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检索条件"任意字段=Conference on Advanced Sensor Systems and Applications III"

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Trade-off Analysis of Gateway Strategies for Embedding of CAN Frames into Ethernet Packets 15

Trade-off Analysis of Gateway Strategies for Embedding of CA...

引用

15th International conference on Information and Communication Technology Convergence, ICTC 2024

作者： Bae, Sungwon Park, Hanyoung Ko, Kanghyun Choi, Ji-Woong Dgist Department of Electrical Engineering and Computer Science Daegu Korea Republic of Cheonan Korea Republic of

ISBN: (纸本)9798350364637

The advancement of advanced driver assistance systems (ADAS) has increased the demand for more sensor data within vehicles, necessitating faster data transmission. To meet this requirement, in-vehicle networks (IVNs) with higher link speeds are essential, as the data rates of traditional IVN protocols are insufficient for future applications. To address these demands, an IVN architecture that integrates both controller area network (CAN) and automotive Ethernet is being considered. The coexistence of CAN and automotive Ethernet necessitates the use of gateways, which introduces latency when transferring data from CAN to automotive Ethernet. However, many studies have not thoroughly explored the strategies and characteristics of such gateways and their impact on performance. Therefore, in this paper, we analyze the processing latency and network efficiency associated with different gateway strategies for embedding CAN frames into Ethernet packets. The findings of this study show the trade-off between latency and network efficiency and highlight the potential for optimizing CAN-Ethernet gateways. © 2024 IEEE.

关键词： advanced driver assistance systems

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STFO - Power-Saving Deep-Sleep States are Overrated 12

STFO - Power-Saving Deep-Sleep States are Overrated

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12th IEEE International conference on Intelligent Data Acquisition and advanced Computing systems: Technology and applications, IDAACS 2023

作者： Ziesmann, Maurice-Christian Fuhner, Claus Busching, Felix Ostfalia - University of Applied Sciences Wolfenbüttel38302 Germany

ISBN: (纸本)9798350358056

In many Internet-of-Things (IoT) and Wireless sensor Network (WSN) application areas, where the wireless nodes sleep most of the time, ultra-low power micro-controllers (μ Cs) are used, which usually feature several sleep modes. At particularly low duty cycles, the corresponding μ C are put into a very deep sleep mode, from which they wake up again - either independently by a timer or triggered from outside - to then perform their actual tasks. In the application area of addressable Wake-up Radios (WURs), mostly μ Cs are used as address decoder, which have a very low quiescent current consumption. In this paper, we show that for the purpose of address decoding in WURs it is not necessary to rely on μ Cs with particularly low sleep current consumption, because it is much more useful to simply switch off the μ Cs by an upstream circuit and thus save even more energy. Our evaluation results suggest that the lessons learned can also be applied to other application areas. © 2023 IEEE.

关键词： addressing energy efficiency internet of things PIC sleep modes sleep states wake-up calls wake-up radios wireless sensor networks

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Radio Frequency and Wireless Optical Communication Comparison for WSN and IoT applications 7

Radio Frequency and Wireless Optical Communication Compariso...

引用

7th IET Smart Cities Symposium, SCS 2023

作者： Amenchar, Ouiam Chakkor, Saad Dkiouak, Aziz Baghouri, Mostafa University of Abdelmalek Esaadi Route de Ziaten Km 10 Tanger Principale B.P1818 Tangier Morocco Sciences and Advanced Technologies Team ENSA Of Tetuan Abdelmalek Essadi University Morocco Laboratory LCCPS ENSAM de Casablanca Hassan II University 150 Boulevard du Nil Casablanca20670 Morocco

ISBN: (纸本)9781839539831

With the continuous expansion of intelligent sensor systems, efficient wireless communication technologies have become increasingly important. This paper presents a concise comparative study between Radio Frequency (RF) communication and Wireless Optical Communication (WoC) using Visible Light Communication (VLC) for Wireless sensor Network (WSN) and Internet of Things (IoT) applications. This study evaluated various performance metrics, such as effective energy utilization, throughput, energy efficiency, link distance, SNR, BER, total attenuation, and received power under varying visibility conditions. Simulation results and theoretical analysis, conducted using MATLAB, demonstrate that WOC outperforms RF communication in most of the analyzed performance metrics. These findings provide valuable insights for optimizing wireless communication systems for intelligent sensor applications. © The Institution of Engineering & Technology 2023.

关键词： Energy utilization

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A STUDY ON CHIP DELAY MEASUREMENT sensor BASED ON SCAN CHAIN 10

A STUDY ON CHIP DELAY MEASUREMENT SENSOR BASED ON SCAN CHAIN

引用

10th International Symposium on Test Automation and Instrumentation, ISTAI 2024

作者： Liu, Peixin Hu, Xiao Yi, Xinjie National University of Defense Technology Changsha China Key Laboratory of Advanced Microprocessor Chips and Systems Changsha China

ISBN: (纸本)9781837242672

The reliability and performance of integrated circuits degrade over time, with one critical factor being the aging of numerous internal combinational logic circuits. Delay variations in these circuits not only reflect the chip's external environmental conditions but also indicate the degree of aging during its operational life. Traditional aging delay measurement sensors typically employ dedicated sampling circuits, which pose challenges for comprehensive detection of delays across all combinational logic paths within the chip. This study introduces a novel chip aging sensor, termed the FATE-sensor, which leverages the internal scan chains of the chip. By performing a full-chip frequency scan of the combinational logic circuits, the FATE-sensor can detect delay variations at various combinational logic locations using the extensive coverage provided by the scan chains. This paper presents a detailed investigation of the FATE-sensor's characteristics, including its consistency, repeatability, temperature and voltage dependencies, and resolution enhancement. Experimental calibration of the FATE-sensor demonstrates its effectiveness in monitoring and reflecting delay variations within the chip's internal circuits. This capability allows for accurate assessment of the chip path delay status, thus enhancing the reliability of chips used in high-precision and advanced applications. This technology not only aids in identifying potential faulty chips and supports chip timing verification testing but also provides new insights for understanding and extending chip lifespan. © The Institution of Engineering & Technology 2024.

关键词： Delay circuits

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Mathematical Model for Determining the Geometric Location of the Environmental Pollutant Based on sensor Data 12

Mathematical Model for Determining the Geometric Location of...

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12th IEEE International conference on Intelligent Data Acquisition and advanced Computing systems: Technology and applications, IDAACS 2023

作者： Khaidurov, Vladyslav Yailymov, Bohdan Shelestov, Andrii National Technical University of Ukraine 'Igor Sikorsky Kyiv Polytechnic Institute' Kyiv03056 Ukraine Space Research Institute NASU-SSAU Kyiv03187 Ukraine

ISBN: (纸本)9798350358056

The practical result of this work is the development of a generalized mathematical model for determining the position of an environmental pollutant. Computer simulation was carried out in order to verify the developed mathematical model. A number of computational experiments were conducted to verify the mathematical model. In the future, the developed algorithm is proposed to be used for real ground air quality measurement stations with additional use of air quality information from satellite data and specify the location of the pollution source using the Urban Atlas. © 2023 IEEE.

关键词： environmental pollutant genetic algorithm inverse problem mathematical modeling PM2.5 smart city Urban Atlas

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Modelling of advanced sensor based Distributed Control System for Real- Time Prediction and Minimization of Power Loss in Industrial Automation systems 4

Modelling of Advanced Sensor based Distributed Control Syste...

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4th International conference on Expert Clouds and applications, ICOECA 2024

作者： Sengeni, D. Mano Jemila, M.R. Priya, G. Soorya Krishnan, T. Santhana Rathinasabapathi, G. Kannan, Sathish CK College of Engineering and Technology Department of Electronics and Communication Engineering Chellangkuppam Tamil Nadu Cuddalore607003 India Dr. N. G.P. Institute of Technology Department of Biomedical Engineering Tamil Nadu Coimbatore641048 India Loyola Institute of Technology Department of Electrical and Electronics Engineering Tamil Nadu Mevalurkuppam Chennai600123 India Department of Electrical and Electronics Engineering Tamil Nadu Thandalam Chennai602105 India Panimalar Engineering College Department of Mechanical Engineering Tamil Nadu Chennai600123 India Saveetha School of Engineering Saveetha Institute of Medical and Techinical Sciences Department of VLSI Microelectronics Tamil Nadu Chennai602105 India

ISBN: (纸本)9798350385793

This research study analyses the integration of a Distributed Control System (DCS) to optimise the efficiency and reliability of industrial automation, with a special emphasis on reducing power loss. Leveraging real-time sensor data and machine learning models, including Decision Trees, Artificial Neural Networks, and Random Forests, the research provides a proactive strategy to anticipating and avoiding anomalous current and voltage patterns. The DCS, armed with predictive maintenance procedures, emerges as a solid framework for reducing energy usage, assuring system stability, and limiting possible quality losses. Evaluation using performance ratings and confusion matrices reveals the efficiency of the proposed system in properly recognising and correcting deviations from normal operating circumstances. The results contribute not only to the progress of distributed control systems in industrial automation but also provide a realistic approach to real-time monitoring and predictive maintenance, supporting sustainability and operational excellence in manufacturing settings. This study sets a platform for future initiatives seeking to construct intelligent, adaptable systems for increased industrial automation performance. © 2024 IEEE.

关键词： Predictive maintenance

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Enhancing Indoor Mobile Robot Localization through the Integration of Multi-sensor Fusion Algorithms 1

Enhancing Indoor Mobile Robot Localization through the Integ...

引用

1st International conference on Robotics, Engineering, Science, and Technology, RESTCON 2024

作者： Yatigul, Rut Pudchuen, Noppadol Blattler, Aran Jitviriya, Wisanu King Mongkut's University of Technology North Bangkok Department of Production and Robotics Engineering Bangkok Thailand King Mongkut's University of Technology North Bangkok Department of Instrumentation and Electronics Engineering Bangkok Thailand

ISBN: (纸本)9798350348842

This paper presents an innovative approach that combines visual odometry, Inertial Measurement Unit (IMU), and wheel odometry, using the Extended Kalman Filter and Unscented Kalman Filter to enhance mobile robot localization and mapping. The primary goal is to improve localization accuracy and robustness while providing a cost-effective alternative to traditional SLAM methods that rely on expensive LIDAR and RGBD camera systems. By integrating visual odometry, IMU data, and wheel odometry our method not only enhances precision and robustness of the mobile robot localization system but also reduces the financial burden associated with high-end sensor hardware. This fusion creates a reliable solution, particularly suited for resource-constrained environments. Our research contributes to the democratization of SLAM technologies, making them more accessible to a wider range of applications. The results presented in this report showcase the potential of our approach. This paper highlights the pivotal role of multi-sensor fusion framework which significantly enhances localization accuracy and robustness. © 2024 IEEE.

关键词： Extended Kalman filters

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Leverage Diagnosis Intensity in Medication Recommendations 20th

Leverage Diagnosis Intensity in Medication Recommendations

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20th International conference on Intelligent Computing (ICIC)

作者： Aziz, Abdul Ali, Zafar Qi, Guilin Huang, Yi Kefalas, Pavlos Aminullah Ali, Asad Southeast Univ Sch Comp Sci & Engn Nanjing Peoples R China China Mobile Res Inst Beijing 100053 Peoples R China Aristotle Univ Thessaloniki Dept Informat Thessaloniki Greece

ISBN: (纸本)9789819756773;9789819756780

In recent years, the patient's medical records have grown rapidly. This has led to the need of medication recommendation systems that use past diagnoses and personalize the proposed treatment. The majority of those systems prioritize medication recommendations based on the current diagnoses of the patient's electronic health record (EHR) without considering diagnosis intensity. Thus, they fail to capture the intensity of the patient's condition, which leads to low accuracy on their recommendations. In this study, we propose a medication recommendation system that leverages the diagnosis intensity in medication recommendation (LDIM-R). The main goal of our model is to compare the severity of diagnoses at each visit to all the previous visits. The proposed study commences by accessing the patient's historical health record from the Medical Information Mart for Intensive Care (MIMIC-iii). Subsequently, the average intensity of previous diagnoses is calculated and compared to the diagnosed intensity of the current visit. Then the proposed model considers three factors: 1) there is no discernible change in the overall diagnosed intensity;2) the overall diagnosed intensity has declined;or 3) the overall diagnosed intensity has increased. As demonstrated by the result of our experiments over the MIMIC-iii dataset, our method outperformed state-of-the-art medication recommendation systems.

关键词： recommender systems medication recommendation diagnosis intensity electronic health record

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A Flexible Hybrid Resource Allocation Model for Enhanced Efficiency using AI in Wireless sensor Networks 3

A Flexible Hybrid Resource Allocation Model for Enhanced Eff...

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3rd International conference on Electronics and Renewable systems, ICEARS 2025

作者： Endla, Purushotham Mohandas, R. Saikia, Achinta Lakshmi, C. Karthikeyan, G. Moharekar, Tejashree Tejpal Sr University School of Sciences and Humanities Department of Physics Telangana Warangal506371 India Chennai Institute of Technology Department of Ece Chennai India Mariani College Department of Statistics Mariani Assam Jorhat785634 India Saveetha Engineering College Chennai India Karpagam College of Engineering Department of Artificial Intelligence & Data Science Coimbatore India Shivaji University Yashwantrao Chavan School of Rural Development Maharashtra Kolhapur India

ISBN: (纸本)9798331509675

Wireless sensor Networks (WSNs) have become a cornerstone technology in various fields, including environmental monitoring, industrial automation, and healthcare. This paper presents a novel hybrid resource allocation model designed to enhance efficiency in Wireless sensor Networks (WSNs) using advanced Artificial Intelligence (AI) techniques. The proposed model integrates static and dynamic resource allocation strategies with machine learning and reinforcement learning to optimize key network resources such as energy, bandwidth, and processing power. Comprehensive evaluations demonstrate that the proposed model outperforms nine existing models across multiple metrics, including energy efficiency, network lifetime, throughput, delay, latency, and accuracy of resource allocation. The proposed model achieved an energy efficiency of 0.98 J/bit, extended network lifetime to 620 days, and maintained a high throughput of 620 Kbps. Notably, the model demonstrated the lowest delay (90 ms) and latency (180 ms) while achieving the highest resource allocation accuracy of 97.8%. These results highlight the model's capability to dynamically adjust resource allocation in response to real-time network conditions, ensuring optimal performance and resource utilization. The proposed model's success in efficiently managing WSN resources marks a significant advancement in the field, offering a robust solution for various WSN applications requiring high efficiency and reliability. © 2025 IEEE.

关键词： Artificial Intelligence Energy Efficiency Machine Learning Network Lifetime Reinforcement Learning Resource Allocation Wireless sensor Networks

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Comparative Analysis of Multi Objective Node Placement Strategies in Wireless sensor Networks 17

Comparative Analysis of Multi Objective Node Placement Strat...

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17th IEEE International conference on advanced Networks and Telecommunications systems, ANTS 2023

作者： Ojha, Amritesh Gupta, Bharat National Institute of Technology Electronics & Communication Engineering Patna India

ISBN: (纸本)9798350307672

Real-world service providers in Wireless sensor Networks (WSN) face the challenge of balancing two important considerations: achieving a high coverage and extending the network's lifespan. The optimization problem of coverage in WSN holds significant importance as it aims to achieve a balance between network lifetime and coverage. This encompasses the reduction of energy consumption, the enhancement of coverage rate, and the optimization of energy consumption balance. Although heterogeneities are acknowledged and addressed in certain aspects of WSNs, such as routing protocols, researchers tend to overlook their significance when it comes to node placement or deployment. This research presents a comparative examination of multi-objective node placement algorithms in WSNs, specifically focusing on their performance in heterogeneous circumstances. However, the impact of an asymmetric link, which may vary depending on the node, is not well considered in heterogeneous WSNs. The detrimental effects of link heterogeneity on the performance of deployment methods have been observed. Our investigation revealed that the thought-out strategy for exploiting heterogeneity was not used. The implementation of sensor networks based on 6G technology in smart city applications necessitates the utilization of diverse sensor nodes. In order to achieve optimal resource usage, it is imperative to take into account the heterogeneity of nodes during the deployment process. © 2023 IEEE.

关键词： sensor nodes

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