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检索条件"任意字段=IEEE International Conference on Embedded and Real-Time Computing Systems and Applications"

共 36970 条记录，以下是971-980 订阅

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Efficient Human Pose Recognition Using Improved OpenPose Algorithm on embedded systems with RK3399 10

Efficient Human Pose Recognition Using Improved OpenPose Alg...

引用

10th international conference on systems and Informatics, ICSAI 2024

作者： Li, Jiasi Liu, Lei College of Computer Science and Technology Xinjiang University Xinjiang China

ISBN: (纸本)9798331510138

In order to address the limitations of traditional human pose recognition methods due to algorithms and hardware devices, which cannot meet the requirements of real-time and accuracy, a human pose recognition system based on convolutional neural networks was designed and implemented using the RK3399 chip to improve recognition accuracy and real-time performance. Adopting a deep convolutional neural network structure, including multiple convolutional layers, pooling layers, and fully connected layers, for feature extraction and classification. Through a large dataset and training, the model is able to accurately recognize human postures at different angles, lighting conditions, and backgrounds. The experimental results show that the method has high accuracy and robustness in human posture recognition, and can be applied to human-computer interaction, motion capture and other fields. The convolutional neural network human posture recognition method based on RK3399 proposed in this paper provides a new solution for the application of embedded systems in the field of human posture *** this leads to a decrease in recognition accuracy, improving OpenPose greatly reduces the amount of computation, greatly reduces the burden on the graphics card, and also reduces the waiting time for computation and improves the timeliness of detection. © 2024 ieee.

关键词： Convolutional neural networks

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Empowering Urban Illumination: Intelligent Street Lighting Android, Firebase, LoRa Wan and Control Card 2

Empowering Urban Illumination: Intelligent Street Lighting A...

引用

2nd ieee international conference on IoT, Communication and Automation Technology, ICICAT 2024

作者： Pandey, Abhishek Pandey, Ankit Pal, Abhinav Pandey, Prashant Katiyar, Himanshu Tripathi, Ravi Prakash Rajkiya Engineering College Department of Electronics Engineering Sonbhadra231206 India Rajkiya Engineering College Department of Civil Engineering Sonbhadra231206 India

ISBN: (纸本)9798350368109

In cities, managing street lighting efficiently is vital for enlightening safety, cutting down on energy use, and enhancing resource distribution. This project offers a complete solution that uses modern technology, including Android apps, Firebase for real-time data sharing, and control cards for connecting to physical systems. The goal of this paper is to create an easy-to-use and flexible street lighting control system that enables city officials or allocated staff to manage and monitor street lights from a distance using an Android app. The system pursues to solve common issues in traditional street lighting management, like slow fault response, poor energy efficiency, and limited monitoring options. By using Firebase, a real-time database, the system allows continuous communication between the Android app and the street lighting setup. Firebase provides rapid updates and data management, allowing for fast responses to user commands and real-time tracking of street light conditions. Control cards help as the link between the digital control system and the street lighting hardware, featuring embedded controllers that can understand commands from the Android app and relay them to the suitable street lights. © 2024 ieee.

关键词： Digital control systems

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Design and Implementation of an Automated pH Control System for Bioreactor with Integrated Water Management

Design and Implementation of an Automated pH Control System ...

引用

2024 ieee international Multi-conference on Smart systems and Green Process, IMC-SSGP 2024

作者： Othmen, Marwa Gasmi, Aicha Ibrahimi, Soumaya Hannachi, Ahmed National School of Engineers of Gabes Research Laboratory of Process Engineering and Industrial Systems Gabes6029 Tunisia

ISBN: (纸本)9798350378382

The maintenance of optimal pH levels is critical for the efficient operation of bioreactors, particularly in processes involving microbial activity, such as wastewater treatment, with applications extending to pharmaceuticals, biotechnology, and bioenergy production. This paper presents the design and implementation of a low-cost, high-precision bioreactor system capable of real-time pH regulation and automated wastewater management. The bioreactor is equipped with integrated pH sensors and a microcontroller to continuously monitor and adjust pH levels through the precise addition of acidic or basic solutions. Additionally, the system includes an immersed temperature sensor for real-time temperature monitoring, ensuring stable operating conditions. In addition to that, the bioreactor is occupied with a solenoid valve-based wastewater management system, which regulates the inflow and outflow of liquids based on a pre-set schedule. Experimental results demonstrate that the bioreactor provides reliable pH stabilization with minimal fluctuations and efficiently manages wastewater, ensuring a stable operating condition of bioreactor. Automatic control of bioprocess leads to minimize human intervention and therefore reduce the operational cost and human error. This work highlights the feasibility of integrating precision and automation into bioprocess technologies, paving the way for more accessible and efficient bioreactor systems for a large scale applications. © 2024 ieee.

关键词： Solenoid valves

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Task-level Thermal Modeling for Temperature Management of Edge TPU

Task-level Thermal Modeling for Temperature Management of Ed...

引用

ieee international conference on embedded and real-time computing systems and applications (RTCSA)

作者： Changhun Han Sangeun Oh Ajou University

ISBN: (数字)9798350387957

ISBN: (纸本)9798350387964

Edge TPU (Tensor Processing Unit) is being widely utilized in various edge computing applications as a high-efficiency, low-power accelerator for deep learning computations. However, temperature rise in Edge TPU can lead to performance degradation, reduced stability, and shortened lifespan, necessitating temperature management through thermal modeling. This paper proposes a task-level thermal modeling technique for predicting Edge TPU temperature. The proposed method estimates power consumption of CPU and Edge TPU based on workloads of various deep learning tasks and predicts the convergence temperature of Edge TPU using a steady temperature model. Through experiments, we confirmed that the proposed method accurately predicts Edge TPU temperature for various workloads. The average prediction error was 0.7°C. This study is expected to serve as a foundation for developing temperature management techniques by presenting an effective temperature prediction model that considers the thermal characteristics of Edge TPU.

关键词： Deep learning Temperature Tensors Computational modeling Predictive models Thermal management Stability analysis real-time systems Thermal stability Thermal degradation

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Graph Based Analysis Technique for Identification of Key Functionalities in Malicious IoT Binaries 6

Graph Based Analysis Technique for Identification of Key Fun...

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6th ieee international conference on Emerging Smart computing and Informatics, ESCI 2024

作者： Patil, Mahesh U. Patil, Shailaja C. Wagaj, Santosh C. JSPM's Rajarshi Shahu College of Engineering Dept. of Electronics and Telecommunication Pune India

ISBN: (纸本)9798350306613

The paradigm of embedded systems being connected to internet have led to the evolution of Internet of Things (IoT). Considering that these devices are connected to home, enterprises, government and critical infrastructure, it has become prime target for the adversaries. Hence malwares on these IoT devices are now being witnessed. Analysis of these malware has become the need of the hour and requires special skills including reverse engineering. Hybrid approaches which include static and dynamic analysis have become popular even for IoT devices. For dynamic analysis to be successful prior static analysis is crucial. This paper highlights a technique of analyzing malicious binaries based on Graph theory. The proposed methodology extracts function call graph and derives the centrality metrics for analysis. To validate the technique, the results are compared across 6 variants of the popular real-world Gafgyt malware samples found in IoT devices including routers. The malware variants are chosen across two architectures i.e. ARM and x86 to demonstrate that the technique is agnostic of the architecture. The results depict that core functionalities of the malware can be traced using the degree and in-degree centrality metrics of graph. Further it was observed that with the proposed methodology, functions as less as 5 % are sufficient to derive core behavioral patterns of the malware. © 2024 ieee.

关键词： binary analysis embedded systems graphs Internet of Things (IoT) malicious behavior malware

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A real-time Spacecraft Health Monitoring embedded Software Based on Three Services of PUS 4th

A Real-Time Spacecraft Health Monitoring Embedded Software B...

引用

4th international conference on Decision Science and Management (ICDSM)

作者： Liu, Xin Han, Lu Zhu, Jian-Bing Wei, Yong-Quan Beijing Inst Spacecraft Syst Engn Beijing 100096 Peoples R China

ISBN: (纸本)9789811927683;9789811927676

To solve the problem of traditional way of large spacecraft health state monitoring with high fake alarm rate and slow anomaly response time, this paper analyzes the disadvantages of traditional way of health monitoring firstly and then researches the services correlated to on -board real-time health monitoring in PUS. Based on the researches, an on -board health monitoring embedded software is designed. The software utilizes real-time telemetry data and the monitoring rules saved in the spacecraft to judge the on -board health state of the spacecraft. When the state violates the monitoring rules, an event report will be sent back to the ground automatically and, in turn, a process of coping with the anomaly will be activated automatically. The software has been applied in China Space Station and an agile platform of remote sensing spacecraft, and it sharply improves reliability of the spacecraft when executing mission and reduces the cost of health monitor on the ground.

关键词： Spacecraft health monitoring real-time embedded software Event action Check rule State machine

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Processor and Bus Co-scheduling Strategies for real-time Tasks with Multiple Service-levels 27

Processor and Bus Co-scheduling Strategies for Real-time Tas...

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27th ieee international conference on embedded and real-time computing systems and applications (RTCSA)

作者： Roy, Sanjit Kumar Sarkar, Amab Gangopadhyay, Rahul IIT Guwahati Dept CSE Gauhati Assam India IIT Kharagpur ATDC Kharagpur W Bengal India St Petersburg State Univ Dept Math & Comp Sci St Petersburg Russia

ISBN: (纸本)9781665441889

Cyber-Physical systems, including those in the automotive domain, are often designed by assigning to each task an appropriate criticality-based reward value which is acquired by the system on its successful execution. Additionally, each task may have multiple implementations designated as service-levels, with higher service-levels producing more accurate results and contributing to higher rewards for the system. This work proposes strategies for co-scheduling a set of periodic tasks with multiple service-levels, on homogeneous processors and system buses. The problem is modeled as a Multi-dimensional Multiple-Choice Knapsack formulation (MMCKP) with the objective of maximizing overall system level rewards. A Dynamic Programming (DP) solution is proposed to solve the MMCKP. It was observed that although the DP based solution produces optimal results, its complexity is highly sensitive to the number of tasks, processors, buses as well as to the number of task service-levels, which severely restricts scalability of the strategy. Therefore, we have also proposed a fast yet efficient heuristic algorithm called Accurate Low Overhead Level Allocator (ALOLA), which attempts to achieve the same objective. Our simulation based experimental evaluation shows that even on moderately large systems consisting of 90 tasks with 5 service-levels each, 16 processors and 4 buses, while MMCKP incurs a run-time of more than 1 hour 20 minutes and approximately 68 GB main memory, ALOLA takes only about 196 mu s (speedup of the order of 10(6) times) and less than 1 MB of memory. Moreover, while being fast, ALOLA is also efficient being able to control performance degradations to at most 13% compared to the optimal results produced by MMCKP. We use an automated flight control system employed in modern avionic systems, a real-world application to illustrate the general applicability of our proposed scheme.

关键词： real-time Processor Scheduling real-time Bus Scheduling Optimal Service-level Selection Cyber-Physical systems Automotive systems Scheduling

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Enhancing Cryptographic Security in RTOS: Addressing Vulnerabilities in embedded systems 10

Enhancing Cryptographic Security in RTOS: Addressing Vulnera...

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10th international conference on Engineering and Emerging Technologies, ICEET 2024

作者： Fteiha, Bara' Ai-Rifa'i, Hadeel Ajmal, Zaina Jaffarsadiq, Manal Zia, Huma College of Engineering Abu Dhabi University Abu Dhabi United Arab Emirates

ISBN: (纸本)9798331532895

This paper systematically reviews the cryptographic methods utilized in embedded systems real-time Operating systems (RTOS), highlighting significant threats that must be addressed immediately. This urgency is raised due to these methodologies' effective aid in the preservation of confidential information, protecting the system, and providing an offense against external attacks. This study presents an overview of the existing security protocols dedicated to RTOS with regard to its historical developments and evaluates the use of methods and systems of proper cryptography. As a result of the systematic understanding of the core problems, common vulnerabilities are revealed and new approaches to strengthening these systems are put forward. Structural and functional characteristics of the proposed solutions are tested under the implementation of the RTOS security, covering plausible defense mechanisms in light of the increase in computer-based attacks. This paper paves the way for future research endeavors to fill in the gaps by proposing or implementing dynamic security strategies. © 2024 ieee.

关键词： embedded systems

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Adaptive Federated Learning for Efficient Network Traffic Management in Edge computing 4

Adaptive Federated Learning for Efficient Network Traffic Ma...

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4th international conference on Ubiquitous computing and Intelligent Information systems, ICUIS 2024

作者： Babu, Kuricheti Suresh Venkatasubramanian, S. Kishore, S. Sree, K. Kavya Ramya Susanna, Ch.Lavanya Rao, Goda Srinivasa Lakkshmanan, Ajanthaa Pace Institute of Technology and Sciences Department of Computer Science and Engineering AndhraPradesh Valluru India Saranathan college of engineering Department of Computer Science and Business Systems Trichy India B V Raju Institute Of Technology Department of Csbs Narsapur Telangana Medak502313 India Aditya University Department of Ai&ml Surampalem India Koneru Lakshmaiah Education Foundation Department of Computer Science and Engineering Andhra Pradesh Vaddeswaram India Kl University Department of Cse Vaddeswaram Andhra Pradesh Guntur India School of Computing Srm Institute of Science and Technology Department of Computing Technologies Kattankulathur Campus Kattankulathur603 203 India

ISBN: (纸本)9798331529635

With the increasing prevalence of edge computing environment, there is a need to establish effective network traffic management that are able to manage vast data while also protecting the privacy of users. The proposed method enhances efficiency of bandwidth, reduce the network latency and manages computational demands without managing data privacy. This is achieved by utilizing the design of edge devices. The adaptable nature of the method enables it to react in real time to different traffic situations. It optimizes the distribution of resources and improves the overall performance of the network. Additionally, it can reduce the possibility of centralized data exposure, providing robust privacy preservation through the allowance of local model training on edge devices. Finally, this method is superior. The employment of federated learning to network traffic management provide efficiency to optimize the traffic in edge computing which is both scalable and safe. This makes it suitable for a wide variety of applications that are utilized in next generation networks © 2024 ieee.

关键词： Federated learning

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Neural Network Characteristics-aware Proactive Boost for Heterogeneous computing to Improve Energy Efficiency 29

Neural Network Characteristics-aware Proactive Boost for Het...

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29th ieee international conference on Electronics, Circuits and systems (ieee ICECS)

作者： Kim, Jungho Choi, Hoon Cho, Insang Cho, Youngchan Samsung Elect SOC Platform Dev Team Syst LSI Business Samsung E Hwaseong South Korea

ISBN: (数字)9781665488235

ISBN: (纸本)9781665488235

embedded artificial intelligence has emerged as an essential technology to realize next-generation embedded services such as self-driving cars, augmented reality, virtual reality and AI camera. For the embedded AI, one of the key technologies is heterogeneous computing that utilizes all available computing units. However, it requires excessive power consumption because of utilizing the all computing units. Since it is crucial to reduce the excessive power consumption, numerous DVFS related work has been proposed to properly lower their operating frequency. However, the existing related work is not suitable to guarantee the desired time of a neural network. In order to overcome the limitation, we propose a neural network characteristics-aware proactive boost for heterogeneous computing. The proposed approach proactively estimates the lowest operating frequencies of NPU, DSP, GPU, CPU, memory controller and system bus to guarantee the desired time of the neural network. We implement our approach into the Galaxy S22 with Exynos 2200. We show the effectiveness of the proposed approach via extensive experiments.

关键词： neural network heterogeneous computing DVFS Exynos NPU DSP CPU GPU embedded system energy efficiency

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