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IEEE International conference on Robotics and Automation (ICRA)

作者： Park, Sungwoo Oh, Sang-Rok Hwang, Donghyun KIST Ctr Robot Res Seoul 02792 South Korea Korea Univ Sch Elect Engn Seoul 02841 South Korea

ISBN: (纸本)9798350323658

We develop a novel hall-effect-based six-axis force/torque (F/T) tactile sensor integrated into the fingertip of robotic hands. When the robotic hands performs the grasping tasks in an unstructured environment, the visual information plays a main role in sensing the external properties of the objects. However, the various intrinsic properties of the objects such as softness, roughness, mass distribution, and weight cannot be measured properly only with the visual information. To detect the various force information in performing diverse tasks, we aim to implement the six-axis F/T fingertip tactile sensor with hall-effect-based principle. The experimental results demonstrate that the proposed sensor can measure the six-axis F/T with average errors of about 3.3 %. In addition, it is observed that the effect of stray field can be shielded by applying a soft magnetic shielding film to the sensor.

关键词： Robotic arms

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An electromagnetic indirect-driving scanning mirror for wide-field coaxial LiDAR applications 24

An electromagnetic indirect-driving scanning mirror for wide...

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2025 conference on MOEMS and Miniaturized systems

作者： Li, Shuangliang Wang, Di Song, Dezhen Zou, Jun Texas A&M Univ Dept Elect & Comp Engn College Stn TX 77843 USA Texas A&M Univ Dept Comp Sci & Engn College Stn TX 77843 USA

ISBN: (数字)9781510685130

ISBN: (纸本)9781510685123;9781510685130

This paper reports an electromagnetic indirect-driving scanning mirror with an enlarged mirror plate (17 mm x 17 mm) supported by high-strength polymer hinges for wide-field coaxial LiDAR (Light Detection and Ranging) applications. An indirect-driving mechanism was developed to achieve large tilting angle through mechanical amplification, while maintaining a relatively high resonance frequency of the enlarged mirror plate. A prototype mirror was designed, fabricated, and tested. A Hall scan position sensor was integrated to monitor the pose of the mirror in real time. The testing results show a coupled resonance frequency of 54.9 Hz with an optical tilting angle of +/- 60 degrees, corresponding to a field of view (FoV) of 120 degrees. A wide-field coaxial LiDAR setup was also built based on the indirect-driving scanning mirror, and 2D imaging was demonstrated.

关键词： Micro scanning mirrors LiDAR mechanical coupling indirect driving scan position sensing

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High Sensitivity Terahertz Biosensor Based on Graphene/Methylammonium Lead Halide Metasurface with Machine Learning-Enhanced Pathogen Detection

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PLASMONICS 2024年 1-22页

作者： Wekalao, Jacob Siddharthan, Niranjana Shibu, Soman Murthy, Garapati Satyanarayana Karthikeyan, Kandaswamy Vasudevan Mallan, Srinivasan Ganesan, Kalpanadevi Sekar, Vijayalakshmi Rashed, Ahmed Nabih Zaki Univ Sci & Technol China Dept Opt & Opt Engn Hefei 230026 Peoples R China Rajalakshmi Inst Technol Dept Artificial Intelligence & Data Sci Chennai Tamilnadu India Panimalar Engn Coll Dept ECE Chennai Tamilnadu India Aditya Univ Dept CSE Surampalem Andhra Pradesh India Sathyabama Inst Sci & Technol Dept ECE Chennai Tamil Nadu India Bannari Amman Inst Technol Dept EEE Erode Tamilnadu India KRamakrishnan Coll Engn Dept ECE Trichy Tamilnadu India Sona Coll Technol Dept ECE Salem Tamilnadu India Menoufia Univ Fac Elect Engn Elect & Elect Commun Engn Dept Menoufia 32951 Egypt Saveetha Univ Saveetha Inst Med & Tech Sci Saveetha Sch Engn Dept VLSI Microelect Chennai Tamilnadu India

This investigation presents an advanced biosensing platform integrating a Methylammonium lead halide metasurfaces with a dual-resonator architecture for high-precision waterborne pathogen detection. The engineered design incorporates a square ring resonator coupled with a graphene-functionalized circular resonator, optimized through systematic parametric analysis to achieve maximum sensitivity and specificity. Comprehensive electromagnetic simulations were performed utilizing COMSOL Multiphysics to characterize the sensor's electromagnetic response across multiple parameters, including graphene chemical potential modulation, incident wave angle variation, and resonator geometric configurations. The platform exhibited exceptional sensitivity to bacterial concentration-induced refractive index variations, demonstrating quantitative performance metrics of 488 GHzRIU-1 sensitivity, 0.234 RIU detection limit, and a quality factor of 12. 914. Implementation of the xGBoost machine learning algorithm for sensor response optimization yielded optimal prediction accuracy (R2 = 1.000) across all investigated parameters within the terahertz regime. These quantitative findings demonstrate the potential for integration of this sensing platform into high-throughput water quality monitoring systems, with significant implications for environmental surveillance and public health infrastructure applications.

关键词： Pathogens sensor COMSOL Halide Metamaterials Graphene Photonic crystal

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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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The Bi-O edge sensor: from theory to practice 9

The Bi-O edge sensor: from theory to practice

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conference on Adaptive Optics systems Ix

作者： Verinaud, Christophe Heritier, Cedric Taissir Kasper, Markus Haffert, Sebastiaan Snik, Frans Doelman, David Carlotti, Alexis Engler, Byron Le Louarn, Miska Correia, Carlos Tallon, Michel European Southern Observ Garching Germany Lab Astrophys Marseille Marseille France Steward Observ Tucson AZ USA Leiden Observ Leiden Netherlands Inst Planetol & Astrophys Grenoble Grenoble France Univ Porto Porto Portugal Ctr Rech Astrophys Lyon Lyon France

ISBN: (纸本)9781510675186;9781510675179

Resolution and sensitivity of the wavefront sensor (WFS) are key requirements for extreme Adaptive Optics (xAO) applications. We present a new class of WFSs, the Bi-Orthogonal Foucault-knife-edge (Bi-O edge), that is directly inspired by the Foucault knife-edge test. The idea consists of using a beam-splitter producing two foci, each of which is sensed by an edge with an orthogonal direction to the other. We describe two implementation concepts. The first one, the tip-tilt modulated sharp Bi-O-edge, can be seen as a mild evolution of the Pyramid. The second one uses a smooth, gradual amplitude mask over a 'grey' zone on the edge (grey Bi-O edge). We analyze the increased gain in sensitivity and the super-resolution capability, we compare these properties to the Pyramid sensor and produce end-to-end simulations. An important advantage of the grey Bi-O edge is the static modulation which is well adapted for fast xAO systems. The grey edge consists of a rectangular zone on the edge of the same size as the modulation circle. We will discuss the manufacturability of loss-less grey Foucault-knife edges, and we develop a polarization-based technique for the Bi-O edge prototype for the ESO GHOST test bench.

关键词： Adaptive Optics Wave-front sensing Pyramid sensor Foucault-knife edge Extremely Large Telescope

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Modeling of Total Occupancy Curves with Integrated Single Parking Times as Input for Microscopic Traffic Simulation 18th

Modeling of Total Occupancy Curves with Integrated Single Pa...

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18th Scientific and Technical conference on Transport systems - Theory and Practice (TSTP)

作者： Kaiser, Alexander Schade, Joachim Zadek, Hartmut Inst Automat & Kommunikat Transport & Assistance Magdeburg Germany

ISBN: (纸本)9783031223587;9783031223594

This paper presents a novel approach for the preparation of real parking data for microscopic traffic simulation or similar applications. Against the backdrop of an incomplete database given from single parking spot sensors and manual countings on a few parking spaces in Munich, the data are cleaned and expanded by various methods, e.g. a neural network to forecast the total occupancy at each hour as well as an optimization model to generate the corresponding parking times of each car. This results in a list of realistic parking events for a certain location and day. The method is transferable to other use cases regarding off-street parking spaces, particularly with an incomplete and discontinuous detection of parking occupancy and times.

关键词： Parking occupancy Parking time Parking sensor Neural network Optimization model Microscopic traffic simulation

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Neural Network Technology of Mine Recognition Based on Data From Magnetic Field sensors 12

Neural Network Technology of Mine Recognition Based on Data ...

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

作者： Peleshchak, Roman Lytvyn, Vasyl Peleshchak, Ivan Voloshyn, Serhii Lviv Polytechnic National University Department of Information Systems and Networks Lviv79000 Ukraine

ISBN: (纸本)9798350358056

Mine detection is an ongoing and growing problem that affects many people around the world due to the enormous danger that mines pose to humans. Mine detection occurs using various methods that use active sensors, including ultra-wideband (UWB) radar. Although active landmine sensors are often used for performance reasons, they can cause unintended landmine detonations because they operate on transmitted and reflected electromagnetic signals. Another way to detect mines without detonating mechanisms is the use of passive detectors. In this article, an optimal neural network structure with Adam's optimization algorithm is developed for effective mine classification based on magnetic field sensor data. This approach made it possible to increase the accuracy of mine detection to 99.23 percent. © 2023 IEEE.

关键词： Adam's optimization algorithm data preprocessing data visualization deep neural network passive mine detection

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Energy Efficient Workflow Scheduling Algorithm for Latency-Sensitive applications using Cloud-Fog Collaboration 17

Energy Efficient Workflow Scheduling Algorithm for Latency-S...

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

作者： Shukla, Prashant Pandey, Sudhakar National Institute of Technology Department of Information Technology Chhattisgarh Raipur India

ISBN: (纸本)9798350307672

The objectives of most studies are aimed at employing fog computing (FC) as an effective support to cloud computing (CC) in order to monitor sensor data and their associated necessities via the rapid advancements in Internet of Things (IoT). FC is completely dedicated to IoT sensor systems and delivers CC based computing, networking, and storage services. The cloud-Fog Collaboration (CFC) Environment will be more suitable for real-time IoT data sensing and workflow applications where fast and reliable internet connectivity is available. Workflow Scheduling means efficiently assigning the interdependent tasks to available computing resources. The workflow scheduling techniques play a significant role in minimizing the latency in Heterogeneous Computing systems (HCS). In this paper, we present a novel Hybrid-metaheuristics Multi-objective based Workflow Scheduling Algorithm (HMWSA) by combining Harmony Search (HS) and Genetic Algorithm (GA) for optimizing workflow scheduling in heterogeneous CFC. The proposed minimization objective function takes into account goals like makespan, energy usage, and cost. To preserve the precedence relationship among tasks, a topologically sorted execution sequence is constructed. Extensive testing results show that our proposed approach yields substantially better cost-makespan trade-offs while significantly reducing energy consumption than other existing algorithms. © 2023 IEEE.

关键词： Multiobjective optimization

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Enhancing Battery Management systems with Machine Learning and 5G Connectivity beyond Maritime Transport Software Architectures 15

Enhancing Battery Management Systems with Machine Learning a...

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15th International conference on Communications, COMM 2024

作者： Paraschiv, Constantin-Laurentiu Tufeanu, Larisa Mihaela Vochin, Marius-Constantin POLITEHNICA Bucharest Faculty of Electronics Department of Telecommunications Bucharest Romania

ISBN: (纸本)9798350355956

The growing advancement in battery technology has revolutionized various domains and services, notably transportation and energy storage. This research focuses on improving battery management systems (BMS) for electric vehicles (EV) and hybrid vehicles (HEV) by leveraging advanced machine learning models and 5G connectivity. This study proposes an integrated software architecture designed for both industrial and road applications, aiming to optimize battery performance and safety by analyzing collected data and predicting the anomaly events by training Random Forest and Gradient Boosting machine learning (ML) models. Throughout the research, key battery performance parameters and their normal operating ranges, such as voltage, current, temperature, charge/discharge rates, internal Resistance and State of Charge (SoC) are analyzed, according to the official regulations and utilized in Python scripting. The Python script implemented simulates battery operations by updating sensor values and logging incidents with factors such as latency, jitter, and encryption time. The script trains and compares machine learning models to determine the most accurate one for anomaly detection. The final part of the script simulates battery performance under different connectivity modes (5G Non-Standalone (NSA) and 5G Standalone (SA)) to assess the impact on data transmission and real-time monitoring. Ultimately, obtained results demonstrate not only advanced, sustainable, mobility solutions by improving the safety and performance of Battery Management systems in electric and hybrid vehicles, but also the importance of leveraging cutting-edge technologies (such as ML) and connectivity (5G). © 2024 IEEE.

关键词： Hybrid vehicles

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Exploiting Self-Tunable RFID Chips for Wireless Sensing of Permittivity to Enable Passive Low-Cost Food-Quality Monitoring systems 13

Exploiting Self-Tunable RFID Chips for Wireless Sensing of P...

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13th IEEE International conference on RFID Technology and applications (IEEE RFID-TA)

作者： Piccinno, Francesco Naccarata, Federica Colella, Riccardo Chietera, Francesco P. Catarinucci, Luca Marrocco, Gaetano Univ Salento Dept Innovat Engn Lecce Italy Univ Roma Tor Vergata Dept Civil Engn & Comp Sci Engn Rome Italy Natl Res Council CNR Lecce Italy

ISBN: (纸本)9798350333534

Self-tunable RFID chips allow for dynamic adjustment of their susceptance to improve the conjugate complex matching with the tag antenna even when working conditions vary over time. By exploiting this feature, the chip can wirelessly provide digital information related to the varied boundary condition. In this work, a fully-passive sensor based on a self-tunable Axzon Magnus-S3 chip has been designed and tested to sense the variations in the dielectric constant of a substrate. To achieve this, a planar interdigitated capacitor was fabricated, characterized, and connected to a tag antenna that was designed to ensure a robust communication link during the chip susceptance excursions. The experimental results demonstrate the feasibility and effectiveness of the proposed approach, showing significant potential for a wide range of applications in the food industry and beyond.

关键词： RFID electrical permittivity self-tunable sensor tag balanced antenna real-time monitoring

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