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

共 9417 条记录，以下是261-270 订阅

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Security Provisioning as Integrity in wireless sensor networks (WSN): A Survey 14

Security Provisioning as Integrity in wireless sensor networ...

引用

14th international conference on Computing Communication and Networking technologies, ICCCNT 2023

作者： Venkateswari, P. Shanmugasundaram, N. Avs College of Technology Department of Computer Science and Engineering Tamil Nadu Salem636106 India Sri Eshwar College of Engineering Department of Electronics and Communication Engineering Tamil Nadu Coimbatore641202 India

ISBN: (纸本)9798350335095

Wireless sensor networks (WSNs) are composed of small sensory nodes with limited energy that are deployed in large numbers in order to monitor a physical event in the area to be watched. These nodes have been built to cooperate and operate independently from a centralized infrastructure. The data sent to the sink node from these sensor nodes is seriously threatened by a range of attacks from malicious nodes. In crucial applications like military surveillance, data integrity is a major problem when it comes to security concerns. In order to pave the road for future researchers with a deep understanding of data integrity in WSN, this study analyzes data integrity research from a variety of angles. The limitations of sensor nodes prevent the deployment of traditional data integrity protection measures in WSNs, which require complicated computations. Researchers have recently devised a number of less sophisticated and unique strategies to ensure and enhance data integrity using various cryptographic techniques. © 2023 IEEE.

关键词： sensor nodes

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Digital Twin and Cloud Based Remote Control of Vehicles 2

Digital Twin and Cloud Based Remote Control of Vehicles

引用

2nd IEEE international conference on Mobility, Operations, Services and technologies, MOST 2024

作者： Rovid, Andras Tihanyi, Viktor Cserni, Marton Csontho, Mihaly Domina, Adam Remeli, Viktor Vincze, Zsolt Szanto, Matyas Szalai, Matyas Nagy, Szabolcs Szalay, Zsolt Budapest University of Technology and Economics Faculty of Transportation Engineering and Vehicle Engineering Department of Automotive Technologies Hungary Budapest University of Technology and Economics Faculty of Electrical Engineering and Informatics Department of Control Engineering and Information Technology Hungary

ISBN: (纸本)9798350307733

Cloud-based, centralized control system architectures have been published in recent years, examining the applications, structure and validity of the idea of controlling a vehicle, or multiple vehicles directly from the cloud. The literature presents possible advantages and disadvantages of Control as a Service (CaaS), as well as multiple viable applications, however no real-car real-world implementation exists to the best of our knowledge. In our experiments, we demonstrate a real-life and real-time vehicle control method that runs in the cloud and reacts adaptively to the vehicle's surroundings. In the presented tests, acquisition of the vehicle and environment state is performed from a collective perception-based digital twin that is also produced in our cloud-based Central System using data streams from our distributed sensor network. We conduct real-world physical vehicle tests, and establish that cloud-based centralized control is a viable solution, and an interesting research direction. We test our vehicle control in one mixed reality, and two real-world scenarios on the ZalaZONE proving ground in Hungary, Zalaegerszeg. Our experiments prove that cloud-based low-level vehicle control is feasible. © 2024 IEEE.

关键词： sensor networks

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Decision Based Control Approach for BLDC Motor Drive in Pedal Assisted Electric Bicycle

Decision Based Control Approach for BLDC Motor Drive in Peda...

引用

2023 IEEE international conference on Power Electronics, Smart Grid, and Renewable Energy, PESGRE 2023

作者： Farakate, Ranjit Ugale, Rajaram. T. Wekhande, Shashank Coep Technological University Department of Electrical Engineering Pune India Allegro MicroSystems Marketing India Pvt Ltd. Applications Marketing Group Pune India

ISBN: (纸本)9798350310573

The electric bicycle is powered by a battery to provide "assist". The assist control is provided by a pedal assist sensor or a throttle sensor. This article presents a simple decision-based control approach for the brushless DC (BLDC) motor of pedal assisted electric bicycle. The duty cycle of the motor is controlled via user input through throttle sensor, feedback information of the pedal via the pedal assist sensor (PAS), and speed feedback using speed sensor. A sensorless field-oriented control (FOC) algorithm is used for the control of BLDC motor to realize an efficient system. The overall system is designed, and hardware implementation is carried out. The steady-state performance, dynamic performance and the thermal performance of the overall system is validated on the developed hardware prototype. © 2023 IEEE.

关键词： Brushless DC Motor (BLDC) Electric Bicycle Field-Oriented Control (FOC) Pedal Assist sensor Throttle sensor

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Design and Research of High Sensitivity Metamaterial sensor

Design and Research of High Sensitivity Metamaterial Sensor

引用

2021 international conference on Optical Instruments and Technology: IRMMW-THz technologies and applications

作者： Wu, Jingwen Du, Yong Centre for THz Research China Jiliang University Hangzhou310018 China

ISBN: (纸本)9781510655737

We propose and demonstrate a multi-peak high-sensitivity refractive index sensor for the terahertz band. The designed sensor is composed of a flexible polyimide substrate and a metal structure array covering the top, which is easy to be processed and convenient to be used. According to different structural changes, we can adjust the resonant frequency of the designed metamaterial sensor. The simulation results show that the sensor has three resonance peaks (0.46, 1.06, and 1.29 THz respectively) in the frequency range of 0.1-1.4 THz, and among them the maximum refractive index sensing sensitivity obtained is 272 GHz/RIU. The proposed metamaterial sensor with such high sensitivity performance has potential application prospects in biomedical sensing and trace substance detection. © 2022 SPIE.

关键词： Metamaterials

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Enhanced Intrusion Detection in Wireless sensor Networks: A Voting and Particle Swarm Optimization Approach 21

Enhanced Intrusion Detection in Wireless Sensor Networks: A ...

引用

21st IEEE international conference on Smart Communities: Improving Quality of Life using AI, Robotics and IoT, HONET 2024

作者： Jaradat, Ameera Alhatamleh, Salem Nasayreh, Ahmad Gharaibeh, Hasan Yarmouk University Dept. of Computer Sciences Irbid Jordan

ISBN: (纸本)9798350378078

Wireless sensor networks (WSNs) are of great importance in advanced technologies in the modern developing world as they are widely used in many applications. Although encryption and authentication protocols in WSNs are widely adopted, there are continuous expectations of new sophisticated attack strategies that are spreading, which pose high risks and threats. This work addresses these challenges using Intrusion Detection Systems (IDS) that will be supported by machine learning algorithms. Specifically, it explores the WSN-DS dataset that includes network activities and attack types. In addition, it initializes the importance of feature selection and proposes data balancing methods such as Synthetic Minority Over-sampling Technique SMOTE, it is a statistical method for correcting class imbalance in datasets by creating synthetic samples for the minority class to enhance the detection rate. To increase the performance of the machine learning model, we use a voting classifier consisting of Random Forest (RF), K-Nearest Neighbors (KNN) and Extreme Gradient Boosting (XGBoost) and optimize them using Particle Swarm Optimization (PSO) by selecting the best hyperparameters. This ensemble method aims to maximize the performance of the used ensemble models. The proposed model is demonstrated by improving the PSO voting classifier model which gives a remarkable accuracy of 99.99% making it a highly effective approach in predicting and filtering different types of attacks in wireless sensor networks. This work will help in promoting further research in protecting wireless sensor networks from invasive intrusions in various applications to ensure security in communication networks. © 2024 IEEE.

关键词： Network intrusion

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Design of USB Average Power sensor Based on Multi-path Diode Detection 15

Design of USB Average Power Sensor Based on Multi-path Diode...

引用

15th international conference on Microwave and Millimeter Wave Technology, ICMMT 2023

作者： Dong, Jiantao Zhao, Hao Ceyear Technologies Co. Ltd Qingdao266555 China

ISBN: (纸本)9798350338874

To minimize the microwave power measurement device, a USB-based multi-path power detection solution is proposed to make accurate average power measurement in a compact design. Firstly, the design principles of analog channel, digital signal processing and USB interface for the whole power sensor is introduced. The focus is set to the multi-path diode design and the signal process. Some comparison results are provided to confirm its workability. This design features small size, light weight and programmable USB interface, which supports USBTMC protocol and thus simplifies the program procedure. This USB-based solution greatly simplifies the power measurement applications. © 2023 IEEE.

关键词： Digital signal processing

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Design and Application of a Virtual Simulation System Based on Wireless sensor Networks 16

Design and Application of a Virtual Simulation System Based ...

引用

16th IEEE international conference on Computational Intelligence and Communication Networks, CICN 2024

作者： Wang, Shaozheng Office of Academic Affairs Wuhan Business University Hubei Wuhan430056 China

ISBN: (纸本)9798331505264

With the rapid development of Wireless sensor Networks (WSNs), how to utilize their advantages for efficient simulation in multiple fields has become a current research hotspot. Wireless sensor networks have been widely used in environmental monitoring, military applications, medical health, and other fields due to their low cost, low power consumption, and strong self-organizing ability. However, due to the complexity and dynamism of WSNs, how to effectively simulate and emulate them to optimize network performance and save resources has become an important research topic. This study innovatively designed an integrated WSNs virtual simulation system that integrated sensor energy consumption, communication protocols, network topology, and dynamic environment simulation, significantly improving simulation accuracy and reliability. It adopts a modular architecture to construct a flexible and scalable simulation framework, which can efficiently operate in multiple scenarios. Although Strategy B lacks control accuracy, it has the lowest energy consumption (480 kWh), reflecting efficient energy management. Experimental results have shown that the system effectively balances accuracy and efficiency, providing solid support for WSNs design optimization, reducing testing costs, promoting protocol algorithm performance evaluation, adapting to technological evolution, and supporting applications such as smart cities and environmental monitoring. © 2024 IEEE.

关键词： Energy efficiency

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Analysis of methods and technologies used to predict and detect fires in forestry 21

Analysis of methods and technologies used to predict and det...

引用

21st international conference on Emerging eLearning technologies and applications, ICETA 2023

作者： Janovec, Michal Papan, Jozef University of Žilina Žilina Slovakia

ISBN: (纸本)9798350370690

To ensure early detection of fires, various methods, including artificial intelligence (Al), Wireless sensor Networks (WSN), and machine learning, are recommended. The most effective approach for safeguarding forestry is through prediction and the early identification of vulnerable areas within forests where ignition is likely to occur. This article provides an overview of various methods, algorithms, and theories employed for early fire detection in forestry, as well as fire prediction. It offers insights into the utilization and accuracy of individual techniques, methods, and algorithms developed for predicting and monitoring forest fires. In this article, we present various used methods/algorithms or theories that are used for early fire detection in forestry as well as its prediction. We will describe the use as well as the accuracy of the available individual options, methods and algorithms designed for the prediction and recording of forest fires. © 2023 IEEE.

关键词： Machine learning

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Ensem-EnsemHAR: Human Activity Recognition using Ensemble of Ensemble Methods and Smartphone sensor Data 15

Ensem-EnsemHAR: Human Activity Recognition using Ensemble of...

引用

15th international conference on Computing Communication and Networking technologies, ICCCNT 2024

作者： Mohidul Islam, S.M. Talukder, Kamrul Hasan Computer Science and Engineering Discipline Khulna University Khulna Bangladesh

ISBN: (纸本)9798350370249

Recognizing human activity has many applications in real life such as in biometrics, military, security, medical care applications, etc. In this paper, we proposed a new activity recognition method using the voting fusion of various ensemble methods. The data are subject-wise split into training and test sets to accomplish a person-independent recognition model. As base ensemble methods we have used random forest, extra-trees, AdaBoost, Histogram-based Gradient Boost, and XGBoost classifier. The hyper-parameters of base ensemble methods are fine-tuned using four different methods: RandomizedSearchCV, HalvingRandomSearchCV, GridSearchCV, and HalvingGridSearchCV. The recognition accuracies of each base ensemble for various parameter tuning techniques as well as for scikit-learn default values of the parameters are compared and we selected those values of hyper-parameters for which we obtained the highest recognition accuracy. Then the base ensembles are used in a voting ensemble which provides the final recognition result. The prediction results show the robustness of the proposed method to many similar existing methods, especially for unbalanced datasets. ©2024 IEEE.

关键词： Smartphones

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Investigation on Indoor Detection and Tracking of People using IWR1642 mmWave sensor 3

Investigation on Indoor Detection and Tracking of People usi...

引用

3rd international conference on Smart technologies, Communication and Robotics, STCR 2023

作者： Haritha, J. Pravin Savaridass, M. Sowntharya, V. Kowshika, R. Hemavardhini, S. Bannari Amman Institute of Technology Eie Tamilnadu India

ISBN: (纸本)9798350370867

There are several challenges associated with investigation in indoor detection and tracking of people using mm Wave sensors. One of the significant obstacle is the increased noise level and interference that can be present in indoor environments. Then it leads to false readings and false alarms. Advanced signal processing techniques such as beamforming and filtering are used. Another challenge is the need for a large number of sensors to cover the entire indoor area. This can be expensive and difficult to implement in practice. To address this, researchers are exploring to reduce the number of sensors required and they increased detection accuracy by employing cutting-edge algorithms and deep learning methods. Various applications such as home automation, advanced driver assistance system (ADAS), security, and healthcare that needs people count and detect the motion of people or object can use this advanced technology mmWave sensor. These mmWave sensors can provide better performance between the frequency ranges of 30 GHz to 300 GHz and can penetrate materials such as walls and clothing, making them suitable for indoor applications. The basic principle of indoor detection and tracking using mmWave sensors is by measuring the time taken by the radio waves to travel to the object from the transmitter antenna and reflected back to the receiver antenna. By analysing the reflected signals, it is possible to track and locate people in a particular specified area. © 2023 IEEE.

关键词： Electrocardiograms

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