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Transient Overvoltage Protection Planning for DC Structural Health Monitoring System Circuit

Transient Overvoltage Protection Planning for DC Structural ...

引用

Electronic and Electrical Engineering and intelligent System (ICE3IS), International conference on

作者： Mas'uda Rosyadi M. Isnaeni Bambang S Lesnanto Multa Putranto Department of Electrical and Information Engineering Universitas Gadjah Mada Yogyakarta Indonesia

ISBN: (数字)9798350378368

ISBN: (纸本)9798350378375

Protection against overvoltage during lightning causes damage to components and sensors in electronic devices, including the Structural Health Monitoring System (SHMS) used in bridges and tunnels in Indonesia, causing one of the functions not to work. The SHMS is equipped with a lightning rod, but its protection in the DC circuit still needs to be improved. Protection of DC networks need to be done to ensure SHMS performance. TVS diode and MOV series are proposed as protection equipment that cuts excess voltage to lower transient waves. The reliability of the protection system can be met by testing the RS485 module connected to the sensor. Implementing the protection system can work better when compared to the RS485 module not connected to the protection system.

关键词： Varistors Metals Lightning Voltage sensor systems sensors Protection Transient analysis Voltage control Monitoring

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Goal-Oriented Communication for Networked Control Assisted by Reconfigurable Meta-Surfaces

Goal-Oriented Communication for Networked Control Assisted b...

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IEEE Workshop on Signal processing Advances in Wireless Communications (SPAWC)

作者： Mohamad Assaad Touraj Soleymani Laboratory of Signals and Systems CentraleSupélec University of Paris-Saclay Gif-sur-Yvette France City St George’s School of Science and Technology University of London London United Kingdom

ISBN: (数字)9798350393187

ISBN: (纸本)9798350393194

In this paper, we develop a theoretical framework for goal-oriented communication assisted by reconfigurable meta-surfaces in the context of networked control systems. The relation to goal-oriented communication stems from the fact that optimization of the phase shifts of the meta-surfaces is guided by the performance of networked control systems tasks. To that end, we consider a networked control system in which a set of sensors observe the states of a set of physical processes, and communicate this information over an unreliable wireless channel assisted by a reconfigurable intelligent surface with multiple reflecting elements to a set of controllers that correct the behaviors of the physical processes based on the received information. Our objective is to find the optimal control policy for the controllers and the optimal phase policy for the reconfigurable intelligent surface that jointly minimize the linear-quadratic-regulation cost function associated with the networked control system. We characterize these policies, and also propose an approximate solution based on a semi-definite relaxation technique.

关键词： Wireless communication Wireless sensor networks Networked control systems Process control Optimal control Reconfigurable intelligent surfaces Signal processing Cost function sensor systems Regulation

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Modeling the Clustering of Wireless sensor networks Using the K-means Method

Modeling the Clustering of Wireless Sensor Networks Using th...

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2021 IEEE International conference "Quality Management, Transport and information Security, information Technologies", T and QM and IS 2021

作者： Voronova, Lilia I. Voronov, Vyacheslav I. Mohammad, Nawar Moscow Technical University Communications and Informatics 'MTUCI' Department of Intelligent Systems in Control and Automation Moscow Russia

ISBN: (纸本)9781665433020

Currently, the development of information and communication technologies has led to the emergence of the Internet of Things. The technological basis for the implementation of the concept of the Internet of Things is wireless sensor networks. Clustering, a machine learning technique, is an effective way to extend the lifecycle and reduce power consumption of wireless sensor networks (WSNs). The article presents modeling and clustering of flying wireless sensor networks that form when a group of drones moves. The introduction of moving sensors leads to dynamic clustering of the entire system at successive times. complicating the determination of the number of individual clusters and their integration. The clustering mechanism is performed using the K-means algorithm with respect to the location of wireless stationary and flying sensors, described by coordinates x, y, and z in three-dimensional space. © 2021 IEEE.

关键词： Wireless sensor networks

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Where Is the Internet of Health Things Data? 24

Where Is the Internet of Health Things Data?

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24th International conference on Enterprise information Systems (ICEIS)

作者： Costa Junior, Evilasio Andrade, Rossana M. C. Venceslau, Amanda D. P. Oliveira, Pedro Almir M. Santos, Ismayle S. Oliveira, Breno S. Fed Univ Ceara UFC Grp Comp Networks Software Engn Syst Great Fortaleza Ceara Brazil

ISBN: (纸本)9789897585692

The advent of Internet of Things (IoT) and the smart objects popularization have boosted the data generation in many areas. Data have then become increasingly valuable as they can be used to "teach" machines to perform the most varied tasks. Health is among the areas that have benefited from such data, because there is, for example, a need for solutions that optimize the cost-benefit ratio of health systems. In this scenario, the Internet of Health Things (IoHT) uses smart sensors to collect patient data and intelligent algorithms to process this data for improving patient Quality of Life. However, researchers and practitioners have faced difficulties in finding and using public health care data sensor repositories. Therefore, we conducted a systematic multivocal review of IoHT databases to identify and characterize the existing datasets. We also bring as a contribution of this paper a set of guidelines about how new IoHT data repositories can be structured.

关键词： Internet of Health Things Databases Systematic Multivocal Review

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TT08 intelligent sensors, sensor networks, and information processing

TT08 Intelligent Sensors, Sensor Networks, and Information P...

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International conference on Emerging Technologies and Factory Automation (ETFA)

Start of the above-titled section of the conference proceedings record.

ISBN: (数字)9781728189567

ISBN: (纸本)9781728189574

Start of the above-titled section of the conference proceedings record.

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Partial Discharge Type Identification Based on PSO Optimised BP-RF Model and Multi-Type sensors

Partial Discharge Type Identification Based on PSO Optimised...

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Power and Electrical Engineering (ACPEE), 5th Asia conference on

作者： Xia Xiaofei Su Yi Feng Bo Lu Yufeng Rao Xiajin Electric Power Research Institute of Guangxi Power Grid Co. Ltd Guangxi China Guangxi Key Laboratory of Intelligent Control and Maintenance of Power Equipment Guangxi China

ISBN: (数字)9798350309638

ISBN: (纸本)9798350309645

For the partial discharge phenomenon occurring during the use of power equipment, the partial discharge data acquired by multiple sensors (HFCT, AE, TEV) are used to correct the PRPD map by image processing techniques, so as to improve the accuracy of partial discharge type identification. The partial discharge signals under different experimental conditions were acquired using HFCT, AE and TEV sensors, and the alignment of PRPD images acquired by different sensors was achieved by image processing. On this basis, the data from individual sensors were preliminary classified using BP neural networks to identify different types of partial discharge patterns; the per-classification results of these individual sensing were input into the Random Forest algorithm model as features, while the Particle Swarm Optimization algorithm was used to search for the optimal hyper-parameters of the Random Forest, and finally, the Random Forest algorithm model of the Particle Swarm Optimization was used to make the final decision and classification. The experimental results show that the method can effectively identify and classify different types of partial discharges, providing a new technical way for power system maintenance and fault prevention.

关键词： Partial discharges Image sensors Image processing Neural networks sensor phenomena and characterization Data models Classification algorithms

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Beyond The Internet of Things: Imagining IoT's Structure and Potential Routes

Beyond The Internet of Things: Imagining IoT's Structure and...

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2023 International conference on Advances in Computation, Communication and information Technology, ICAICCIT 2023

作者： Varalakshmi, K.R. Mahesh, T.R. Singh, Akhilendra Pratap Presidency University Department of Electronics and Communication Engineering Karnataka Bangalore India Faculty of Engineering and Technology Department of Computer Science Engineering Karnataka Bangalore India Maharishi University of Information Technology Maharishi School of Engineering & Technology Uttar Pradesh India

ISBN: (纸本)9798350344387

wireless sensor system technology has made it possible for ubiquitous sensing, which affects many aspects of contemporary life. Indicators of environmental health, from sensitive ecologies as well as biodiversity to urban settings, may now be measured, inferred, and understood. The Internet of Things is enabled by the extensive utilization of these devices in a network that facilitates communication and action. In this network, the actuators and sensors smoothly interact with our environment as data is exchanged across platforms to provide a unified operational view. Near field communication (NFC) is the upcoming technology that will enable the transformation of the worldwide web into a fully integrated Future Internet. This technology is being advanced through the adoption of variousenabling device methods, such as tags, audience members, encased sense and actuators nodes, and nodes for near field interaction. The demand for data-on-demand, using complex and straightforward queries, increases significantly as studies transition from web to web2 to web3. This study presents a cloud-centric vision for the worldwideimplementation of the Internet of Things. The future of IoT research is expected to be influenced by many significant technology enablers and their corresponding application domains, which are emphasized. A cloud architecture based on the interplay of public as well as private clouds and employing Aneka is shown. Study conducted elaborate on the need of unity, the global web, and distributed processing in our last section of our IoT vision for the community of technical researchers. © 2023 IEEE.

关键词： Cloud-centric Internet of Things Data storage and analytics Internet of Things (IoT) New protocols Participatory Sensing Quality of Service (QoS) Radio Frequency Identification (RFID) User-cantered cloud-based paradigm Visualization Wireless sensor networks

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A Hybrid Residual CNN with Channel Attention Mechanism for Continuous User Identification Using Wearable Motion sensors

A Hybrid Residual CNN with Channel Attention Mechanism for C...

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International conference on Telecommunications and Signal processing (TSP)

作者： Sakorn Mekruksavanich Wikanda Phaphan Anuchit Jitpattanakul Department of Computer Engineering School of Information and Communication Technology University of Phayao Phayao Thailand Department of Applied Statistics Faculty of Applied Science Research Group in Statistical Learning and Inference King Mongkut's University of Technology North Bangkok Bangkok Thailand Department of Mathematics Faculty of Applied Science Intelligent and Nonlinear Dynamic Innovations Research Center King Mongkut's University of Technology North Bangkok Bangkok Thailand

ISBN: (数字)9798350365597

ISBN: (纸本)9798350365603

Recognizing individuals continuously using wearable devices has several applications in personalized services and security. This paper presents a hybrid deep network architecture called SE-ResBiLSTM that integrates a squeeze-and-excitation (SE) mechanism with residual bidirectional LSTM layers. The goal is to enhance the accuracy of person identification using data from wearable motion sensors. The SE blocks facilitate channel-wise feature refinement, highlighting helpful information. Residual connections enable the training of deeper LSTM architectures. The proposed method's accuracy in identifying individuals across increasing periods between training and testing is evaluated using the SP-SW HAR dataset, which contains activity data collected from wristwatch sensors. By leveraging representation learning and exhibiting resilience against sensor noise and temporal fluctuations, SE-ResBiLSTM improves recognition accuracy compared to regular and convolutional LSTM networks. According to the trial data, SE-ResBiLSTM achieved a maximum identification accuracy of 98.71 %. The experimental results demonstrate that this approach significantly boosts the performance of user identification using wristwatch sensors.

关键词： Training Representation learning Accuracy Motion detection Telecommunications Security Wearable devices

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Demo Abstract: CaringFM: An Interactive In-home Healthcare System Empowered by Large Foundation Models

Demo Abstract: CaringFM: An Interactive In-home Healthcare S...

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International Symposium on information processing in sensor networks (IPSN)

作者： Haiyang Wu Kaiwei Liu Siyang Jiang Zhihe Zhao Zhenyu Yan Guoliang Xing The Chinese University of Hong Kong Hong Kong SAR

ISBN: (数字)9798350362015

ISBN: (纸本)9798350362022

The demand for fully on-device health monitoring is huge and urgent. However, deploying Large Foundation Models conventionally relies on cloud-based computing services, which poses privacy concerns. Driven by the belief of delivering personalised healthcare to family members, this study presents the development of an innovative on-device machine learning system, CaringFM. This family caring system utilizes privacy-protecting sensors and an edge-deployed Foundation Model(FM) to offer a convenient and low-cost solution for chronic disease prediction and health condition monitoring at home. In particular, CaringFM provides general health suggestions and personalized medical information while ensuring high privacy by processing and preserving all data locally.

关键词： Privacy Computational modeling Knowledge based systems Medical services Machine learning information processing Predictive models

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Adaptive Monitoring Optimization Based on Deep-Q-Network for Energy Harvesting Wireless sensor networks 12th

Adaptive Monitoring Optimization Based on Deep-Q-Network for...

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12th International conference on Mobile networks and Management, MONAMI 2022

作者： Bao, Xuecai Bian, Peilun Tan, Wenqun Xu, Xiaohua Nie, Jugen Jiangxi Province Key Laboratory of Water Information Cooperative Sensing and Intelligent Processing Nanchang Institute of Technology Nanchang Jiangxi330099 China Jiangxi Provincial Technology Innovation Center for Ecological Water Engineering in Poyang Lake Basin Jiangxi330029 China

ISBN: (纸本)9783031324420

In order to improve the energy efficiency of environmental monitoring for energy harvesting wireless sensor networks (EH-WSNs) in remote areas and achieve energy-neutral operation, an adaptive monitoring and energy management optimization method of EH-WSNs based on deep Q network (DQN) algorithm is proposed. In this paper, aiming at EH-WSNs with single-hop cluster structure, we first present a more realistic energy model established by combining different climate characteristics. Then, the optimization model of maximizing long-term monitoring utility is formulated based on harvested energy constraints. We use deep Q network (DQN) to learn random and dynamic solar energy harvesting process on solar-powered sensor nodes and optimize the monitored performance of EH-WSNs through the replay memory mechanism and freezing parameter mechanism. Finally, we present an adaptive monitoring optimization method based DQN to achieve the long-term utility. Through simulation verification and comparative analysis, in different rainy weather environments, the proposed optimization algorithm has greatly improved in terms of average monitoring reward, monitoring interruption rate and energy overflow rate. Moreover, it also indicates that the proposed algorithm has effective adaptation to the random and dynamic solar energy arrival. © 2023, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Energy harvesting

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