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

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Design and Numerical Analysis of a Compact Microstrip Antenna sensor for Wireless Body Area Networks

Design and Numerical Analysis of a Compact Microstrip Antenn...

引用

2022 IEEE International conference on Signal Processing, Informatics, Communication and Energy systems, SPICES 2022

作者： Sreelekshmi, S. Sankar, S. Perumal Apj Abdul Kalam Technological University Toc H Institute of Science & Technology Department of Ece Kerala India

ISBN: (纸本)9781665449403

The design and analysis of wearable, reshaped rectangular patch antenna with resonant frequency of 2.5 GHz is proposed. The proposed antenna can be used as a microstrip sensor for wearable applications, which is made flexible and compact by using Arlon AD 1000 with thickness 1.6 mm and high dielectric constant 10.2, as the dielectric substrate. The miniaturization is further achieved by reshaping the rectangular patch which makes the overall dimensions of antenna as 25x25x1.6 mm3. Using the Ansys High-Frequency Structure Simulator software, various parameters like return loss, gain, VSWR, radiation efficiency and directivity are examined and validated using finite element approach. Proposed antenna exhibits a gain of 2.4275 dB, -25.6686 dB return loss, -10 dB bandwidth of 123 MHz, and directivity of 3.2742 dB, according to the simulation findings. Because of its compact design and flexibility, the proposed antenna can be employed as a microstrip sensor in Wireless Body Area Network applications. © 2022 IEEE.

关键词： Wireless local area networks (WLAN)

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Loosely-vs. Tightly-coupled incorporation of nonlinear measurements in tracking applications 62

Loosely-vs. Tightly-coupled incorporation of nonlinear measu...

引用

62nd Israel Annual conference on Aerospace Sciences, IACAS 2023

作者： Hackmon, Shlomi Sigalov, Daniel Rafael-Advanced Defense Systems Israel

We consider the problem of tracking a single target using a set of sensors with nonlinear measurement models. Two options for utilizing the measurements are addressed. First, is the direct utilization of raw sensor data using a nonlinear fil-Ter such as the Extended Kalman filter (EKF). The second option is based on the conversion of the set of nonlinear observations to a single cartesian measurement and subsequent application of a linear Kalman filter or related algorithm. Nat-urally, both approaches involve approximations. In the former case, there is the inherent approximation of the EKF mechanism. The nonlinearities in the measure-ment model are tackled by the means of linearization about the latest estimate. On the contrary, in the second approach a nonlinear optimization problem needs to be solved and, typically, it can be solved only approximately. Moveover, usually, the measurement noise covariance can not be analytically transformed through a nonlinear function. Thus, in practical cases, it is not a-priori clear which of the two approaches is preferable. We borrow the terminology from the navigation domain, and refer to direct processing of the raw sensor measurements by a nonlinear algo-rithm (mostly EKF) as the tighly coupled (TC) architecture. On the contrary, the setup in which a linear filter is preceded by a nonlinear transformation of the raw data into an effective Cartesian measurement, will be called loosely coupled (LC). In this work we compare, through a numerical study, the TC and LC approaches in a few multisensor scenarios involving nonlinear measurement models, and identify whether one of the approaches should be preferred over its counterpart. © IACAS 2023. All rights reserved.

关键词： Extended Kalman filters

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TinyTracker: Ultra-Fast and Ultra-Low-Power Edge Vision In-sensor for Gaze Estimation

TinyTracker: Ultra-Fast and Ultra-Low-Power Edge Vision In-S...

引用

IEEE sensors conference

作者： Bonazzi, Pietro Rueegg, Thomas Bian, Sizhen Li, Yawei Magno, Michele Swiss Fed Inst Technol Ctr Project Based Learning Zurich Switzerland

ISBN: (纸本)9798350303872

Intelligent edge vision tasks encounter the critical challenge of ensuring power and latency efficiency due to the typically heavy computational load they impose on edge platforms. This work leverages one of the first "Artificial Intelligence (AI) in sensor" vision platforms, IMx500 by Sony, to achieve ultra-fast and ultra-low-power end-to-end edge vision applications. We evaluate the IMx500 and compare it to other edge platforms, such as the Google Coral Dev Micro and Sony Spresense, by exploring gaze estimation as a case study. We propose TinyTracker, a highly efficient, fully quantized model for 2D gaze estimation designed to maximize the performance of the edge vision systems considered in this study. TinyTracker achieves a 41x size reduction (similar to 600Kb) compared to iTracker [1] without significant loss in gaze estimation accuracy (maximum of 0.16 cm when fully quantized). TinyTracker's deployment on the Sony IMx500 vision sensor results in end-to-end latency of around 19ms. The camera takes around 17.9ms to read, process and transmit the pixels to the accelerator. The inference time of the network is 0.86ms with an additional 0.24 ms for retrieving the results from the sensor. The overall energy consumption of the end-to-end system is 4.9 mJ, including 0.06 mJ for inference. The end-to-end study shows that IMx500 is 1.7x faster than Coral Micro (19ms vs 34.4ms) and 7x more power efficient (4.9mJ VS 34.2mJ).

关键词： Energy utilization

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Software and Hardware Cooperative Implementation of the Rafflesia Optimization Algorithm 5th

Software and Hardware Cooperative Implementation of the R...

引用

5th International conference on Smart Vehicular Technology, Transportation, Communication and applications, VTCA 2022

作者： Fu, Zonglin Pan, Jeng-Shyang Guo, Yundong Snášel, Václav College of Computer Science and Engineering Shandong University of Science and Technology Qingdao266590 China Faculty of Electrical Engineering and Computer Science VŠB-Technical University of Ostrava Ostrava70032 Czech Republic

ISBN: (纸本)9789819908479

With the development of edge technology in the fields of transportation, wireless sensor networks, and the internet of things, more and more intelligent optimization algorithms are implemented in hardware structures. The Rafflesia optimization algorithm (ROA) is a novel intelligent optimization algorithm proposed recently. To observe its performance on hardware, this paper implements the ROA algorithm in a cooperative way of software and hardware, referred to as the FROA algorithm. To convenient testing and accelerated computing, the initialization module, fitness module, and update module of the FROA algorithm are deployed on the advanced RISC machine (ARM) platform and the field programmable gate array (FPGA) platform, respectively. In the experimental part, we test the FROA algorithm on nine different benchmark functions. The results are compared with those implemented in software. The experimental results demonstrate the effectiveness and superiority of the FROA algorithm. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Wireless sensor networks

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Research on a Bipolar Structure Voltage sensor Based on Capacitive Coupling Principle

Research on a Bipolar Structure Voltage Sensor Based on Capa...

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advanced Electrical and Energy systems (AEES), International conference on

作者： Bofeng Luo Shijie Li Tianyu Hou Siyu Hu Chuyan Zhang China Southern Power Grid Company Limited Guangzhou China China University of Geosciences Beijing Beijing China

ISBN: (数字)9798331517724

ISBN: (纸本)9798331517731

This paper investigates a bipolar structure voltage sensor based on the principle of capacitive coupling. The non-contact voltage sensor, based on electric field coupling, offers advantages such as simple structure, excellent insulation performance, and fast response. A bipolar differential electrode structure was designed for the sensor, and by reducing the internal resistance of the voltage follower circuit, the measurement stability and accuracy were improved. Simulation and experimental results indicate that the sensor can effectively detect electric field variations in a uniformly distributed field and exhibits good linear response in both low-frequency and power-frequency signal measurements, showing great potential for future applications.

关键词： Couplings Resistance Voltage measurement Power measurement Accuracy Power system stability Frequency measurement Electrical resistance measurement Electric fields Transient analysis

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MZ Core: An Enhanced Matrix Acceleration Engine for HPC/ AI applications 24

MZ Core: An Enhanced Matrix Acceleration Engine for HPC/ AI ...

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24th IEEE International conference on High Performance Computing and Communications, 8th IEEE International conference on Data Science and systems, 20th IEEE International conference on Smart City and 8th IEEE International conference on Dependability in sensor, Cloud and Big Data systems and Application, HPCC/DSS/SmartCity/DependSys 2022

作者： Cao, Yasong Wen, Mei Shen, Junzhong Liu, Sheng Wang, Zhi Tang, Minjin Fang, Yahao Yang, Jianchao Yang, Renyu Kang, Yuhan Fei, Jiawei College of Computer National University of Defense Technology Changsha China Hunan Normal University Software Engineering Changsha China

ISBN: (纸本)9798350319934

The convergence of High-Performance Computing (HPC) and Artificial Intelligence (AI) has become a promising trend. Due to the different computation patterns of HPC and AI applications, it's challenging to design an appropriate architecture to balance their demand. To address this, we propose Matrix Zone (MZ), an enhanced Systolic Array-based matrix engine that accelerates General Matrix Multiplication (GEMM) for both HPC and AI applications. We develop a semi-memory hierarchy to reduce on-chip area consumption and a data stitching method to support multi-precision floating-point processing efficiently. We demonstrate that MZ improves performance for both HPC and AI applications significantly. For AI-GEMM tasks, the performance of MZ is 1.80x (FP32), 15.11x (FPI6), and 3.48x (FPI6-FP32) of the TPU-like model on average, respectively. MZ's performance is more than 10.29x (FP32) and 26.37x (FPI6) of the HPC core in Convolutional (CONV) layers on average, and it is 4.66x (FP32) and 20.75x (FPI6) in Fully Connected (FC) layers on average. For HPC-GEMM tasks, the HPC core + MZ is 6.28x and 1.15x faster than that of the HPC core only and the MZ only on average, respectively. The area of MZ is 2.052 square millimeters. © 2022 IEEE.

关键词： Systolic arrays

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GelPixel: A Single-Pixel-Based Tactile sensor

GelPixel: A Single-Pixel-Based Tactile Sensor

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2023 IEEE International conference on Real-Time Computing and Robotics, RCAR 2023

作者： Huang, Binhua Li, xiaoyu Sumari, Putra Ye, Chaoxiang Zhou, Zhenning Yin, Meng Yi, Zhengkun Wu, xinyu Shenzhen Institute of Artificial Intelligence and Robotics for Society Siat Branch Shenzhen518055 China Universiti Sains Malaysia School of Computer Science 11800 Malaysia Chinese Academy of Sciences Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Shenzhen518055 China

ISBN: (纸本)9798350327182

In this paper, we present the design and development of a novel optical tactile sensor that uses a single-pixel color light-to-frequency converter (TCS3200) and spectral decoding to recognize presses at different positions. This innovative approach overcomes the limitations associated with camera-based sensors, such as increased manufacturing costs and shape restrictions, enabling potential integration as a skin-like layer over a robot's body. Our proposed direct light propagation structure demonstrates enhanced sensitivity and a broader measuring range compared to traditional reflection structures. Using Ecoflex as the elastomer, the sensor's design incorporates a three-layer structure, including an LED layer, an elastomer layer, and a color sensor layer. Experimental results demonstrate that the proposed sensor performs well in localization tasks, achieving over 95% accuracy using multi-target regression for rendering poked positions. This study demonstrates the potential of single-pixel-based tactile sensors in various applications and provides a foundation for further exploration in this area. © 2023 IEEE.

关键词： Tactile sensors

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RF Sensing -enabled Interference Mitigation for Wi-Fi-based IoT systems: A Deep Learning Approach

RF Sensing -enabled Interference Mitigation for Wi-Fi-based ...

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IEEE conference on Communications and Network Security (CNS)

作者： Lin, ChunChih Li, Gen Zhang, xiaonan Guo, Linke Clemson Univ Holcombe Dept Elect & Comp Engn Clemson SC 29634 USA Florida State Univ Dept Comp Sci Tallahassee FL 32306 USA

ISBN: (纸本)9798350375978;9798350375961

The proliferation of the Internet of Things (IoT) over the 2.4GHz has transformed the way people interact with the world in their daily lives. For emerging applications requiring diverse types of data, using IoT devices from different protocols, such as Wi-Fi, Bluetooth, and ZigBee, for data collection will help fulfill designated objectives. Hence, the increasing use of these IoT devices will form a heterogeneous environment with inevitable wireless coexistence. Due to the dynamic IoT environment, the wireless transmission among heterogeneous IoT devices becomes unknown and notoriously hard to manage, where the network performance is always compromised. This paper leverages the RF sensing information to develop a deep learning-based framework for mitigating the cross-technology interference of the Wi-Fi-based IoT system. Each IoT device can provide detailed Channel State Information (CSI) of the transmission link, by which the gateway uses Generative Adversarial Networks (GAN) for building a detailed environmental RF map. Then, we propose a CSI -inspired gateway topology management strategy to find the optimal gateway location, anticipating reaching the highest network throughput. To enhance the efficiency of the proposed scheme, we also adopt the advanced differentiable augmentation approach to reduce the training data size for gateway deployment. Extensive experimental results have demonstrated both the feasibility and efficiency of our design.

关键词： Wireless local area networks (WLAN)

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Calibration of a Robot's Tool Center Point Using a Laser Displacement sensor

Calibration of a Robot's Tool Center Point Using a Laser Dis...

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2022 International conference on advanced Robotics and Intelligent systems, ARIS 2022

作者： Lin, Chih-Jer Wang, Hsing-Cheng Graduated Institute of Automation Technology National Taipei University of Technology Taiwan

ISBN: (数字)9781665487184

ISBN: (纸本)9781665487184

The conventional tool center point calibration (TCP) method requires the operator to set the actual position of the tool center point by eye. To address this lengthy workflow and low accuracy while improving accuracy and efficiency for time-saving and non-contact calibration, this paper proposes an enhanced automatic TCP calibration method based on a laser displacement sensor and implemented on a cooperative robot with six degrees of freedom. During the calibration process, the robot arm will move a given distance along the x and Y axes and collect the information when the tool passes through the laser during the process to calculate the deflection of the tool, and then continue to move a given distance along the x and Y axes for the second height calibration. After the deflection angle is calculated and calibrated by triangulation, the deflection calibration is completed and the third x and Y axis displacement is performed to find out the exact position of the tool on the x and Y axes. Finally, the tool is moved to a position higher than the laser, and the laser is triggered by moving downward to obtain information to complete the whole experimental process and get the calibrated tool center position. The whole calibration method is firstly verified in the virtual simulation environment and then implemented on the actual cooperative robot. The results of the proposed TCP calibration method can achieve a positioning accuracy of about 0.07 mm, a positioning accuracy of about 0.18 degrees, a positioning repeatability of ± 0.083 mm, and a positioning repeatability of less than ± pm 0.17 degrees. This result meets the requirements of TCP calibration, but also achieves the purpose of simple, economical and time-saving, and it takes only 60 seconds to complete the whole calibration process. © 2022 IEEE.

关键词： Calibration

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A Secure IoT Framework for Remote Health Monitoring Using Fog Computing 5

A Secure IoT Framework for Remote Health Monitoring Using Fo...

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5th International conference on Intelligent Computing, Communication, Networking and Services, ICCNS 2024

作者： Harasees, Alaa Al-Ahmad, Bilal Alsobeh, Anas Abuhussein, Abdullah The University of Jordan Computer Information Systems Jordan Saint Cloud State University Computer Science and Information Technology Minnesota United States Southern Illinois University Carbondale Infortmation Technology CarbondaleIL United States

ISBN: (纸本)9798350354690

This paper presents a secure IoT framework for remote health monitoring using fog computing, tailored for the Jordanian healthcare context. The proposed Remote Health System (RHS) addresses critical challenges in healthcare IoT applications, including latency, security, and bandwidth consumption. By integrating IoT wireless sensor networks with fog and cloud computing, our framework overcomes limitations prevalent in cloud-only solutions. The architecture leverages fog computing layers to provide local storage, real-time data processing, and preliminary analysis, acting as decision-makers and security checkpoints before relaying data to the cloud for complex functions. We incorporate advanced threat detection mechanisms and secure protocols to protect sensitive health data throughout its lifecycle. The performance and security of the proposed framework were evaluated using FogNetSim++ and OMNeT++ 4.6 simulations. The paper uses fog security and ZigBee communication protocols which implemented in the proposed framework. Results demonstrate the system's ability to reduce latency, energy consumption, and end-to-end delay while maintaining high security levels. CPU usage, memory consumption, and end-to-end delay were analyzed for various node configurations. The framework shows promise in enhancing healthcare delivery in Jordan, particularly in remote and underserved areas, by leveraging the strengths of IoT, fog computing, and cloud infrastructure. This work contributes to the evolving landscape of e-health systems in Jordan, by proposing a scalable, efficient, and secure solution that addresses the unique challenges of the country's healthcare sector. © 2024 IEEE.

关键词： Zigbee

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