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

共 9443 条记录，以下是1181-1190 订阅

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Hybrid Image Encryption for WISN in Privacy Protection and Security of Public Big Data Using Chaotic Maps

Hybrid Image Encryption for WISN in Privacy Protection and S...

引用

Advances in Modern Age technologies for Health and Engineering Science (AMATHE), international conference on

作者： Nikhitha Geddada Aditi Sahu Suseela G Jayshnav S Suchi Arora Department of Networking and Communications SRM Institute of Science and Technology Chennai India Department of Computing Technologies SRM Institute of Science and Technology Chennai India

ISBN: (数字)9798350371567

ISBN: (纸本)9798350371574

Image big data has become pervasive in today's world. Every day huge volumes of data are being transferred across systems. Significant advancements have been made in networking and file transfer technologies. Due to the remarkable expansion of network infrastructures, multimedia transmission has become inevitable. Image data is being produced at a faster rate and the variety of data types is expanding rapidly. A number of big data-related surveillance applications use wireless image sensor networks (WISN). Important and sensitive data must be hidden from different hackers trying to break into the system. So, encryption is used to hide sensitive information from various hackers. Lorenz attractor along with the chaotic maps are used to withstand statistical attacks. Dual confusion and dual diffusion are implemented so as to ensure maximum chaos and makes the encryption system strong against attacks. The pixels of the image are scrambled using logistic maps so that only authorized users can decipher it. Through the integration of tent map and logistic map, this study approaches an efficient image encryption algorithm.

关键词： Wireless communication Data privacy Wireless sensor networks Computer hacking Surveillance Big Data Encryption

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Optimizing Network Energy In Cloud-Assisted IOT With Wireless sensor Networks Using Similarity-Navigated Graph Neural Networks

Optimizing Network Energy In Cloud-Assisted IOT With Wireles...

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Advanced Computing technologies (ICoACT), international conference on

作者： S. Jamuna Rani D. Santhakumar Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences(SIMATS) Saveetha University Chennai TamilNadu India

ISBN: (数字)9798331509859

ISBN: (纸本)9798331509866

Wireless sensor Networks (WSNs) have been identified as important in cloud assisted internet of things (IoT) applications such as remote monitoring and energy saving. However, energy consumption and having limited network life time are still the major challenges in WSNs. Conventional methods of energy optimization does not achieve an optimal balance between avoiding overhead and effective communication. To overcome these drawbacks, this work presents a new Similarity-Navigated Graph Neural Network with Running City Game Optimizer (SNGNN-RCGO) model for energy optimization in IoT-WSN structures. It has a wireless sensor layer at the application tier, interconnecting layer at the middle tier, and the cloud layer at the software tier. SNGNN also reduces the energy usage by grouping nodes with similar nodes but excludes low energy node in the group. RCGO enable SNGNN hyperparameters tuning by exploiting exploration-exploitation trade-off while GBO enables efficient route and cluster head selection. In this regard, the proposed SNGNN-RCGO finds the highest residual energy (361.32 units) for node and network life time up to 1809 rounds with 195 alive nodes proving better energy efficiency. It also reduces the overall network overhead to 2 units and realizes the smallest end-to-end delay of 41.3 ms, which explains its efficiency and effectiveness for IoT and WSN. The proposed approach thus eliminates shortcomings of prior techniques since it enhances network energy efficiency and network lifetime with little added cost and complexity.

关键词： Wireless communication Wireless sensor networks Cloud computing Urban areas Games Graph neural networks Energy efficiency Complexity theory Internet of Things Optimization

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Energy Efficiency Optimization of Wireless sensor Networks with K-Means Integration

Energy Efficiency Optimization of Wireless Sensor Networks w...

引用

international conference on Advanced Communication technologies and Networking (CommNet)

作者： Adil Hilmani Yassine Sabri Abderrahim Maizate Siham Aouad Mohammed Koundi Fouad Ayoub LASTIMI High School of Technology Salé Mohammed V University Rabat Morocco Laboratory of Metrology and Information Processing (LMTI) FacuIty of Sciences Ibn Zohr University Agadir Morocco RITM ESTC/CED-ENSEM University Hassan II Casablanca Morocco Smart Systems Laboratory ENSIAS Mohamed V University Rabat Morocco ASE-Lab ENSA Ibn Tofail University Kenitra Morocco ERATIC Team LaREAMI Lab CRMEF-K Kenitra Morocco

ISBN: (数字)9798350367027

ISBN: (纸本)9798350367034

In wireless sensor networks (WSNs), optimizing energy consumption and ensuring efficient data transmission are crucial for network longevity and performance. This paper introduces an enhanced clustering technique for wireless sensor networks that aims to extend network lifetime and ensure reliable data delivery. Instead of regular K-Means clustering, we integrate the Silhouette score method to evaluate cluster quality and decide the optimal number of clusters. This improves how nodes are grouped together in the network. Additionally, we strategically select routing paths from cluster heads to the base station that minimize energy drainage. Comprehensive simulations show our dual optimization approach outperforms standard K-Means in terms of energy efficiency, stable network organization and effective data transmission and overall, the proposed improvements to clustering and routing significantly advance energy-constrained wireless sensor networks toward more sustainable and dependable real-world applications.

关键词： Wireless sensor networks Energy consumption Standards organizations Organizations Routing Energy efficiency Stability analysis Data communication Reliability Optimization

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Research on Signal Processing and sensor Fusion Technology in Electrical Engineering Automation

Research on Signal Processing and Sensor Fusion Technology i...

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IEEE international conference on Civil Aviation Safety and Information Technology (ICCASIT)

作者： Rong Chen Zhenjiang Vocational Technical College Zhenjiang China

ISBN: (数字)9798350389418

ISBN: (纸本)9798350389425

This study introduces an electrical measurement system grounded in multi-sensor fusion. Through the incorporation of information fusion techniques and parallel computing strategies, the system achieves reconstruction and optimization. The system is designed with a dynamic clustering algorithm that effectively merges data from various sensors, thereby enhancing both the precision and real-time performance of the measurements. To validate the system’s effectiveness, this paper conducts simulations and carries out detailed data analysis of the simulation outcomes. The findings demonstrate that the proposed sensor fusion approach substantially increases the measurement accuracy of the electrical measurement system while maintaining robust stability in challenging environments. Furthermore, the system’s parallel computing capabilities notably boost processing efficiency, reducing the time required for data handling. These outcomes indicate that the signal processing and sensor fusion technologies explored in this research hold significant potential for applications in electrical engineering automation, offering a solid theoretical foundation and technical support for future engineering implementations.

关键词： Electrical engineering Automation Heuristic algorithms Computational modeling Electric variables measurement Signal processing algorithms Clustering algorithms sensor fusion Signal processing Parallel processing

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Micro-Cantilever Capacitive sensor for Magnetic Field Measurement

Micro-Cantilever Capacitive Sensor for Magnetic Field Measur...

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5th international conference on Machine Learning and Big Data Analytics for IoT Security and Privacy, SPIoT 2024

作者： Xu, Changbao Feng, Qihui Zhang, Yide Xin, Mingyong Tang, Saiqiu Electric Power Science Research Institute Guizhou Power Grid Co. Ltd. Guiyang550002 China

From motor control to navigation systems, the accurate measurement of magnetic fields provides essential information for a variety of applications, and the development and application of magnetic field sensors has become one of the research areas of interest in the field of electrical engineering. With the development of technology and the diversification of application scenarios, the traditional magnetic field sensors based on the principles of Hall effect, magnetoresistive effect, etc. have shown their limitations in terms of high accuracy, miniaturization, and high sensitivity. In order to meet the needs of emerging applications, this paper proposes a micro-cantilever capacitive based magnetic field measurement sensor structure. The structure changes the capacitance of the cavity in the sensor by the vibration of the cantilever beam under the magnetic field, thus realizing the measurement of the magnetic field. We simulated the designed sensor using COMSOL Multiphysics software and the results show that the sensor has good magnetic field response and can be extended to industrial applications in power grids. © 2025 The Authors. Published by Elsevier B.V.

关键词： Magnetic field measurement

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UAV Based Fog Computing for IoT Networks 22

UAV Based Fog Computing for IoT Networks

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22nd OITS international conference on Information Technology, OCIT 2024

作者： Prasad, Jitendra Sai Annabathuni, Eeshatwayi Srivalli, Venkata padma Namburu, Sujitha Kumar, Ramesh Department of Computer Science and Engineering SRM University-AP Amaravati522 240 India

ISBN: (纸本)9798331510404

Fog computing using Unmanned Aerial vehicles is one of the most emerging technologies in the modern era. It has various advantages like high mobility, increased scalability, wireless connectivity, minimum man-power requirement, etc. Unmanned Aerial vehicles can act as fog devices between the Cloud and Internet of Things remote applications. It enhances the connectivity for the IoT devices available in remote areas by transferring the data to the cloud server in less time. In this paper, we propose algorithms that could be followed for the proper and optimal data transmission to the cloud from IoT remote applications via fog Nodes. © 2024 IEEE.

关键词： Wireless sensor networks

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EMG-based Wrong Posture Detection System using Raspberry Pi and Cloud-based Visualization

EMG-based Wrong Posture Detection System using Raspberry Pi ...

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Computing and Data Science (ICCDS), international conference on

作者： C.S. Manikandababu J.K. Ishvarya M Hiroshith JSP Arun Aakarshan Department of ECE Sri Ramakrishna Engineering College Coimbatore Tamil Nadu

ISBN: (数字)9798350365337

ISBN: (纸本)9798350365344

Human-computer interaction experts investigate posture detection with cutting-edge methodologies and electromyography (EMG) signals. This study presents an innovative system that provides users with real-time feedback via cloud visualization, electromyography (EMG) sensors, and a Raspberry Pi. To obtain more comprehensive data, sensor fusion methods integrate gyroscopes and accelerometers, while state-of-the-art machine learning algorithms are employed to improve the precision of posture detection. The proposed approach provides a precise and nonintrusive substitute for incorrect posture recognition to avoid the shortcomings of current technologies. The report emphasizes sensor integration, pattern recognition, and classification algorithms as critical elements in enhancing the system's dependability. In addition to strategically placed accelerometers, the methodology incorporates a deep learning framework of LSTM. Subsequent investigations should concentrate on developing real-time processing algorithms and exploring alternative sensor modalities to obtain more comprehensive data, given the promising practical applications of posture detection systems.

关键词： Accelerometers Cloud computing Machine learning algorithms Data visualization sensor fusion Electromyography sensor systems

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UAV Based Fog Computing for IoT Networks

UAV Based Fog Computing for IoT Networks

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Information Technology (OCIT), OITS international conference on

作者： Jitendra Sai Prasad Eeshatwayi Annabathuni Venkata Padma Srivalli Sujitha Namburu Ramesh Kumar Department of Computer Science and Engineering SRM University-AP Amaravati India

ISBN: (数字)9798331510404

ISBN: (纸本)9798331510411

关键词： Wireless communication Cloud computing Wireless sensor networks Scalability Autonomous aerial vehicles Internet of Things Servers Security Monitoring Edge computing

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Wireless sensor Networks Data Anomaly Detection: A Smart Approach

Wireless Sensor Networks Data Anomaly Detection: A Smart App...

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Intelligent technologies (CONIT), international conference on

作者： Ahshanul Haque Hamdy Soliman Md Naseef-Ur-Rahman Chowdhury Department of Computer Science New Mexico Tech New Mexico USA

Wireless sensor Networks (WSNs) are at the core of many critical civil and military applications where they are very amenable for deployment in some harsh/unsafe environments. The WSNs sensed data integrity and validity are very important in all applications, yet vital in some civil and military applications, where any faulty data might result in very serious consequences such as loss of human lives and precious commodities. In WSNs, sensors might report anomalous readings due to many factors related to their environment of deployment, energy level, computing capabilities, hardware failure, wireless media vulnerabilities, etc., which is a serious challenge. Hence, the need arises for immediate detection of such anomalies at the WSNs sink node, to guarantee the processing of accurately sensed data. In this paper, we devise a smart model to address a solution to the aforementioned problematic challenge. In our approach, we utilize different Machine Learning (ML) models in the process of anomaly detection in sensed data. The performances of the utilized ML models are compared, and the top performance model is incorporated into our smart anomaly detection model (SADM). In the design process of our new SADM, we experimented with over 2.2 million sensed data records from the Intel-MIT lab dataset to train and test many different ML models. The preliminary results of our SADM detection accuracy are very promising, which is very encouraging to proceed in this research direction, with different encoding data sets, to generalize the utilization of the new SADM model over a wider set of WSNs applications.

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Localization in Wireless sensor Network: Techniques, Algorithms Analysis and Challenges 9

Localization in Wireless Sensor Network: Techniques, Algorit...

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9th IEEE international conference on Reliability, Infocom technologies and Optimization (Trends and Future Directions), ICRITO 2021

作者： Kaur, Bhupinder Prashar, Deepak Lovely Professional University Phagwara India

ISBN: (纸本)9781665417037

Appearance of Wireless sensor Network in contrasting fields is vital and in current era the use of sensors in contrasting applications is immense. Various application such as in dense forest area, military area, medical field, smart watches and in human tracking sensors are going to be a used. But sensed information is not useful until the action taker is not aware about the location of the event. Researchers have done the work on this problem that is known as localization, in WSN others challenges are also there. In this article we are summarizing the WSN, Localization process various techniques for localization and comparison of those techniques, different existing localization algorithm, and issues of localization in WSN. © 2021 IEEE.

关键词： Location awareness Wireless communication Wireless sensor networks Forestry Network security Data collection Market research

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