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

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Energy Consumption Aspects on embedded System for IoT applications 13

Energy Consumption Aspects on Embedded System for IoT Applic...

引用

13th international conference on Modern Circuits and systems Technologies (MOCAST)

作者： Sofianidis, Ioannis Konstantakos, Vasileios Nikolaidis, Spyridon Aristotle Univ Thessaloniki Phys Dept Thessaloniki Greece

ISBN: (纸本)9798350385434;9798350385427

In the era of IoT and mobile computing an important factor for the lifespan of related devices is current consumption. In this paper the current consumption of an audio monitoring IoT system that incorporates an RP2040 MCU and a PDM MEMS microphone, and performs recording, processing, and transmitting of data is explored. A variety of measurement sets were conducted for current profiling purposes. The MCU was monitored during different operating conditions, working phase, light sleep, deep sleep and dormant. Its consumption was measured during execution of various computational loads, as defined by three algorithms as FFT, FIR and Autocorrelation. Additionally, the power consumption for data transmission over UART protocol was measured in different baud rates. Furthermore, all the above measurements were performed in several operating conditions, regarding frequency and voltage settings. The collected measurements form a guide on energy demands of an IoT system audio specific based on RP2040 MCU.

关键词： embedded systems IoT applications energy consumption measurements low power operation voltage and frequency tradeoffs

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Elderly Activity Recognition Based embedded Machine Learning 31

Elderly Activity Recognition Based Embedded Machine Learning

引用

31st conference on Electronics Circuits and systems

作者： Yaacoub, Mohamad Khalifeh, Razan Herz, Zahraa Ibrahim, Ali Univ Genoa Dept Naval Elect Elect & Telecommun En Genoa Italy Lebanese Int Univ Dept Elect & Elect Engn Beirut Lebanon

ISBN: (纸本)9798350377217;9798350377200

This paper presents the implementation of an embedded-based machine learning system for elderly activity recognition. Two types of neural networks namely Convolutional Neural Network (CNN) and Multilayer Perceptron (MLP) were used to process data from Inertial Measurement Units (IMUs) sensors mounted on the legs of elderly participants. Results demonstrate the effectiveness of the proposed system in classifying elderly activity, achieving an accuracy of 99% and 80% for CNN and MLP, respectively. The MLP performs better in inference time than the CNN with 2 ms per classification compared to 656 ms for CNN. The proposed system has been successfully deployed on an Arduino nano BLE sense providing real-time on-board elderly activity recognition.

关键词： Human activity recognition multilayer perceptron convolutional neural network embedded neural networks

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CYNQ: Speeding Up FPGA applications With Simplicity 31

CYNQ: Speeding Up FPGA Applications With Simplicity

引用

31st conference on Electronics Circuits and systems

作者： Leon-Vega, Luis G. Avila-Torres, Diego Leon-Vega, Indra Castro-Godinez, Jorge Univ Trieste Math Informat & Geosci Dept Trieste Italy Univ Estatal Distancia Informat Sch Liberia Costa Rica Inst Tecnol Costa Rica Sch Ind Design Engn Cartago Costa Rica Inst Tecnol Costa Rica Sch Elect Engn Cartago Costa Rica

ISBN: (纸本)9798350377217;9798350377200

FPGAs for hardware acceleration face several issues in their adoption by the emerging AI embedded software community, mainly due to the difficulty of getting started in the field. To address these issues, FPGA vendors have tried to simplify and combine workflows to make them user-friendly. This has also impacted the runtime libraries used on Linux to allow user space applications to interact with FPGA programmable logic. However, this approach can result in suboptimal results, given the added overhead in single-purpose applications in an attempt to generalise the runtime libraries. This work presents CYNQ Runtime Library, a simplistic and API-agnostic C/C++ runtime library with the ease of PYNQ and the efficiency of C++ and XRT. In comparison to most popular runtime libraries for AMD FPGAs, our work outperforms PYNQ and XRT with more than 5.34x speedup in execution latency and more than 1.20x in large workloads than XRT, which poses a better scenario for high-performance single-purpose applications.

关键词： Field Programmable Gate Arrays Hardware Acceleration Edge computing Cloud computing High Performance computing

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MemFlex: A Hybrid Memory System to boost Cost of Ownership in Data Centers 48

MemFlex: A Hybrid Memory System to boost Cost of Ownership i...

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48th Annual ieee international Computers, Software, and applications conference (COMPSAC) - Digital Development for a Better Future

作者： Chakrabortti, Chandranil Islam, Mohammad Maminur Trinity Coll Dept Comp Sci Hartford CT 06106 USA

ISBN: (纸本)9798350376975;9798350376968

Modern large-scale computing clusters face scalability challenges with traditional DRAM-based memory systems due to issues like increasing cell leakage current and reduced reliability. To overcome these limitations, alternative memory solutions have emerged, including 3D-stacked DRAM and emerging non-volatile memory (NVM) technologies. However, these alternatives are unlikely to fully replace DRAM due to capacity constraints and higher cost-per-bit. Hybrid memory systems, combining DRAM with NVM technologies, offer a cost-effective solution by leveraging the strengths of both memory types. Effective data placement decisions are crucial for optimizing hybrid memory systems. This paper introduces MemFlex, an machine learning (ML)-driven approach for migrating pages between memory tiers in a hybrid memory system based on predicted page lifetimes. MemFlex utilizes application-specific ML models to predict death-time ranges with high accuracy, guiding placement decisions to the appropriate storage tier. Evaluation results demonstrate MemFlex's superiority over state-of-the-art techniques, achieving an average performance improvement of 19% over evaluated baselines, with minimal performance degradation. This paper contributes to hybrid memory management research, leveraging real-world traces for evaluation, and introducing an ML based approach for optimized data placement decisions.

关键词： Hybrid memory systems Page migration Data placement Memory management Death-time prediction

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SUMMARY OF THE 2024 LOW-POWER EFFICIENT AND ACCURATE FACIAL-LANDMARK DETECTION FOR embedded systems

SUMMARY OF THE 2024 LOW-POWER EFFICIENT AND ACCURATE FACIAL-...

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ieee international conference on Multimedia and Expo (ICME)

作者： Ni, Yu-Shu Chen, Han-Chun Tsai, Chia-Chi Chen, Chih-Cheng Chen, Po-Yu Kuo, Hsien-Kai Hunag, Jun-Ying Hui, Po-Chi Hwang, Jenq-Neng Guo, Jiun-In Natl Yang Ming Chiao Tung Univ Dept Elect Engn Hsinchu Taiwan Natl Yang Ming Chiao Tung Univ Inst Elect Hsinchu Taiwan Natl Cheng Kung Univ Dept Elect Engn Tainan Taiwan Pervas Artificial Intelligence Res Labs PAIR Labs Hsinchu Taiwan Univ Washington Dept Elect Engn Seattle WA 98195 USA MediaTek Inc Hsinchu Taiwan

ISBN: (纸本)9798350379822;9798350379815

The 2024 ieee ICME Grand Challenge has been a pivotal event in advancing low-power efficient and accurate facial-landmark detection for embedded systems. It emphasized the development of models that are both energy-efficient and highly accurate. With participation from 165 teams, the competition provided an extensive dataset for model training, highlighting facial diversity to bolster model resilience. This competition unfolded in two phases: an initial online evaluation and a subsequent final round conducted on the MediaTek Dimensity 9300 Series platform, aimed at assessing the efficacy of real-time applications. A critical aspect of the competition was the models' ability to precisely detect 51 facial landmarks, a feature integral to applications such as autonomous driving, by capturing detailed facial expressions. The victors of the challenge were recognized based on their models' accuracy and minimal power consumption, marking a notable advancement in the field of facial-landmark detection and significantly advancing applications in embedded systems.

关键词： Facial-landmark detection autonomous driving and embedded deep learning

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Advancing Human-Computer Interaction: real-time Gesture Recognition and Language Generation Using CNN-LSTM Networks

Advancing Human-Computer Interaction: Real-Time Gesture Reco...

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2024 international conference on Innovative computing, Intelligent Communication and Smart Electrical systems, ICSES 2024

作者： Kavitha, M. Brintha Rajakumari, S. Bharath Institute of Higher Education and Research Department of Computer Applications Tamil Nadu Chennai India Bharath Institute of Higher Education and Research Department of Computer Science Tamil Nadu Chennai India

ISBN: (纸本)9798331543617

Efficient human-computer interaction (HCI) has pushed forward hand gesture recognition (HGR), and natural language utterance generation (NLUG). Traditional systems are limited because these rely on static infrastructure and manual processing, accompanied by inaccuracies and latency. In comparison, the proposed system uses an advanced fusion of convolutional neural networks (CNNs) for gesture recognition and long short-term memory (LSTM) networks for language generation to achieve real-time processing with context-aware responses. The results of the experiments showed a 90.5% increase in precision for gesture recognition and BLEU score 0,715 NLUG were described as displaying superiority to existing systems on the tool performance The proposed approach also reduces the latency to 90 ms, while in traditional systems it is about 150 ms. These results suggest an opportunity to reimagine HCI systems as truly immersive and efficient, responsive experiences that can optimize not only user interactions with applications in specific domains, but also social computing at large. © 2024 ieee.

关键词： real time systems

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Digital Shadow Enabled Integrated Multi-platform Automation System for Industrial Assembly 10

Digital Shadow Enabled Integrated Multi-platform Automation ...

引用

10th ieee international conference on Electronics, computing and Communication Technologies (ieee CONECCT)

作者： Revankar, Ashutosh Halapeti, Deepa Vengurlekar, Samarth Giriyapur, Arunkumar C. KLE Technol Univ Dept Automat & Robot Hubballi India

ISBN: (纸本)9798350385939;9798350385922

This paper presents a fully autonomous assembly line for custom cubes with two sub-block options (plastic and aluminium). Users can design their cubes through an Android app or website interface. The system retrieves orders, processes them based on deadlines, and dispenses the required sub-blocks. A quality inspection station with computer vision and machine learning ensures that defect-free parts are used. Cobots handle sub-block transportation and manipulation throughout the assembly process, with a dedicated station for inserting pins when necessary. A digital Shadow model facilitates performance analysis and optimization. Cloud-based platforms manage data, order processing, and remote access. Finally, an Automated Storage and Retrieval System (ASRS) manages cube storage and delivery. This research demonstrates the potential of combining automation, machine learning, and real-time monitoring for efficient custom product assembly. The approach offers applications in various industries and lays the groundwork for future research on expanding customization options and production flow optimization.

关键词： Digital-shadow Robotic assembly line Pneumatic systems Industry 4.0 IoT Control strategy optimization MATLAB Simulink OPC UA server PLCs

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WIRE: Web3 Integrated Reputation Engine 44

WIRE: Web3 Integrated Reputation Engine

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44th ieee international conference on Distributed computing systems (ICDCS)

作者： Jain, Suraj Shamsundar Zhou, Huancheng Gu, Guofei Texas A&M Univ SUCCESS Lab College Stn TX 77840 USA

ISBN: (纸本)9798350386066;9798350386059

Distributed applications (DApps), powered by smart contracts, have sparked a significant transformation in the Web3 ecosystem by enabling the execution of real-world contracts on decentralized networks. However, the growing popularity of DApps has also led to an increase in malicious activities exploiting smart contracts, thereby exposing users to greater financial risks. Inspired by the FICO score system in traditional finance, we introduce WIRE, a reputation engine designed to evaluate the trustworthiness of deployed DApps. WIRE first derives diverse properties from contract activities, rather than relying solely on potentially irrelevant or unavailable source code. Based on selected properties, WIRE trains a machine learning model for assessing the trustworthiness of individual contracts. Furthermore, WIRE utilizes a bytecode disassembler to identify related contracts of a DApp, thus determining its overall trustworthiness score. Moreover, WIRE's dashboard offers explainable and detailed reports that are accessible to users without professional knowledge. The evaluation results show that WIRE can provide a reliable and explainable reputation score for DApps. As a result, WIRE's users can distinguish between benign and malicious DApps or contracts with a high confidence.

关键词： blockchain security ethereum decentralized applications

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Low-Power Design of Advanced Image Processing Algorithms under FPGA in real-time applications 4

Low-Power Design of Advanced Image Processing Algorithms und...

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4th ieee international conference on Power, Electronics and Computer applications, ICPECA 2024

作者： Wang, Yuyao Lamar University Department of Electrical Engineering BeaumontTX United States

ISBN: (纸本)9798350359589

Due to the real-time measurement required for image processing in practice, image processing technology is increasingly supplemented by hardware, such as using DSP (Digital Signal Processing) chips (image processing specific chips). However, when storing and processing large amounts of data, using DSP for image processing also has problems such as slow processing speed and poor real-time performance of the system. This article combines the embedded cache module in the IP core of FPGA (Field Programmable Gate Array) with the read/write ping-pong structure to store and retrieve image data, in order to save memory space on the chip. The relatively simple algorithm functions and parallel computing of FPGA, combined with a pipeline structure, shorten the image preprocessing time and solve the problem of poor real-time image processing. The experimental results show that due to the increase in workload, the static power consumption of FPGA algorithm design only increased from lW to 1.242W, while the static power consumption of traditional design increased from 1.009W to 1.578W;The dynamic power consumption of FPGA algorithm design has increased from 1.005W to 1.489W. © 2024 ieee.

关键词： Field Programmable Gate Array Image Processing Low-power Design Synchronous Dynamic Random Access Memory

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A Logical time-Triggered Distributed computing Environment for Cyber-Physical systems with V2X Wireless Communication 1

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17th international conference on Information Technology and applications, ICITA 2023

作者： Nakajima, Shunsuke Shimabukuro, Kenji Takehara, Eiya Yokoyama, Takanori Yoo, Myungryun WingArc1st Inc. Tokyo Japan BIGLOBE Inc. Tokyo Japan TOPPAN Edge Inc. Tokyo Japan Tokyo City University Tokyo Japan

ISBN: (数字)9789819983247

ISBN: (纸本)9789819983230

The paper presents a logical time-triggered distributed computing environment for cyber-physical systems utilizing V2X (Vehicle to Everything) wireless communication based on ieee802.11p protocol. Logical time-triggered processing realizes real-time distributed computing equivalent to the time-triggered architecture without time synchronization. We have developed a real-time operating system emulator running on Linux, which manages tasks based on EDF (Earliest Deadline First) scheduling with logical deadlines. We have also developed distributed computing middleware that manages logical time and timestamped messages and communication software that supports ieee802.11p. By using the distributed computing environment, logical time-triggered cyber-physical systems with ieee802.11p wireless communication can be developed without considering either timestamps or logical time. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： real time systems

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