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

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An Investigation on Energy Consumption in Wireless sensor Network 8

An Investigation on Energy Consumption in Wireless Sensor Ne...

引用

8th International conference on advanced Computing and Communication systems, ICACCS 2022

作者： Thiyagarajan, N. Shanmugasundaram, N. Sri Eshwar College of Engineering Dept. of Ece Coimbatore India

ISBN: (纸本)9781665408165

Wireless sensor Networks (WSNs) has gained undisputed importance in the past decade in wide range of applications. WSN consists of densely deployed sensor nodes to monitor the environment. The sensed and collected data is communicated to the end user via the sink node using multi-hop transmission. There are several constraints in the construction of a sensor node such as processing power, memory and battery capacity. When the sensor nodes spend energy in an inefficient manner, it will reduce the network lifetime (NL) and hence the components of sensor node and the protocols governing the network must be optimally designed to extend its lifetime by reducing energy consumption. Many investigators have done their work in identifying energy consumed by the various activities carried out in WSNs. A detailed study is required for complete analysis of energy consumed by various elements in the WSN for the development of efficient protocols. This paper summarizes the energy consumed in a WSN and provides an insight for further research in WSN. © 2022 IEEE.

关键词： Energy utilization

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Comparative Analysis of Human Hand Gesture Recognition in Real-Time Healthcare applications 1st

Comparative Analysis of Human Hand Gesture Recognition in Re...

引用

1st International conference on Expert Clouds and applications, ICOECA 2023

作者： Dhande, Archita Mantri, Shamla Pande, Himangi MIT World Peace University Pune India

ISBN: (纸本)9789819917440

There is strong evidence that people will be able to communicate with various sensor-based devices more effortlessly and intuitively thanks to future human–computer interfaces (HCI), creating a more human-like interaction. Human–computer interaction has advanced as a result, and new technologies have been created that allow humans to connect with computers in increasingly intuitive and natural ways. Computer systems that use these technologies exhibit improved efficiency, speed, power, and realism. Real-time gesture interpretation is utilized by a vision-based system to modify items in a medical data visualization environment. This study suggests a technique for recognizing gestures that makes use of a convolutional neural network's sequential model made out of a collection of near-infrared pictures obtained by a Leap Motion sensor. The CNN model is made up of 13 different layers. The study also discusses numerous hand gesture recognition applications in the field of healthcare as well as the methodologies employed by these applications. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Human computer interaction

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Optical tastebuds for water quality testing 23

Optical tastebuds for water quality testing

引用

conference on Optical Fibers and sensors for Medical Diagnostics, Treatment and Environmental applications xxIII

作者： Sperling, Justin R. Savage, Laurie Wilson, Liam T. Cuthill, Calum McGuire, Katie Robbie, Jill Sloan, William Gauchotte-Lindsay, Caroline Peveler, William J. Clark, Alasdair W. Univ Glasgow James Watt Sch Engn Glasgow Lanark Scotland Univ Glasgow Sch Chem Glasgow Lanark Scotland Univ Glasgow Sch Law Glasgow Lanark Scotland

ISBN: (纸本)9781510658493;9781510658509

To achieve the UN Sustainable Development Goal of universal access to clean water and sanitation, we need to rethink centralized water systems with global net-zero carbon and sustainability in mind. One approach is to develop scalable off-grid systems that are reliable and easy to use and maintain. A major challenge for such systems is translating the standard laboratory-based monitoring of centralized systems to a more sustainable and scalable model for regularly and routinely monitoring system outputs, which consist of complex mixtures with varying concentrations of molecules and ions in water. Here, we demonstrate a preliminary sensor that, once fully developed, could allow for point-of-use measurements with a single output to monitor. Rather than developing multiple sensors to monitor the levels of each individual component in the water, our label-free, array-based design mimics the biological system of taste. The sensor is comprised of an array of nano-tastebuds made of tailored plasmonic metasurfaces. The combination of different signals from each nano-tastebud to the same sample yields a unique fingerprint for that sample. Through training, these fingerprints build an identification model. By integrating a fully developed sensor into decentralized water systems, we seek to provide non-expert end-users with an easy-to-read output capable of warning of imminent system failures.

关键词： plasmonics water environment sensor nanophotonics array-based sensing cross-reactive sensing metasurface

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Investigation into auto-labeling a novel dataset for off-road autonomy using transfer learning 2

Investigation into auto-labeling a novel dataset for off-roa...

引用

Artificial Intelligence for Security and Defence applications II 2024

作者： Honigfort, Haley B. Price, Stanton R. Carley, Samantha S. Butler, Samantha J. Davis, Trenton G. Dabbiru, Lalitha Ball, John E. Price, Stephanie J. Fairley, Joshua R. United States Army Corps of Engineers Engineer Research and Development Center VicksburgMS United States Mississippi State University Center for Advanced Vehicular Systems StarkvilleMS United States

ISBN: (纸本)9781510681200

In autonomous driving, utilizing deep learning models to help make decisions has become a popular theme, particularly in the realm of computer vision. These models are heavily geared to make decisions based on the environment in which they are trained. Currently, there are very few datasets that exist for off-road autonomy. In order for autonomous vehicles to traverse off-road or unstructured settings, the vehicles must have an understanding of these environments. This paper seeks to lay the groundwork for a new, off-road, multi-modality dataset, with initial data being collected at Mississippi State University’s Center for advanced Vehicular systems (MSU CAVS). This dataset will include co-aligned and co-registered LiDAR, thermal, and visual sensor data. Additionally, this dataset will include semantic segmented visual data as well as object detection and classification labels for all three modalities. However, to perform semantic segmentation on each image individually would be strenuous and time-consuming due to the large quantity of images. Thus, this paper will explore the utility of transfer learning for auto-labeling. Specifically, this paper considers how transfer learning for a unique and under-represented (data-wise) domain performs in reducing the burden associated with hand-annotation datasets for deep learning applications. © 2024 SPIE.

关键词： Semantic Segmentation

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Room-Temperature Ammonia sensor Based on MoS2/Polyaniline 16

Room-Temperature Ammonia Sensor Based on MoS2/Polyaniline

引用

16th International conference on Signal Processing systems, ICSPS 2024

作者： Qi, Guochen Ma, Zhichuang Ren, Shuwei Gao, Hao Liu, Pan Ge, Jingmin School of Mechanics and Safety Engineering Zhengzhou University Zhengzhou China

ISBN: (纸本)9781510689251

Ammonia (NH3) pollution poses a serious threat to human health and environmental safety. To achieve low-cost, rapid detection of ammonia, this paper proposes a sensor based on a molybdenum disulfide (MoS2)/polyaniline (PANI) composite material for quick ammonia detection. The powdery MoS2/PANI composite was synthesized using hydrothermal reaction and in-situ polymerization methods. The resulting materials were characterized using x-ray diffraction and other techniques to determine their composition and unique morphology. A sensor was fabricated by wrapping gold electrodes around an alumina ceramic tube. The sensor exhibits excellent gas-sensitive performance, providing precise responses to ammonia concentrations ranging from 3 to 250 ppm at room temperature. A segmented fitting method (3-20 ppm and 20-250 ppm) yielded good linear relationships with R2values of 0.997 and 0.998, respectively. It features rapid response, high sensitivity, and good selectivity, achieving a response to 200 ppm ammonia in 15 seconds and a maximum sensitivity of approximately 45% at 20 ppm. This method is characterized by simple manufacturing, low cost, and good reproducibility, showing promising applications in industrial production, healthcare, and environmental monitoring. © 2025 SPIE.

关键词： Ammonia

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International conference on Power Engineering and Intelligent systems, PEIS 2024

International Conference on Power Engineering and Intelligen...

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International conference on Power Engineering and Intelligent systems, PEIS 2024

ISBN: (纸本)9789819767090

The proceedings contain 41 papers. The special focus in this conference is on Power Engineering and Intelligent systems. The topics include: Smart Seating: The Smart Seating Solution for Crowded Public Transit;comparative Study of Coil Shapes for Electric Vehicle Resonant Wireless Power Transfer System;A Case Study of Solar Photovoltaic and Biomass-Based Hybrid Power System in Educational Institutes in Delhi-NCR;comparative Analysis of Water Bodies Segmentation Techniques;load Frequency Control in Hybrid Integrated Power systems with Redox Flow Batteries Using Dual-Mode Gain Scheduling Method;enhanced Discrete Cosine Transform Image Compression for Ultra-High-Resolution Imagery;Simulation and Analysis of 6T SRAM Cell in NGSpice: Exploring Performance and Stability;design of Double Precision Floating Point Comparator for Multiple Numbers;secured Regulatory Data Compliance for the Pharmaceutical Sector Through Blockchain;Optimizing IoT-Based Quantum Wireless sensor Networks Using NM-TEEN Fusion of Energy Efficiency and Systematic Governance;optimal Sizing and Allocation of Multiple Distributed Generation;high-Gain x-Band Patch Antenna for Spaceborne Synthetic Aperture Radar applications;protection of Series Compensated Networks Using Different Techniques: An Overview;a Robotic Way to Investigate Unapproachable Places and Inaccessible Substances Using e-skin;a Review of Chatbot Technology: Its Design and Implementation;exploring the Microcosm: A Comprehensive Survey of Micro sensor applications Across Multidisciplinary Research;stress Classification Using Machine Learning Techniques: Comparative Study;normalized Mutual Information-Driven Feature Extraction Method for Big Data Analytics;modeling of a Novel Correlation-Weighted Elman Neural Network for Building Automation System;Application FOPID for PLL Design in Grid Integration;Impact of Inter-Next Generation Node B (gNB) Distance on End-User applications in 5G Networks.

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Detector Plane Data Analysis of Scattered x-Rays Distribution: Theoretical Study vs Simulation Result 12

Detector Plane Data Analysis of Scattered X-Rays Distributio...

引用

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

作者： Smahina, Mariya Netreba, Andrii Radchenko, Sergiy National Taras Shevchenko University of Kyiv Faculty of Radiophysics Electronics and Computer Systems Kyiv01601 Ukraine

ISBN: (纸本)9798350358056

The precise description of the photons' scattering in matter is a complex physical, mathematical and computational task. However, just the scattered radiation is the dominant factor of x-ray images formation. So an approximate description of the scattered quantas distribution in the detector plane of the x-ray system is obtained based on theoretical dependencies. The data analysis and verification are carried out using the results of mathematical Monte Carlo modeling. The dependency simplicity and sufficient accuracy of the photon distribution description are grounds for mathematical correction algorithm developing of initial radiological data and image improvement. © 2023 IEEE.

关键词： computer Monte Carlo simulation GATE scatter reduction Scatter to Primary Ratio (SPR) software compensation x-ray medical image noise

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Research on traffic object recognition based on multi-sensor fusion

Research on traffic object recognition based on multi-sensor...

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2023 International conference on Computer Graphics, Artificial Intelligence, and Data Processing, ICCAID 2023

作者： Wu, Weilin Liu, Chunquan College of Electronic Information Guangxi Minzu University Nanning Guangxi530006 China Guangxi Postdoctoral Innovation Practice Base Wuzhou University Wuzhou Guangxi543003 China

ISBN: (纸本)9781510677685

The automotive advanced driver assistance systems (ADAS) are increasingly sophisticated due to the rapid advancement of intelligent connected vehicle technology. Consequently, higher demands are placed on both hardware infrastructure and onboard systems. To tackle the challenge of achieving complex traffic object recognition on limited hardware resources, a novel multi-sensor feature-level fusion strategy is proposed, which integrates data from millimeter-wave radar and visual sensors. By achieving synchronization of different sensors in both time and space domains, this strategy enhances the accuracy and robustness of traffic object recognition, while also improving computational efficiency and overall system performance. © 2024 SPIE.

关键词： Object recognition

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The BOHEMIAN Project: Versatile Hybrid in-Fiber Optical-Electrochemical systems for Widely Applicable Biosensing 3

The BOHEMIAN Project: Versatile Hybrid in-Fiber Optical-Elec...

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3rd IEEE International conference on Metrology for extended Reality, Artificial Intelligence and Neural Engineering, MetroxRAINE 2024

作者： Andò, Bruno Manenti, Mattia Greco, Danilo Guascito, Maria Rachele Lamberti, Giuseppe Martina, Laura Arcadio, Francesco Zeni, Luigi Cennamo, Nunzio Trono, Cosimo Tombelli, Sara Berneschi, Simone Marcucci, Niccolò Pasquardini, Laura Dieei University of Catania Catania Italy DiSTeBA University of Salento Lecce Italy Ennio De Giorgi University of Salento Dep. of Mathematics and Physics Lecce Italy University of Campania L. Vanvitelli Dep. of Engineering Aversa Italy Istituto di Fisica Applicata 'Nella Carrara' CNR-IFAC Firenze Italy Indivenire srl Trento Italy

ISBN: (纸本)9798350378009

Thereis a growing interest in the development of advanced chemical and biochemical detection methodologies enabling applications in the agri-food, environmental and healthcare sectors. This paper reports the main tasks accomplished in this field by the BOHEMIAN project. The project aims to develop an integrated sensing device implementing different detection methodologies for biosensing, such as electrochemical, capacitive and optical. In particular, exploiting features of the above sensing strategies, the following two solutions will be investigated by using aptamers as bioreceptors: a 'hybrid opto-electrochemical intrinsic fiber sensor' and a 'opto-capacitive sensor'. © 2024 IEEE.

关键词： Chemical detection

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Novel machine learning-based EOIR sensor performance modeling for naval applications 34

Novel machine learning-based EOIR sensor performance modelin...

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conference on Infrared Imaging systems - Design, Analysis, Modeling, and Testing xxxIV

作者： Crow, Brandon J. Espinola, Richard L. Owens, Saba Wilson, Rebecca US Navy Res Lab Code 5751 Washington DC 20375 USA Appl Technol Inc King George VA 22485 USA

ISBN: (纸本)9781510661806;9781510661813

The US Naval Research Laboratory (NRL) has recently developed an efficient modeling and simulation (M&S) capability to support naval surface warfare applications against a variety of EOIR sensing threats in the context of a tactical decision aid architecture. Starting with ship/ target signature, background sea clutter, and atmospheric transmission inputs obtained from high fidelity models such as ShipIR/NTCS and MODTRAN, combined with an Army CCDC RTID sensor performance metric, NRL used a novel methodology based on machine learning (ML) neural networks (NNs) to reduce large amounts of target/environment/sensor parameter data into an efficient network lookup table to predict target detectability. The model is currently valid for a few types of naval targets, in open ocean backgrounds as well as limited littoral scenarios for the VNIR (0.4-1 mu m) and IR (3-5 and 8-12 mu m) spectral regions. By using ML and NNs, the computational runtimes are short and efficient. This paper will discuss the methodology and show preliminary results produced in an integrated tactical decision aid software.

关键词： EOIR sensor modeling simulation machine learning neural network

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