, Huapeng Beijing University of Technology Beijing Engineering Research Center for IoT Software and Systems Beijing China

ISBN: (纸本)9798350372328

With the continuous innovation of information technology, the Internet of Everything (IoE) is gradually being realized, and more IoT application scenarios have increasingly urgent requirements for high-performance computing and low-latency response. To address the bottleneck of insufficient computing power and energy constraints of terminal devices, edge computing can effectively enhance the task processing capability of terminal devices and improve service quality. However, existing edge computing network architectures, which often provide a single edge server computing capability based on terrestrial networks, cannot meet the task offloading requirements of terminal devices in ubiquitous network environments. This paper designs a cloud-edge-end collaboration space-air-ground integration multi-layer edge computing network architecture (CEEC-SAGIN), and based on this architecture, a heterogeneous network system of terminal devices, multi-layer edge computing services and cloud computing services are constructed. Then, a task processing model is constructed with the optimization objective of minimizing the task processing delay of the system, taking into account the task offloading ratio, computational resources and transmission resources involved in the task processing process of the terminal devices of the system. Further, a multi-layer task offloading and resource allocation algorithm (MTORA) is proposed to realize the optimal allocation of resources in system task processing. Finally, simulation experiments show that the CEEC-AGIN architecture proposed in this paper can meet the requirements of more applications, and the proposed model can improve the system task processing efficiency by up to roughly 15% and reduce the system task processing latency by up to approximately 10% compared with other resource allocation strategies. © 2024 IEEE.

关键词： Resource allocation

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