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检索条件"任意字段=13th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications"

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QoS Guaranteed Resource Allocation for Coexisting eMBB and URLLC Traffic in 5G Industrial Networks 28

QoS Guaranteed Resource Allocation for Coexisting eMBB and U...

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28th ieee international conference on embedded and real-time computing systems and applications (RTCSA)

作者： Shen, Dawei Zhang, Tianyu Wang, Jiachen Deng, Qingxu Han, Song Hu, Xiaobo Sharon Northeastern Univ Sch Comp Sci & Engn Shenyang Peoples R China Univ Connecticut Dept Comp Sci & Engn Storrs CT 06269 USA Univ Notre Dame Dept Comp Sci & Engn Notre Dame IN 46556 USA

ISBN: (数字)9781665453448

ISBN: (纸本)9781665453448

the fifth-generation (5G) cellular networks are increasingly considered for industrial applications, such as factory automation systems. In 5G networks, Enhanced Mobile Broadband (eMBB) and Ultra-Reliable Low-Latency Communication (URLLC) are two essential services. eMBB services require high data rates with some lower bounds while URLLC traffic is subject to strict latency and reliability requirements. Existing approaches to scheduling coexisting eMBB and URLLC traffic all assume that URLLC traffic preempts eMBB traffic immediately upon arrival, which can adversely impact the achievable eMBB data rates. Furthermore, none of the prior work considers guaranteeing minimum data rate requirements imposed on certain eMBB traffic. this paper proposes a new model to capture the URLLC and eMBB requirements and introduces a novel framework, QoSG-RA, to perform network resource allocation for coexisting eMBB and URLLC traffic. QoSG-RA builds on a hybrid offline/online approach which performs offline resource allocation to ensure the Quality of Service (QoS) requirements of eMBB and URLLC traffic to be satisfied and online resource allocation to maximize fairness on the data rates among eMBB traffic based on runtime information. QoSG-RA is able to (i) meet latency and reliability requirements of URLLC traffic, and (ii) maximize the data rates for eMBB traffic in a fair way while fulfilling their minimum data rate requirements. Experimental results demonstrate the effectiveness of QoSG-RA compared to the state-of-the-art.

关键词： QoS 5G industrial applications eMBB URLLC coexisting performance resource allocation

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T-SYS: timed-Based System Security for real-time Kernels 13

T-SYS: Timed-Based System Security for Real-Time Kernels

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13th ACM/ieee international conference on Cyber-Physical systems (ICCPS )

作者： McDonald, Brayden Mueller, Frank North Carolina State Univ Raleigh NC 27695 USA

ISBN: (纸本)9781665409674

the increasing proliferation of cyber-physical systems in a multitude of applications presents a pressing need for effective methods of securing such devices. Many such systems are subject to tight timing constraints, which are poorly suited to traditional security methods due to the large runtime overhead and execution time variation introduced. However, the regular (and well documented) timing specifications of real-time systems open up new avenues with which such systems can be secured. this paper contributes T-SYS, a timed-system method of detecting intrusions into real-time systems via timing anomalies. A prototype implementation of T-SYS is integrated into a commercial real-time operating system (RTOS) in order to demonstrate its feasibility. Further, a compiler-based tool is developed to realize a T-SYS implementation with elastic timing bounds. this tool supports integration of T-SYS protection into applications as well as the RTOS the kernel itself. Results on an ARM hardware platform with benchmark tasks including those drawn from an open-source UAV code base compare T-SYS with another method of timing-based intrusion detection and assess its effectiveness in terms of detecting attacks as they intrude a system.

关键词： real-time systems security worst-case execution time

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Obstruction simulation in real-time 3D audio on edge systems 20

Obstruction simulation in real-time 3D audio on edge systems

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20th ieee international conference on embedded and Ubiquitous computing (EUC)

作者： Surricchio, Mattia Damiani, Andrea Santambrogio, Marco D. Politecn Milan DEIB Milan Italy

ISBN: (纸本)9798350396355

After the COVID-induced lock-downs, augmented/virtual reality turned from leisure to desired reality. real-time 3D audio is a crucial enabler for these technologies. Nevertheless, systems offering object spatialization in 3D audio fall in two limited cases. they either require long-running pre-renders or involve powerful computing platforms. Furthermore, they mainly focus on active audio sources, while humans rely on the sound's interactions with passive obstructions to sense their environment. We propose a hardware co-processor for real-time 3D audio spatialization supporting passive obstructions. Our solution attains similar latency w.r.t. workstations while draining a tenth of the power, making it suitable for embedded applications.

关键词： Coprocessors Digital signal processors Audio systems

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Enhancing Smart Home Automation with Arduino and Artificial Intelligence 13

Enhancing Smart Home Automation with Arduino and Artificial ...

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13th international conference on System Modeling and Advancement in Research Trends, SMART 2024

作者： Ahmad, Nazia Hussain, Sajithunisa Khan, Rubina Liyakat Quraishi, Suhail Javed Singh, Anupam George, Remya P. Applied College Imam Abdulrahman Bin Faisal University Dammam Saudi Arabia Mriirs Computer Applications Haryana Faridabad India Graphic Era Hill University Department of Computer Science and Engineering Uttarakhand Dehradun India

ISBN: (纸本)9798350380583

the current instigation aims to examine how AI and IoT work hand in hand to use smart home automation with a special focus on the application based on Arduino microcontrollers. the suggested system focuses on increasing comfort, convenience, and safety of the home spaces by applying AI algorithms. the system comprises a number of integrated sensors and actuators that gather real time data and the data is analyzed and decisions are made by an AI control module. the strategies of design considerations, implementation, and the assessment of the energy usage, comfort level for the user and the security aspects of the system are also provided in the study. Exploitation of the proposed experimental benchmark confirms potential advancement compared to traditional systems, including the viability of successful, comprehensive smart home platforms. Keywords: Smart Home Automation, Energy Efficiency, Internet of things (10 T), Artificial Intelligence (AI), Arduino Uno © 2024 ieee.

关键词： Smart homes

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Constructing Future Vehicle Digital Twins with Insights from Cloud-Edge Collaboration 21

Constructing Future Vehicle Digital Twins with Insights from...

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21st ieee international Symposium on Parallel and Distributed Processing with applications, 13th ieee international conference on Big Data and Cloud computing, 16th ieee international conference on Social computing and Networking and 13th international conference on Sustainable computing and Communications, ISPA/BDCloud/SocialCom/SustainCom 2023

作者： Shi, Xin Zhao, Liang Lin, Na Xu, Lexi Hawbani, Ammar Bi, Yuanguo Shenyang Aerospace University Shenyang China China Unicom Beijing China Northeastern University Shenyang China

ISBN: (纸本)9798350329223

Intelligent Transportation System (ITS) is embarking on a new development road, in which Digital Twins (DT) provides crucial support for improving the smartness standard of vehicles and realizing a high-level of traffic management in this process. However, the existing solutions face challenges such as limited computing resources, data scarcity and data distribution, which hinder the application prospects of DT for ITS. First, we propose the concept of future-oriented DT aim to address these issues. Specifically, lightweight local DTs are deployed at the different edge servers to provide services for vehicles, and a strong performance global DT is deployed in the cloud server to manage and optimize the local DTs. then, we introduce a collaborative learning method between two models to construct the DT network architecture and realize the vision of the future-oriented. this method makes use of rich global knowledge and local data, so that the model can dexterously integrate personalization and generalization capabilities. Finally, We use an Incremental Learning algorithm to improve the ability of the model that adapt to new scenarios and changing input data. All experiments are based on real traffic data, and trajectory prediction task as application carrier. Experimental results demonstrate the effectiveness of the proposed method, and the stability and performance of DTs have achieved excellent performance in the construction process. © 2023 ieee.

关键词： Learning systems

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Depth Estimation Using Single Fisheye Camera 13

Depth Estimation Using Single Fisheye Camera

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13th ieee international conference on CYBER Technology in Automation, Control, and Intelligent systems, CYBER 2023

作者： Kwok, Chun Xi, Ning The University of Hong Kong Department of Industrial and Manufacturing Systems Engineering Hong Kong

ISBN: (纸本)9798350315196

With the increasing utilization of automotive navigation systems in automotive platforms. the robot system is required to measure the distance of the surrounding area in real time. Omnidirectional distance measurement technology has emerged as a crucial requirement in the robotic industry. Traditional distance measurement methods for example stereo cameras and time of flight sensors have a limited field of view. this paper reports on a novel depth estimation method that operates on the mobile platform. the method involves collecting 180° fisheye images or 360° panoramic images via a single fisheye camera, detecting target objects in the image, and estimating their distance and size. this method can provide real-time omnidirectional distance estimation using a single fisheye camera, with an average recognition accuracy of 92.60% for 480 human targets with varying sizes and poses. the experimental result shows that the accuracy does not affect by the target size and pose. the improved distance estimation method has significant potential for robotic applications such as real-time obstacle avoidance. © 2023 ieee.

关键词： Object detection

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embedded real-time Human Activity Recognition on an ESP32-S3 Microcontroller Using Ambient Audio Data 12

Embedded Real-Time Human Activity Recognition on an ESP32-S3...

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12th ieee international conference on Intelligent Data Acquisition and Advanced computing systems: Technology and applications, IDAACS 2023

作者： Pfitzinger, thomas Wohrle, Hendrik Dortmund University of Applied Sciences and Arts Dortmund Germany

ISBN: (纸本)9798350358056

the task of Human Activity Recognition (HAR) finds application in smart homes and assisted living and is mostly approached with machine learning. Sensor data for HAR is often collected and processed by separate devices. Performing the recognition task directly on the sensor device can decrease network traffic and reduce the related energy consumption and privacy concerns. In this work, an intelligent sensor device is developed that performs real-time HAR on an ESP32-S3 microcontroller using ambient audio data. A convolutional neural network to classify human activities is designed and subsequently reduced in size and computation cost in order to enable its inference on the microcontroller. this is achieved with neural architecture search, resulting in multiple simplified model variations. these are tested on the ESP32-S3 and a feasible version is identified. © 2023 ieee.

关键词： embedded systems Human Activity Recognition Machine Learning Microcontrollers Neural Architecture Search

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Artificial Intelligence-Driven Solutions for Privacy and Security in Smart City Data Management systems for Smart Cities 13

Artificial Intelligence-Driven Solutions for Privacy and Sec...

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13th international conference on System Modeling and Advancement in Research Trends, SMART 2024

作者： Jena, Rakesh Kumar, Mandeep Mallela, Indra Reddy Das, Abhishek Vashishtha, Sangeet Agarwal, Nishit Biju Patnaik University of Technology Odisha Bhubaneswar Rourkela India Sharda School of Law Sharda University Greater Noida India Independent Researcher Telangana Suryapet508213 India Ring Road Baimundi Marg Near Hanuman Mandir Dagarpara Cuttack Sadar Odisha Cuttack753002 India Iimt University Meerut India Rikab Gunj Telangana Hyderabad500002 India

ISBN: (纸本)9798350380583

In addition to traffic management, energy, education, healthcare, and urban development, smart city applications generate significant amounts of data. real-time monitoring and analysis of urban events is possible due to the continuous production of this data. Nevertheless, reliable and efficient data management resources are necessary in order to utilize all this information effectively. A comprehensive review of the role that data management systems play in smart city environments is presented in this paper, emphasizing the importance of advanced methodologies for ensuring data integrity, privacy, and security. In this article, we examine the challenges posed by privacy threats stemming from sensitive data exchanges, explain the inadequacies of current privacy measures, and analyze AI's implications for handling data. Based on an indepth analysis, the study demonstrates the importance of integrating robust data management strategies into smart city development in order to facilitate informed decision-making and enhance service delivery. © 2024 ieee.

关键词： Data integrity

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Sleep Apnea Detection System Using Machine Learning on Resource-Constrained Devices 17

Sleep Apnea Detection System Using Machine Learning on Resou...

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17th Annual ieee international systems conference (SysCon)

作者： Mallick, Sayani Gawali, Shubhangi Onime, Clement Goveas, Neena BITS Pilani EEE Dept Goa Campus Sancoale Goa India BITS Pilani CSIS Dept Goa Campus Sancoale Goa India Abdus Salaam Int Ctr Theoret Phys Trieste Italy

ISBN: (纸本)9781665439947

Sleep Apnea is a condition in which a person has pauses in breathing or very low breathing episodes during sleep. It is a condition that could prove life-threatening if not monitored and treated. A medical diagnosis of Sleep Apnea involves overnight recording of body signals, monitoring by a medical professional, use of hospital based equipment and data analysis for detection of anomalies. During the past decade, the measurement and analysis of human body signals using machine learning techniques on embedded devices have started to transform healthcare applications. the use of cost effective micro-controllers can ensure that health monitoring is available and accessible to all. In this paper, we show that machine learning models deployed on microcontrollers can successfully analyze ECG signals in real-time for Sleep Apnea detection. We have created TinyML models using TensorFlow Lite which we have deployed on cost effective and resource constrained devices like the Raspberry Pi Pico and ESP32. Our setup has given results comparable to more advanced and expensive devices for the detection of Sleep Apnea using ECG signals.

关键词： ECG embedded Device Signal Processing TinyML TensorFlow Lite Machine Learning Edge Impulse Sleep Apnea Artificial Neural Networks Edge computing

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Guiding Hardware-Driven Turbo with Application Performance Awareness 13

Guiding Hardware-Driven Turbo with Application Performance A...

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ieee 13th international Green and Sustainable computing conference (IGSC)

作者： Wilson, Daniel C. Al-rawi, Asma H. Lawson, Lowren H. Jana, Siddhartha Ardanaz, Federico Eastep, Jonathan M. Coskun, Ayse K. Intel Corp Santa Clara CA USA Boston Univ Boston MA USA

ISBN: (数字)9781665465502

ISBN: (纸本)9781665465502

Parallel programming across many CPU cores offers many challenges in software design, such as mitigating performance or efficiency loss in applications that reach synchronization points at varying times across the CPU cores. Existing solutions often aim to resolve this through clever optimizations in application design, or by reacting to the imbalance by throttling the CPU core frequency of the early-finishing cores at application run time. In this work, we propose a method to rebalance bulk-synchronous MPI applications by selectively speeding up the late-finishing cores throughout application run time. this algorithm makes use of the new Intel (R) Speed Select Turbo Frequency feature that enables software to guide the hardware toward increasing the turbo frequency limits of some cores in exchange for decreased turbo frequency limits in other cores. We demonstrate up to 40% energy reduction and 17% execution time reduction in a highly-imbalanced, compute-bound benchmark application and up to 21% energy reduction with 5% execution time reduction in an imbalanced real-world application.

关键词： energy-aware systems power management

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