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检索条件"任意字段=International Conference on Sensor Technologies and Applications, SensorComm"

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Numerical Study of Sensitivity Enhancement in Optical Waveguide sensor Due to Core Diameter 22nd

Numerical Study of Sensitivity Enhancement in Optical Wavegu...

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22nd Asia Simulation conference, AsiaSim 2023

作者： Marippan, Thienesh Saris, Nur Najahatul Huda Mohd Hanafi, Ahmad Izzat Mohd Razali, Nazirah Faculty of Electrical Engineering Universiti Teknologi Malaysia Johor Skudai81310 Malaysia Malaysia-Japan International Institute of Technology Universiti Teknologi Malaysia Kuala Lumpur54100 Malaysia

ISBN: (纸本)9789819972425

The need for sensing technology has arisen as a result of the growing environmental concern over microplastic pollution in water systems. In this work, a potential microplastic sensor based on an optical planar doped polymer waveguide was theoretically investigated by using Wave Optics Module-COMSOL Multiphysics® software over a range of 2 μm to 16 μm waveguide core diameters. The microplastic refractive index of the analytes employed in this research ranged from 1.48 RIU to 1.50 RIU reflecting the microplastic refractive index. The results revealed that a 2 μm core diameter of the waveguide sensor achieved the best sensitivity value of 5.12 × 10–5 at fixed cladding depth and wavelength of 0 μm and 617 nm, respectively. The simulation work offers useful information for designing a potential waveguide for real world applications to detect microplastics in water. This study is believed to contribute towards the development of cutting-edge sensing technologies through the optimized optical waveguide sensor design, which shows promise in addressing the serious problem of microplastic pollution in water systems. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Multiphysics

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Rotation Scheme Based Power Consumption Analysis for Wireless sensor Network 1

Rotation Scheme Based Power Consumption Analysis for Wireles...

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1st IEEE international conference on Smart technologies and Systems for Next Generation Computing, ICSTSN 2022

作者： Julie Therese, M. Devi, A. Balaji, B. Senthilnayaki, B. Dharanyadevi, P. Sri Manakula Vinayagar Engineering College Department of Ece Puducherry India Ifet College of Engineering Department of Ece Villupuram India Ifet College of Engineering Department of Eee Villupuram India Anna University College of Engineering Dept of Information Science and Technology Chennai India Pondicherry Technological University Department of Cse Puducherry India

ISBN: (纸本)9781665421119

In wireless sensor network (WSN) application, one of the most important problems to be considered is power consumption. As a result, a number of methodologies or methods for analyzing the power consumption of the application have been presented. These methodologies may aid in the prediction of the lifespan of WSNs, the providing of suggestions to application developers, and the optimization of the amount of energy utilized by WSN applications. All of the sensors in wireless sensor nodes are rechargeable batteries devices with a limited amount of battery power available. It will be difficult to replace every power supply battery available in the network on an individual basis after deploying of sensor nodes. To sort out these issues, an efficient analyzing technique for analyzing the power consumption of WSN is proposed. In this research work, a prototype model with a simulation model is presented. The proposed research work may lower the amount of power used by each sensor node, while also increasing the life of sensors by shutting down certain of their components in order to achieve higher energy savings and longer life. It is necessary to do an analysis of the power usage of each sensor node before using this power management strategy. As a result of this, the proposed method analyzes the WSN power consumption in real time manner. © 2022 IEEE.

关键词： Electric power utilization

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2nd international conference on Cybersecurity and Evolutionary Data Engineering, ICCEDE 2022

2nd International Conference on Cybersecurity and Evolutiona...

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2nd international conference on Cybersecurity and Evolutionary Data Engineering, ICCEDE 2022

ISBN: (纸本)9789819950799

The proceedings contain 31 papers. The special focus in this conference is on international conference on Cybersecurity and Evolutionary Data Engineering. The topics include: Analysis of Multimodal Biometric System Based on ECG Biometrics;performance Analysis of Nature Inspired Optimization Based Watermarking Schemes;A Review of Ensemble Methods Used in AI applications;stress Detection Based on Multimodal Data in a Classroom Environment;comparative Study of Different Generations of Mobile Network;A Novel Framework for VM Selection and Placement in Cloud Environment;quad Clustering Analysis and Energy Efficiency Evaluation in Wireless sensor Networks;artificial Intelligence in Gaming;analysis of Pulmonary Fibrosis Progression Using Machine Learning Approaches;cyber Bullying: The Growing Menace in Cyber Space with Its Challenges and Solutions;Lung Conditions Prognosis Using CNN Model;stock Trend Prediction Using Candlestick Pattern;motion Based Real-Time Siamese Multiple Object Tracker Model;Design and Development of IOT & AI Enabled Smart Entrance Monitoring Device;sunlight-based Framework: An Approach for Energy Efficiency in IoT Systems;metaverse technologies and applications: A Study;body sensor Networking: A Case Study of Heart Pulse Detection and Alert System;brand Sentiment Analytics Using Flume;The $$\lambda $$ NF Problem;the Indian Search Algorithm;Hybrid Feature Extraction for Analysis of Network System Security—IDS;COVID-19’s Influence on Buyers and Businesses;Exploring Textural Behavior of Novel Coronavirus (SARS–CoV-2) Through UV Microscope Images;stranger Trust Architecture: An Advancement to Zero Trust Architecture;Genetic Algorithm Optimized SVM for DoS Attack Detection in VANETs;digital and IoT Forensic: Recent Trends, Methods and Challenges.

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CHARACTERIZATION AND RELIABILITY ANALYSIS OF DIRECT-WRITE ADDITIVELY PRINTED FLEXIBLE HUMIDITY sensor WITH SUPER CAPACITIVE MATERIAL FOR WEARABLE ASTRONAUT sensor IN HARSH ENVIRONMENTS

CHARACTERIZATION AND RELIABILITY ANALYSIS OF DIRECT-WRITE AD...

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ASME international Technical conference and Exhibition on Packaging and Integration of Electronic and Photonic Microsystems (InterPACK)

作者： Lall, Pradeep Jang, Hyesoo Hill, Curtis Auburn Univ Dept Mech Engn NSF CAVE3 Elect Res Ctr Auburn AL 36849 USA QuaniTech Inc Jacobs Space Explorat Grou ESSCA Contract NASA MSFC Huntsville AL 35808 USA

ISBN: (纸本)9780791886557

Using additive technologies to fabricate printed circuit boards eliminates the need for expensive manufacturing - software-based design and production permit production flexibility, as well as quicker tool modifications and design evolution. In addition, additive printing techniques can be applied to various surfaces and shapes. This adaptability to a wide range of applications enables the construction of novel applications, such as biosensors, by designers. Several previous studies have focused on developing additively printed humidity sensors because of their potential for flexibility and integration. Flexure in the operating environment has been known to cause performance degradation in prior generations of temperature and humidity sensor technologies. This study uses the direct write printing method with a nScrypt printer to print the humidity sensor. Characterization of the sensor has been done by studying the process-performance interactions of temperature coefficient to resistance and sensitivity to humidity. sensor accuracy, hysteresis, repeatability, linearity, and stability have been quantified concerning printing recipe and encapsulation. A folding reliability test has been conducted to assess the viability of the sensor in operation to mimic real-life use conditions. The cyclic folding motions are administered every 13 seconds with the same folding diameter and travel distance on every three samples, with single trace and multi-trace sensing materials and trace with polyimide encapsulation. Furthermore, chemo-electrical measurement with cyclic voltammetry method has been conducted to assess water possession under high humidity conditions. It is found that encapsulation might help improve the humid and mechanical reliability of the additively printed humidity sensor.

关键词： Additive Fabrication Printed Electronics Substrate Materials sensors and Actuators Biosystems and Biomedicine Materials Interactions and Characterization Reliability of Devices Systems Reliability Modelling and Simulation Reliability Test Methods

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Development of a flexible sensor based on fiber Bragg grating technology for simultaneous respiratory and heartbeat measurements

Development of a flexible sensor based on fiber Bragg gratin...

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2023 IEEE international Symposium on Medical Measurements and applications, MeMeA 2023

作者： Presti, Daniela Lo Massaroni, Carlo Bianchi, Daniele Caponero, Michele Gizzi, Alessio Schena, Emiliano Università Campus Bio-Medico di Roma Dept. of Engineering Rome Italy Micro and Nanostructure Laboratory Enea Research Center of Frascati RM Frascati Italy

ISBN: (纸本)9781665493840

In the last decades, the growing interest in the use of wearables has fostered the exploitation of innovative technologies in the development of highly performant sensing solutions for monitoring human health. Several sensing elements have been proposed to instrument wearable items and textiles, making them able to detect physiological parameters, including respiratory and cardiac *** work presents a wearable sensor based on fiber Bragg grating (FBG) technology with a novel design to simultaneously measure respiration and heartbeat activities with improvements in optical fiber robustness. The proposed sensor prototype consists of a flexible matrix with an optical fiber inscribed with a 5 mm-length FBG sensing element. Only a small portion of the optical fiber (i.e., 10 mm) is integrated into the polymer matrix. In this way, the FBG is protected by the matrix and can be stretched further without any damage. A metrological characterization of the developed sensor was proposed to better investigate any changes in response to strain and temperature of the encapsulated sensing element compared to a bare FBG. Then, a preliminary assessment of the performance of the flexible sensor in monitoring respiration and heartbeat was carried out on a healthy subject. The flexible sensor was equipped with an elastic band to be fastened around the thorax. The preliminary results of this test foster future investigations to assess the capability of the proposed wearable system in monitoring cardiorespiratory activity considering different measuring sites (e.g., thorax and neck) and under various body positions (e.g., supine and standing). © 2023 IEEE.

关键词： Fiber Bragg gratings

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Robust Methodology Design to Detect Anomalies Over Wireless sensor Networks Using Predictive Learning Strategy 9

Robust Methodology Design to Detect Anomalies Over Wireless ...

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9th international conference on Science, Technology, Engineering and Mathematics, ICONSTEM 2024

作者： Rajeshwari, R. Ajai Athithya, V. Gowthamkumar, M. Manigandamurthi, R. Sivanesh, B. Nivetha, R. S. A. Engineering College Department of Master of Computer Applications Chennai India

ISBN: (数字)9798350365092

ISBN: (纸本)9798350365092

In the realm of intrusion detection, the effective utilization of machine learning algorithms is paramount to safeguarding network security. Using the NSL-KDD dataset, this study investigates how well different feature extraction approaches and prediction models perform intrusion detection. We looked at a variety of feature extraction methods such ShuffleNet, CNN, PCA, and Autoencoder, as well as a variety of prediction models like LightGBM, Random Forest (RF), SVM, and Logistic Regression. The F1-score, recall, accuracy, and precision are some of the critical performance indicators used to evaluate each approach. The findings demonstrate that ShuffleNet is effective for feature extraction, especially when used in conjunction with LightGBM, which improves its testing accuracy to 0.92. Furthermore, the predictive models exhibit varying degrees of effectiveness, with LightGBM demonstrating superior performance compared to other models, achieving a testing accuracy of 0.92. Additionally, the hybrid model consisting of ShuffleNet and LightGBM achieves a remarkable testing accuracy of 0.94, highlighting the potential of integrating feature extraction and predictive modeling techniques to enhance intrusion detection systems and bolster network security against cyber threats. © 2024 IEEE.

关键词： Feature extraction

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Evaluation of the Reliability of a LiDAR sensor Through a Geometric Model in applications to Autonomous Driving 4th

Evaluation of the Reliability of a LiDAR Sensor Through a Ge...

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4th international conference on Advances in Emerging Trends and technologies, ICAETT 2022

作者： Zea, Danny J. Toapanta, Alex P. Minaya, César A. Paspuel, Carlos A. Moreno, Irlanda E. Instituto Tecnológico Universitario Rumiñahui Sangolquí Ecuador Universidad Politécnica de Madrid Madrid Spain

ISBN: (纸本)9783031259418

In recent years, there has been a drastic increase in research related to autonomous driving applications, getting autonomous vehicles to circulate and engage in vehicular traffic. However, there are still difficulties in achieving reliable autonomous driving. This is due to the unexpected actions of the entities involved in the autonomous vehicle’s journey, the lack of interaction of the vehicle with the environment, the reliability of the sensors in capturing the environment, among others. These problems have already caused several accidents involving autonomous vehicles. In order to overcome these drawbacks, researchers rely on 3D simulation software with modules dedicated to autonomous driving applications with the aim of shortening research times and especially the validation of dangerous scenarios. The research in this article proposes the simulation of a vehicle that performs automatic guidance while avoiding obstacles along its path. The proposal is to evaluate the reliability of the angle and distance of an obstacle detected by a LiDAR sensor. These two variables will also be obtained and compared by means of a geometric model that involves the additional implementation of a GPS sensor and a Compass sensor over the LiDAR sensor. Automatic vehicle guidance is achieved through the implementation of a Camera sensor that captures images that are processed to track the yellow line of the road. The results obtained can be used to plan methods and techniques for more accurate and reliable maps. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Autonomous vehicles

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An Enhanced Security Algorithm for Wireless sensor Networks

An Enhanced Security Algorithm for Wireless Sensor Networks

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2023 IEEE international conference on Electrical, Computer and Energy technologies, ICECET 2023

作者： Sebothoma, Puseletso Mathonsi, Topside E. Tshwane University of Technology Department of Information Technology Pretoria South Africa

ISBN: (纸本)9798350327816

In recent years, the significance of Wireless sensor Networks (WSNs) has increased due to their cost-effective deployment and widespread internet accessibility. WSNs have found applications in various domains such as military, aviation, healthcare, home automation, transportation, fitness, and forestry. However, the finite energy source of these sensors necessitates the replacement of depleted energy. Moreover, WSNs face numerous challenges including high bandwidth requirements, power consumption, Quality of Service (QoS) delivery, data processing and compression techniques, and cross-layer design. Denial-of-Sleep (DoSL) attacks further exacerbate these challenges. These attacks exploit the sleep mode, which is crucial for minimizing power consumption in sensor nodes. By flooding the targeted nodes with unnecessary fake packets, DoSL attacks prevent them from entering sleep mode, ultimately depleting their power supply and adversely affecting network performance and lifespan. Hence, practical and effective solutions are necessary to tackle these issues. This paper addresses the emerging problems and challenges related to security in WSNs. The proposed solution, namely the DSD-RSA algorithm, integrates existing models such as the S-MAC protocol, AES algorithm, and RSA algorithm. DSD-RSA aims to minimize power consumption and end-to-end delay while maximizing network throughput in WSNs. To evaluate the effectiveness of DSD-RSA, we conducted a comparative analysis with three traditional algorithms, namely WSN-FAHN, GA-DoSLD, and GSHMAC, using the Network Simulator-2 (NS-2) tool. Computer simulation results demonstrated that the proposed DSD-RSA algorithm outperformed the traditional algorithms in terms of average throughput, average delay, and energy consumption. Specifically, the DSD-RSA algorithm achieved an average throughput of 95%, an average end-to-end delay of 19%, and an average energy consumption of 30%. In contrast, WSN-FAHN, GA-DoSLD, and GSHMAC algorithms y

关键词： Denial of Sleep attacks DSD-RSA RSA Cryptography WSN

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Model-Free sensor Fusion for Redundant Measurements Using Sliding Window Variance 22

Model-Free Sensor Fusion for Redundant Measurements Using Sl...

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22nd international conference on Control, Automation and Systems (ICCAS)

作者： Makinen, P. Mustalahti, P. Launis, S. Mattila, J. Tampere Univ Automat Technol & Mech Engn Tampere Finland Sandv Min & Construct Oy Rock Technol & Drilling Tampere Finland

ISBN: (纸本)9788993215243

In this paper, a model-free data fusion method for combining redundant sensor data is presented. The objective is to maintain a reliable tool center point pose measurement of a long-reach robotic manipulator using a visual sensor system with multiple cameras. The fusion method is based on weighted averaging. The weight parameter for each variable is computed using the sliding window variance with N latest observations. After each sliding window, the window length N is updated, and simple transition smoothing is included. For experimental validation, two sets of pose trajectory data from redundant visual sensors were obtained: 1) using a camera located near the tip of a long-reach manipulator running a simultaneous localization and mapping (SLAM) algorithm and 2) marker-based tracking with cameras located near the base of the manipulator. For pose tracking, a fiducial marker was attached near the SLAM camera. The proposed methodology was examined using a real-time measurement setup and offline data analysis using the recorded data. The results demonstrate that the proposed system can increase the overall robustness and fault tolerance of the system, which are desired features for future autonomous field robotic machines.

关键词： sensor Fusion Machine Vision sensor Systems and applications

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A driver's dangerous driving behavior detection method based on the YOLOV5-CA network 2

A driver's dangerous driving behavior detection method based...

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2nd international conference on Sensing, Measurement, Communication and Internet of Things technologies, SMC-IoT 2023

作者： Wen, Yonghui Shang, Wenli Guangzhou University School of Electronic and Communication Engineering Guangzhou China Key Laboratory of On-Chip Communication and Sensor Chip of Guangdong Higher Education Institutes China

ISBN: (纸本)9798350373257

The current fatigue driving detection algorithm based on deep learning image recognition has been widely researched and applied, but it faces issues of suboptimal detection performance, singular detection behavior, and ambiguous detection outcomes. To address these problems, this paper proposes a dangerous driving behavior detection method based on the YOLOv5-CA network. Firstly, to address the suboptimal detection performance, an attention mechanism CA method is proposed to enhance the feature extraction capability of targets. Secondly, to address the singular detection behavior, detection of four common dangerous driving behaviors is designed, including eye closure, yawn, glancing left and right, and making phone calls. Furthermore, to further enhance the practicality of the algorithm, an interface tailored to the algorithm is designed, and the logic of traffic demerit points is introduced. The experimental results show that the accuracy of this model in dangerous driving behavior detection reaches 90.8%, and the comprehensive accuracy of classification reaches 92.6%. This verifies the feasibility and effectiveness of the model in practical applications. © 2023 IEEE.

关键词： Feature extraction

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