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Gray Wolf Optimization Algorithm to Enhance Data Aggregation in Wireless sensor Network 5

Gray Wolf Optimization Algorithm to Enhance Data Aggregation...

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5th international conference on Inventive Research in computing Applications, ICIRCA 2023

作者： Loganathan, Sathyapriya Victoria Jancee, B. Senkamalavalli, R. Subbu Lakshmi, T.C. Srm Institute of Science and Technology Department of Computing Technologies Tamil Nadu Kattankulathur India St.Joseph's College of Engineering Department of Electronics and Communication Engineering Tamil Nadu Chennai India East Point College of Engineering and Technology Department of Computer Science Engineering Karnataka Bangalore India Francis Xavier Engineering College Department of Information Technology Tamil Nadu Tirunelveli India

ISBN: (纸本)9798350321425

Wireless sensor networks (WSNs) have become increasingly popular as distributed systems using small, lightweight nodes with limited resources for monitoring environmental conditions or measuring physical parameters. To minimize energy utilization, data aggregation can be employed to reduce the data quantity forward to the base station (BS). To solve these issues, a Gray wolf optimization algorithm (GWOA) is proposed to enhance data aggregation in WSN. Increasing the network lifetime, node reliability, and throughput with the selection of best cluster heads (CHs) utilizing the Gray Wolf Optimization (GWO) algorithm is the major objective of this research. This approach selects the CH by applying the GWO algorithm established on the node remaining energy, available bandwidth, and distance. The GWO-based clustering protocol minimizes dead nodes and energy utilization and raises the clustering rounds and throughput. The simulation results demonstrate that the increases the node reliability and network throughput. © 2023 ieee.

关键词： Energy efficiency

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2023 19th international conference on Wireless and Mobile computing, Networking and Communications, WiMob 2023

2023 19th International Conference on Wireless and Mobile Co...

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19th ieee international conference on Wireless and Mobile computing, Networking and Communications, WiMob 2023

ISBN: (纸本)9798350336672

The proceedings contain 81 papers. The topics discussed include: outage performance of IRS-assisted underwater optical wireless communication systems over combined channel model;sensor-based wastewater monitoring framework to detect COVID-19;deep learning assisted channel estimation for cell-free distributed MIMO networks;multi-agent Q-learning for drone base stations;RF fingerprint-based identity verification in the presence of an sei mimicking adversary;analyzing the feasibility of privacy-respecting automated tracking of devices fleeing a burglary;security implications of a satellite communication device on wireless networks using Pentesting;deep learning assisted quality ranking for list decoding of videos subject to transmission errors;robotaxis as computing clusters: a stochastic modeling approach;chained estimation for data reduction-driven routing in wireless sensor networks;lightweight group pre-handover authentication scheme for aviation 5g air-to-ground networks;learning to detect wireless spectrum occupancy using clustering approaches;smartphone camera as a diagnostic tool for detection of pulse rate and blood oxygen concentration;density-aware reinforcement learning to optimize energy efficiency in UAV-assisted networks;area under time series transformation for home appliance classification;and a novel single grant-based uplink scheme for high throughput and reliable low latency communication.

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Detection and Classification of Human Activities using distributed Sensing of Environmental Vibrations

Detection and Classification of Human Activities using Distr...

引用

ieee international conference on Omni-Layer Intelligent systems (ieee COINS)

作者： Koch, Marcel Schlenke, Fabian Kohlmorgen, Fabian Kuller, Markus Bauer, Joerg Woehrle, Hendrik Dortmund Univ Appl Sci & Arts Dept Informat Technol Dortmund Germany

ISBN: (数字)9781665483568

ISBN: (纸本)9781665483568

The recognition of human activities in a smart home is an essential prerequisite in order to derive typical behaviors and needs of the inhabitants and adapt the functions of the smart home to them. Different sensor modalities, such as video or audio data in combination with machine learning methods can be used for this purpose. However, the use of video and audio data is associated with a strong infringement on the privacy of the inhabitants. In this paper, we present an alternative approach that uses vibrational data that is acquired by stationary wall-mounted sensors to detect a specific set of inhabitant activities using machine learning. We compare different neural-network based time series classifiers and show that is possible to detect the selected activities with up to 95% accuracy.

关键词： IoT Machine Learning Human Activity Recognition Edge computing

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Certain Investigation of Optimization Methods of sensor Nodes in Biomedical Recording systems 9

Certain Investigation of Optimization Methods of Sensor Node...

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9th international conference on Advanced computing and Communication systems, ICACCS 2023

作者： Ashokkumar, N. Pappa, C. Kanmani Siva Kumar, A. Srinivasan, Dhamodharan Vijay, M.M. Mohan Babu University Department of ECE Tirupati India Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Department of ECE Tamilnadu Chennai India SRM Institute of Science and Technology Department of Data Science and Business Systems Chennai India Sri Eshwar College of Engineering Department of Computer and Communication Engineering Tamilnadu Coimbatore India SCAD College of Engineering and Technology Department of ECE Tirunelveli India

ISBN: (纸本)9798350397376

Biosensors will monitor a patient's physiological signals (ECG, EEG, etc.) and send an alarm as soon as irregularities are discovered. Downsized biomedical sensors are the focus of this article, which explores innovative circuit approaches for miniaturised sensors. In order to demonstrate the proposed biomedical compression engine, ECG compression was applied and assessed. A MIP (mixed-integer programming model) is used to represent and solve the clustering issue based on the power consumption analysis. It follows that an architectural model that may be used to design ECG monitoring systems has been provided, as well as an in-depth study of the ECG monitoring system's value chain and a complete evaluation of relevant literature based on an expert classification. Time synchronisation and signal synthesis are the two stages of the distributed cooperative sensing algorithm's execution of ECG signal gathering. This method uses the mutation probability of each solution to prevent local convergence. © 2023 ieee.

关键词： Electrocardiograms

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A Virtual Sink-based Strategy for Reducing the Funneling Effect in ieee 802.15.4 DSME Networks

A Virtual Sink-based Strategy for Reducing the Funneling Eff...

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international conference on distributed computing in sensor systems (dcoss)

作者： Ivonne Andrea Mantilla González Volker Turau Institute of Telematics Hamburg University of Technology Hamburg Germany

ISBN: (数字)9781665495127

ISBN: (纸本)9781665495134

The MAC protocol ieee 802.15.4 DSME has features for WSNs to support exigent requirements such as high reliability and adaptability to dynamic traffic. This work introduces the concept of a virtual sink, which comprises the sink and its 1-hop neighbors, a.k.a. satellites, as the core of a strategy to alleviate the burden caused by the funneling effect in data collection scenarios. Our strategy enables the coexistence of a centralized scheduling algorithm at the virtual sink and a decentralized scheduling algorithm for the remaining nodes of the network. Through a simulative assessment, we compare the performance of the virtual sink-based strategy with the status quo of DSME via a decentralized slot scheduler TPS. Results show an improvement of the network throughput of up to 38% and a reduction of the energy consumption of about 30% at satellites.

关键词： ieee 802.15 Standard Wireless sensor networks Energy consumption Satellites Scheduling algorithms Throughput Media Access Protocol

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TeeSwap: Private Data Exchange using Smart Contract and Trusted Execution Environment 23

TeeSwap: Private Data Exchange using Smart Contract and Trus...

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23rd ieee international conference on High Performance computing and Communications, 7th ieee international conference on Data Science and systems, 19th ieee international conference on Smart City and 7th ieee international conference on Dependability in sensor, Cloud and Big Data systems and Applications, HPCC-DSS-SmartCity-DependSys 2021

作者： Chen, Peng Shi, Peichang Xu, Jie Fu, Xiang Li, Linhui Zhong, Tao Xiang, Liangliang Kong, Jinzhu College of Computer National University of Defense Technology National Key Laboratory of Parallel and Distributed Processing Changsha410073 China Zhejiang Lab Hangzhou311100 China Kylin Software Co. Ltd Changsha410073 China

ISBN: (纸本)9781665494571

With importance of data value is approved, data-sharing will create more and greater value has become consensus. However, data exchange has to use a trusted third party(TTP) as an intermediary in an untrusted network environment, which may lead to leakage of data privacy. In this paper, we design a system named TeeSwap, which uses smart contract to complete data exchange, and at the same time uses cryptographic algorithms and trusted execution environment (TEE) to ensure privacy in process of data transmission, verification and contract execution. Meanwhile, TeeSwap can ensure the credibility, fairness, integrity and privacy while data are shared in our system. In the end, we implement contracts about data market and data exchange. When confirming the data transaction, data market contract can automatically generate and deploy exchange contract, which can complete the data exchange authoritatively. © 2021 ieee.

关键词： Data privacy Smart contracts Data communication Cryptography

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RBCP: A Reputation-based Blockchain Consensus Protocol for Internet of Things 24

RBCP: A Reputation-based Blockchain Consensus Protocol for I...

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24th ieee international conference on High Performance computing and Communications, 8th ieee international conference on Data Science and systems, 20th ieee international conference on Smart City and 8th ieee international conference on Dependability in sensor, Cloud and Big Data systems and Application, HPCC/DSS/SmartCity/DependSys 2022

作者： Shang, Jiaze Lu, Tianbo Cai, Yingjie Luo, Shuang Jin, Zhaoxin School of Computer Science National Pilot Software Enginerring School Beijing University of Posts and Telecommunications Beijing China Beijing University of Posts and Telecommunications Key Laboratory of Trustworthy Distributed Computing and Service Ministry of Education Beijing China

ISBN: (纸本)9798350319934

The application of blockchain in the Internet of Things (IoT) solves the problem of centralization, enables data interaction of IoT nodes in untrusted environments. However, most of the blockchain consensus protocols are computationally expensive and poorly scalable, which cannot meet the current demand for low power consumption and low latency of IoT devices. Meanwhile, IoT nodes suffer from many malicious attacks. An effective reputation evaluation scheme is valuable for establishing a trusted, secure IoT environment with certain applications. In this paper, we propose RBCP, a novel reputation-based blockchain consensus protocol, and apply it to the IoT. The protocol divides IoT nodes into multiple regions, and consensus nodes in each region are selected based on real-time updated reputation values, which are used to participate in light PoW consensus and finally propose blocks. Then, we model the deposits and profits of the nodes as Stackelberg game and analyze the relationship between them. To evaluate our proposed protocol, we compare it with existing consensus protocols through several experiments. Our experimental results show that RBCP has advantages in terms of TPS, consensus time, and communication consumption, proving that it has low latency and less consensus time under the premise of sufficient security. © 2022 ieee.

关键词： Internet of things

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sensorimotor Correlation Using Printed Synaptic Transistors and Conditioning PCB

Sensorimotor Correlation Using Printed Synaptic Transistors ...

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2022 ieee international conference on Flexible and Printable sensors and systems (FLEPS)

作者： Liu, Fengyuan Baghini, Mahdieh Shojaei Chakraborty, Moupali Christou, Adamos Dahiya, Ravinder Univ Glasgow James Watt Sch Engn Bendable Elect & Sensing Technol BEST Grp Glasgow G12 8QQ Lanark Scotland

ISBN: (纸本)9781665442732

The advances in robotics are often inspired by biological systems, which have attained harmonised functionality and efficiency through billions of years of evolution. Motivated by the nature, this paper presents the realisation of sensorimotor correlation using printed synaptic transistor. While such a concept has drawn increasing attention recently, no report on the adopted technology details has been published. To this end, this paper specifically presents the technical elements for the practical realisation of the concept through printed synaptic transistor and the development of the conditioning printed circuit board (PCB) for operating the as-realised device. This work presents a possible roadmap for the future advancement towards e-Skin with neural-like processing capability through a heterogeneous integration of printed circuits on flexible PCBs.

关键词： Printed electronics sensorimotor correlation distributed computing synaptic transistor electronic skin

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Demo: RhythmEdge: Enabling Contactless Heart Rate Estimation on the Edge 8

Demo: RhythmEdge: Enabling Contactless Heart Rate Estimation...

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8th ieee international conference on Smart computing (SMARTCOMP)

作者： Hasan, Zahid Dey, Emon Ramamurthy, Sreenivasan Ramasamy Roy, Nirmalya Misra, Archan Univ Maryland Baltimore Cty Dept Informat Syst Ctr Real Time Distributed Sensing & Auton CARDS Mobile Pervas & Sensor Comp Lab Baltimore MD 21228 USA Singapore Management Univ Sch Comp & Informat Syst Singapore Singapore

ISBN: (纸本)9781665481526

In this demo paper, we design and prototype RhythmEdge [1], a low-cost, deep-learning-based contact-less system for regular HR monitoring applications. RhythmEdge benefits over existing approaches by facilitating contact-less nature, real-time/offline operation, inexpensive and available sensing components, and computing devices. Our RhythmEdge system is portable and easily deployable for reliable HR estimation in moderately controlled indoor or outdoor environments. RhythmEdge measures HR via detecting changes in blood volume from facial videos (Remote Photoplethysmography;rPPG) and provides instant assessment using off-the-shelf commercially available resource-constrained edge platforms and video cameras. We demonstrate the scalability, flexibility, and compatibility of the RhythmEdge by deploying it on three resource-constrained platforms of differing architectures (NVIDIA Jetson Nano, Google Coral Development Board, Raspberry Pi) and three heterogeneous cameras of differing sensitivity, resolution, properties (web camera, action camera, and DSLR). RhythmEdge further stores longitudinal cardiovascular information and provides instant notification to the users. We thoroughly test the prototype stability, latency, and feasibility for three edge computing platforms by profiling their runtime, memory, and power usage.

关键词： Heart rate Volume measurement Prototypes Estimation Cameras Ubiquitous computing Real-time systems

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Integrated Algorithm for Passive and Active Motion Artifact Removal in Photoplethysmography

Integrated Algorithm for Passive and Active Motion Artifact ...

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international conference on distributed computing in sensor systems (dcoss)

作者： Wilson A. Camargo-Gómez Claudia L. Garzón-Castro Annamaría Filomena-Ambrosio Engineering Faculty Research Group CAPSAB Universidad de La Sabana Chía Colombia International School of Economics and Administrative Sciences Research Group Alimentación Gestión de Procesos y Servicio Universidad de La Sabana Chía Colombia

ISBN: (数字)9798350369441

ISBN: (纸本)9798350369458

Within the extensive panorama of wearable devices worldwide, motivated by various factors that have driven the monitoring of physiological variables, the application of the photoplethysmography technique stands out. This technique presents a broad spectrum of applications for analyzing and detecting various components within the human body, employing non-invasive optical principles. These principles allow the quantification of the physiological characteristics of an individual. However, the technique is affected by the so-called motion artifacts, which are alterations that can compromise the accuracy and reliability of the signal *** counteract this phenomenon, this paper presents a custom-made algorithm which is part of a prototype under development. This algorithm incorporates a passive reduction system based on a differentiated use of the photodiodes, together with an active reduction system based on the application of analysis, decomposition and filtering algorithms, supported by the data from the built-in accelerometer, thus identifying and suppressing the disturbances present in the acquired *** results show that the algorithm worked efficiently on the wearable device, exhibiting positive results in terms of detection, analysis and reduction of artifacts. These results were congruent with the subsequent analysis of the acquired signal and acceleration values recorded by the accelerometer. However, it is imperative to continue the research to compare the values obtained by the prototype against clinically approved devices, this will allow to determine the reliability ranges and estimate the magnitude of the deviation between the data obtained and the data close to reality.

关键词： Performance evaluation Prevention and mitigation Prototypes Photoplethysmography Hardware Reliability Object recognition

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