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

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Techniques to Improve Robustness of Video-Based sensor Networks 39th

Techniques to Improve Robustness of Video-Based Sensor Netwo...

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39th IMAC, A conference and Exposition on Structural Dynamics, 2021

作者： Mantell, Sarah Sapong, Nathan Schwamb, Addison Mascareñas, David Cattaneo, Alessandro University California Polytechnic State University San Luis ObispoCA United States University of California Riverside RiversideCA United States Oklahoma Christian University EdmondOK United States Los Alamos National Laboratory Los AlamosNM United States

ISBN: (纸本)9783030760038

Recently, work has been done to combine video-based structural dynamics with structural health monitoring—rather than using contact-based sensors such as accelerometers and strain gauges. The installation and maintenance costs of contact-based sensors along with the difficulty in processing the data from malfunctioning sensors pose a significant challenge for long-term, large-scale applications. Video-based structural health monitoring provides a framework for obtaining the data relevant to structural health monitoring without the drawbacks associated with contact-based sensors. Each pixel from a video can be analyzed for structural health monitoring, resulting in a higher data resolution than that collected by contact-based sensors. As video-based structural health monitoring is a new field, there are still major challenges to overcome. Undesirable event data such as atmospheric noise, misalignment or loss of camera monitor, or objects entering the frame can obstruct measurement procedures. Additionally, videos are inherently large in size—data of this magnitude is costly to analyze, transmit, and store for long-term applications. We improve the robustness of the full-field modal analysis algorithm by increasing the algorithm’s performance under various types of digital noise, occlusions, and rotations. Additionally, we use sparse sensing techniques to reduce the size of the transmitted and stored data, working toward making video-based dynamics a low-cost and robust option for structural health monitoring applications. © 2022, The Society for Experimental Mechanics, Inc.

关键词： sensor networks

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A CNN-based Audio sensor for Rainfall Estimation: Implementation on Embedded Board 11

A CNN-based Audio Sensor for Rainfall Estimation: Implementa...

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11th IEEE International conference on Intelligent Data Acquisition and advanced Computing systems - Technology and applications (IDAACS)

作者： Russo, Michele Puglisi, Valerio Francesco Avanzato, Roberta Beritelli, Francesco VICOSYSTEMS SRL Viale Odorico da Pordenone I-95128 Catania Italy Univ Catania DMI Viale Andrea Doria 6 I-95125 Catania Italy Univ Catania DIEEI Viale Andrea Doria 6 I-95125 Catania Italy

ISBN: (纸本)9781665426053

At present, one of the main issues of interest is climate change. It triggers calamitous phenomena (fires, hydrogeological instability and many others) that put crops, vegetation and even human beings at risk. Considering the phenomenon of hydrogeological instability, there is a wide range of smart application contexts (for example, smart city, smart road and smart agriculture), which require a real-time rainfall level monitoring, recognition and classification system. This system is supposed to provide accurate and real-time estimates of rain intensity and alert those in charge in order to reduce the risks associated with the various application contexts. Thus, the present paper proposes an audio sensor enabled real-time audio rainfall classification, based on 1-D convolutional neural network (CNN) which offers 95% classification accuracy in five rainfall intensity classes.

关键词： Audio classification Enviroment sound classification Feature extraction techniques Convolutional Neural Networks Multimodal Analysis Rainfall Estimation

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Railway Switch Machine Fault Diagnosis Considering sensor Abnormality Scenarios

Railway Switch Machine Fault Diagnosis Considering Sensor Ab...

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International conference on Intelligent Transportation

作者： Xiaoxi Hu Xiaohan Zhang Zhaorong Wang Yunbo Chen Jiangnan Xia Yawen Du Yi Li State Key Laboratory of Advanced Rail Autonomous Operation Beijing Jiaotong University Beijing China Polytechnic Institute Zhejiang University Hangzhou China

Since the safe and reliable behavior of a Railway Switch Machine (RSM) is definitely pivotal for rail transportation, scholars and engineers have studied a considerable number of algorithms for RSM fault diagnosis via many kinds of sensor information. However, scholars have yet to consider the impact of the sensors' states on RSM fault classification, which cannot be ignored in practical railway applications. To fill the gap, we propose an end-to-end deep learning architecture named Fault Diagnosis Considering sensor Abnormality Network (FD-CSANet) for RSM behavior recognition under various sensor states. Our approach includes sensor Information Aggregate Module (SIAM) and Fault Diagnosis Module (FDM). The SIAM utilizes the idea of the channel attention mechanism to filter and aggregate multiple sensor features, which weights normal sensor observation and weakens anomalous sensor information. The FDM adopts the DB EM as the backbone for the RSM fault diagnosis. Ultimately, ablation experiments and comparative studies demonstrate the superiority of our algorithm.

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A Sensitivity-enhanced All-fiber Fabry-Perot High-pressure sensor with a Hard-core Diaphragm 11

A Sensitivity-enhanced All-fiber Fabry-Perot High-pressure S...

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conference on advanced sensor systems and applications XI

作者： He, Xiu Ran, Zengling Wang, Nan Ding, Zhaoyang Gan, Lupeng Yu, Mengke He, Zhengxi Sun, Dong Rao, Yunjiang Zhang, Yachao Ye, Dongsheng Univ Elect Sci & Technol China Minist Educ Fiber Opt Res Ctr Key Lab Opt Fiber Sensing & Commun Chengdu 611731 Sichuan Peoples R China Shaanxi Binchang Dafosi Min Co Ltd Xian Shanxi Peoples R China Shanxi Coal Chenghe Min Co Ltd Xian Shanxi Peoples R China

ISBN: (数字)9781510646520

ISBN: (纸本)9781510646520;9781510646513

A novel sensitivity-enhanced all-fiber Fabry-Perot high-pressure sensor consisting of a long gauge-length and a hard-core diaphragm is proposed and demonstrated. The hard-core diaphragm can effectively improve the pressure sensitivity of the sensor and eliminate the additional reflection of its outer surface. Theoretical and experimental results show that the pressure sensitivity of the sensor is increased to about 2 times when its diaphragm thickness is decreased from 5 mm to 11 mu m. In addition, the pressure and temperature sensitivity of -342.6 pm/MPa and -2.8 pm/degrees C are achieved, respectively, in the pressure range of 0 similar to 20 MPa and temperature range of 13.6 similar to 300 degrees C. The proposed sensor could offer some excellent features such as good high-temperature stability, low-temperature pressure cross-sensitivity, low mechanical hysteresis, making it attractive for pressure measurement under harsh environments.

关键词： fiber-optic Fabry-Perot sensitivity-enhanced high pressure diaphragm

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Water Quality Monitoring and Cleaning System

Water Quality Monitoring and Cleaning System

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International conference on Communication, Computing and Internet of Things (IC3IoT)

作者： B. Puviyarasi P. Gubhenthiran P. Keerthana S. Megala Electronics and Instrumentation Engineering Sri Sairam Engineering college Chennai India

ISBN: (数字)9798350352689

ISBN: (纸本)9798350352696

This paper shows a strategy for the growing need for water resources, making it necessary to maintain the sustainability and quality of these essential ecosystems. This paper introduces a sophisticated Water Quality Monitoring and Cleaning System designed to revolutionize the way we perceive, assess, and safeguard our water bodies. The primary goal is to develop an integrated platform that seamlessly combines cutting-edge sensor technologies, mobile applications, and intelligent alert systems to address the challenges associated with water quality monitoring and purification. The primary aim of this paper is to establish an effective and user-centric system that provides real-time insights into water quality parameters. This system includes advanced sensors and data is collected and transmitted to a secure Firebase database. A feature-rich mobile application empowers users to visualize, analyze, and interpret current and historical water quality data. Additionally, an intelligent alert system ensures immediate response to potential water quality deviations, promoting timely intervention.

关键词： Ecosystems Water quality Water conservation Real-time systems Water pollution Mobile applications Telecommunication computing

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Giant Magnetoimpedance Microwires for sensor applications

Giant Magnetoimpedance Microwires for Sensor Applications

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8th International conference on Antennas and Electromagnetic systems, AES 2022

作者： Zhukov, Arcady Corte-León, Paula González-Legarreta, Lorena Ipatov, Mihail Blanco, Juan M. Zhukova, Valentina Dpto. Fisica de Materiales Fac. Quimicas UPV/EHU Paseo Manuel Lardizabal 3 San Sebastian20018 Spain Dpto. de Física Aplicada EIG UPV/EHU Europa Plaza 1 San Sebastian20018 Spain IKERBASQUE Basque Foundation for Science Bilbao48011 Spain

The influence of post-processing (annealing and stress-annealing) on the Giant magnetoimpedance (GMI) effect in thin magnetic microwires is reviewed. High GMI effect has been observed in Co-rich magnetic microwires with vanishing magnetostriction coefficient. Post-processing including annealing or stress-annealing at adequate conditions allows further improvement of GMI effect in Co-rich magnetic microwires. © 2022 advanced Electromagnetics Symposium. All rights reserved.

关键词： Annealing

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A Novel Laser Patterned Flexible Graphene Nanoplatelet Electrode for Fast Charging Lithium-Ion Battery applications

A Novel Laser Patterned Flexible Graphene Nanoplatelet Elect...

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2022 IEEE International conference on Flexible and Printable sensors and systems (FLEPS)

作者： Emani, H. R. K. M. Palaniappan, V Ahmadi, S. Zhang, X. Maddipatla, D. Bazuin, B. J. Wu, Q. Atashbar, M. Z. Western Michigan Univ Dept Elect & Comp Engn Kalamazoo MI 49008 USA Western Michigan Univ Dept Chem & Paper Engn Kalamazoo MI 49008 USA

ISBN: (纸本)9781665442732

A flexible anode was developed with graphene nanoplatelet (xGnP) as the anode material for fabricating fast charging lithium-ion battery. The ink consists of xGnP as active material along with C-45 carbon black as conductive additive and polyvinylidene fluoride (PVDF) as binder. The ink was bar coated on to a flexible copper film to form anode. Then the anode was laser patterned to introduce secondary pore network (SPN) consisting of pores with diameter of similar to 75 mu m with an edge-to-edge distance of similar to 70 mu m between the pores. Half-cell lithium-ion batteries was assembled with laser patterned anode and lithium metal foil as counter electrode. Ethylene carbonate and dimethyl carbonate (EC: EDC) in 50/50 (v/v) mixed with 1M lithium hexafluorophosphate (LiPF6) was used as electrolyte in assembled coin-cells. Rate performance was tested for laser patterned electrodes at different current rates. Resultant laser-patterned xGnP electrode delivered enhanced specific capacity of 333 mAh/g when compared to bar-coated electrode without SPN (243 mAh/g) at 6A/g current rate.

关键词： laser-patterned graphene nanoplatelet flexible secondary pore network (SPN) specific capacity

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Optimized Bidirectional Long Short-Term Memory Model for Distributed Denial of Service Attack Detection in Wireless sensor Networks

Optimized Bidirectional Long Short-Term Memory Model for Dis...

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Smart Technologies and systems for Next Generation Computing (ICSTSN), International conference on

作者： K Poongodi S Mithuna S Rajkumar Computer Science and Engineering K. S. Rangasamy College of Technology India

ISBN: (数字)9798350391565

ISBN: (纸本)9798350391572

The rapid expansion of Wireless sensor Networks (WSNs) has made them a critical component in various applications, from environmental monitoring to military surveillance. However, their inherent vulnerabilities make them prime targets for Distributed Denial of Service (DDoS) attacks, that have the potential to significantly impair data integrity and network performance. This paper presents an advanced approach for DDoS detection in WSNs using an optimized Bidirectional Long Short-Term Memory (Bi-LSTM) network. The proposed method leverages the strengths of Bi-LSTM in capturing temporal dependencies and patterns within network traffic data, providing a robust mechanism for identifying anomalous activities indicative of DDoS attacks. To enhance the detection accuracy and efficiency, introduce a novel optimization technique that fine-tunes the BiLSTM parameters, balancing the trade-offs between detection performance and computational overhead. Extensive simulations demonstrate that our optimized Bi-LSTM model significantly outperforms traditional machine learning approaches and standard LSTM configurations. The results underline the potential of this approach in fortifying WSNs against sophisticated DDoS threats, ensuring reliable and secure network operations.

关键词： Wireless communication Wireless sensor networks Computational modeling Surveillance Telecommunication traffic Denial-of-service attack Security

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Intelligent Fruit Quality Monitoring System using sensor Networks and Deep Learning

Intelligent Fruit Quality Monitoring System using Sensor Net...

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Smart Electronics and Communication systems (ISENSE), International conference on

作者： Arvind Kumar N. Jaya Krishna Mahesh Chandra Rampravesh Kumar Jaya Prakash Sahoo N. Poojitha Biswajit Karan Kamlesh Kishore Department of EECE Gitam University Bengaluru India School of ECE Reva University Bengaluru India Department of EEE Sandip University Nashik India Department of EEE University of Stellenbosch Stellenbosch South-Africa Department of ECE RTC Institute of Technology Bengaluru India

ISBN: (数字)9798331528126

ISBN: (纸本)9798331528133

This paper presents a novel approach for fruit quality detection using a multi-modal system that combines sensor data and image processing techniques with deep learning. In the first stage of our experiment, we employed various sensors to measure temperature, gas levels, and moisture content using DHT 11 and MQ-135 sensors. These sensors provide valuable insights into the environmental conditions surrounding the fruits, which are crucial indicators of their freshness. In the second stage, we utilized image processing algorithms to pre-process fruit images and train a SqueezeNet convolutional neural network (CNN) to classify fruits into two classes: fresh and rotten. By integrating sensor data with image-based classification, our proposed method offers a comprehensive solution for real-time fruit quality assessment. Experimental results demonstrate the effectiveness of our approach in accurately detecting fruit quality, paving the way for advanced applications in food safety and quality control.

关键词： Deep learning Temperature measurement Temperature sensors Accuracy Quality control Robustness Food safety Quality assessment Convolutional neural networks Monitoring

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Highly sensitive temperature sensor with optomechanofluidic resonators 11

Highly sensitive temperature sensor with optomechanofluidic ...

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conference on advanced sensor systems and applications XI

作者： Liu, Yize Jiang, Junfeng Liu, Kun Wang, Shuang Niu, Panpan Wang, Tong Liu, Tiegen Tianjin Univ Sch Precis Instrument & Optoelect Engn Tianjin 300072 Peoples R China Tianjin Univ Minist Educ Key Lab Optoelect Informat Technol Tianjin 300072 Peoples R China Tianjin Univ Inst Opt Fiber Sensing Tianjin Opt Fiber Sensing Engn Ctr Tianjin 300072 Peoples R China

ISBN: (数字)9781510646520

ISBN: (纸本)9781510646520;9781510646513

Microfluidic optomechanical device are a unique optofluidics platform that can exhibit optomechanical oscillation in the 10-20 MHz, driven by radiation pressure (RP). The resonant enhancement of both mechanical and optical response in microcavity optomechanical devices allows exquisitely sensitive measurements of environment stimuli (pressure, force, sound speed change) and non-solid states of matter (freely flowing particles, viscous fluids). In this work, we experimentally investigate temperature tuning of these hollow-shell oscillators. We also demonstrate the effect of temperature on the frequency domain of optical machine oscillation resonance shift and applied it to the field of temperature sensing. Our result is a step towards optomechanical sensor in the field of temperature.

关键词： Optomechanical oscillation Temperature sensor Whispering gallery mode

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