This research study describes a novel way to secure the smart grid system by utilizing cryptographic and Artificial Intelligence (AI) methods. This research study intends to safeguard the grid from cyber-attacks and m...
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With the rapid development of the industrial sector, the application scenarios of distortion analyzers have also become more extensive. However, most distortion analyzers currently available on the market still have s...
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Parallel processing involves challenges on data dependency. In this work, we presented an investigation of performance into image background removal using the Rembg algorithms incorporating parallel computing techniqu...
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Federated learning (FL) has grown in popularity among universities and industrial businesses in processing and analyzing large amounts of data from IoT devices. Maintaining FL efficiency by preserving the privacy of I...
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In response to the demand for real-time performance and control quality in industrial internet of Things (IoT) environments, this paper proposes an optimization control system based on deep reinforcement learning and ...
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ISBN:
(纸本)9798350366105;9798350366099
In response to the demand for real-time performance and control quality in industrial internet of Things (IoT) environments, this paper proposes an optimization control system based on deep reinforcement learning and edge computing. The system leverages cloud-edge collaboration, deploys lightweight policy networks at the edge, predicts system states, and outputs controls at a high frequency, enabling monitoring and optimization of industrial objectives. Additionally, a dynamic resource allocation mechanism is designed to ensure rational scheduling of edge computing resources, achieving global optimization. Results demonstrate that this approach reduces cloud-edge communication latency, accelerates response to abnormal situations, reduces system failure rates, extends average equipment operating time, and saves costs for manual maintenance and replacement. This ensures real-time and stable control.
With the rapid development of virtual reality and augmented reality technologies, real-time 3D human pose estimation plays a key role in various interactive applications. This paper proposes a real-time 3D human pose ...
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The proliferation of edge computing has significantly reduced latency and improved network responsiveness, but its full potential remains unrealized due to challenges in managing the dynamic migration of mobile statio...
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In recent years, with the rapid development of technology, the level of informatization of power systems based on cloud computing has also been continuously improving. More and more data has been accumulated in variou...
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In response to the problems of poor trajectory matching accuracy, high matching cost, limited map accuracy, and inability to handle large-scale trajectory data in current traditional map matching methods, this paper c...
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With the development of the internet of Things, the number of devices connected to the internet has increased exponentially, leading to a huge increase in the amount of data to be processed in the cloud, with a signif...
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