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检索条件"任意字段=2nd IEEE International Conference on Distributed Computing in Sensor Systems"

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2nd ieee international conference on distributed computing and Electrical Circuits and Electronics, ICDCECE 2023

2nd IEEE International Conference on Distributed Computing a...

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2nd ieee international conference on distributed computing and Electrical Circuits and Electronics, ICDCECE 2023

ISBN: (纸本)9798350347456

The proceedings contain 295 papers. The topics discussed include: deep learning & computer vision integrated smart voting system;performance analysis of machine learning algorithms with hyperparameter tuning for diabetes prediction;transient analysis of motor terminal voltage, common mode voltage and bearing voltage in 2-level and multilevel PWM inverter fed induction motor with long cable;comparative analysis of phase/frequency detector in a complete PLL system;a research on various security aware mechanisms in multi-cloud environment for improving data security;network traffic virtualization using Wireshark and Google maps;cluster enabled routing algorithm for wireless sensor networks: an optimization and future prospective;detection and recognition of animals using Yolo algorithm;voltage improvement and loss reduction by placement and sizing of DG using grid oriented multi objective particle swarm optimization;prediction of heart disease using naive bayes and particle swarm optimization (PSO) method;lane detection using video processing for robot cars;convolutional neural network for printed circuit board verification;and multiple disease prediction based on user symptoms using machine learning algorithms.

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An O(1)-rounds Deterministic distributed Approximation Algorithm for the Traveling Salesman Problem in Congested Clique 20

An O(1)-rounds Deterministic Distributed Approximation Algor...

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20th Annual international conference on distributed computing in Smart sensor systems and the Internet of Things (DCOSS-IoT)

作者： Saikia, Parikshit Natl Inst Technol Silchar Assam India

ISBN: (纸本)9798350369458;9798350369441

We study the Traveling Salesman Problem (TSP) in the Congested Clique Model (CCM) of distributed computing. We present a deterministic distributed algorithm that computes a tour for the TSP using O(1) rounds and O(m) messages for a given undirected weighted complete graph of n nodes and m edges with an approximation factor 2 of the optimal. The TSP has wide applications in logistics, planning, manufacturing and testing microchips, DNA sequencing etc., and we claim that our proposed O(1)-rounds approximation algorithm to the TSP, which is fast and efficient, can also be used to minimize the energy consumption in Wireless sensor Networks.

关键词： Traveling Salesman Problem distributed computing Approximation Congested Clique

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Cluster Enabled Routing Algorithm for Wireless sensor Networks: An Optimization and Future Prospective 2

Cluster Enabled Routing Algorithm for Wireless Sensor Networ...

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2nd ieee international conference on distributed computing and Electrical Circuits and Electronics, ICDCECE 2023

作者： Korishetty, Sharanu Jawaligi, Shivkumar S. Sharnbasva University Dept.of e & Ce Kalaburagi India

ISBN: (纸本)9798350347456

Devices with sensors are rapidly becoming indispensable. As the technology behind sensors has improved, a wide variety of sensor-based automated systems have emerged. By relaying data from sensors to actuators, these systems can perform actions automatically. Researchers face difficulties in obtaining long-lasting efficacy from sensor nodes into wireless sensor networks (WSNs) because of inadequate resources, energy constraints, and interference. For WSNs to continue operating for as long as possible, it is essential that their limited supply of energy be conserved. technique to organize groups of sensor nodes into clusters of varying sizes, each of which will then send its data on to the central station. First, the CEOMS algorithm build energy density task of the network nodes, & using the energy density function, it designates the sensor nodes having maximum left-over energy like cluster heads. © 2023 ieee.

关键词： sensor nodes

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An Innovation of distributed Scheduling and QoS Localized Routing Scheme for Wireless Industrial sensor Network 2

An Innovation of Distributed Scheduling and QoS Localized Ro...

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2nd ieee international conference on distributed computing and Electrical Circuits and Electronics, ICDCECE 2023

作者： Ravishankar, S. Kanniga, Devi Department of Electronics and Communication Engineering Bangalore India Bangalore India

ISBN: (纸本)9798350347456

A novel strategy for ensuring reliable and effective communication between sensor nodes and the industrial control systems is the QoS (Quality of Service) Localized Routing scheme for Wireless Industrial sensor Networks. This plan is built on the idea of localized routing, a routing technique based on the network's local topology. This system enables effective network performance monitoring and may be used to give QoS assurances to apps that need them. In order to regulate the network, centralized scheduling methods rely on a centralized controller. This controller is responsible for making decisions about the scheduling of resources, such as frequency allocation and transmission power. These algorithms offer a number of advantages, such as scalability, reliability, and security. However, they can be difficult to implement in large networks and may require significant amounts of communication and computation resources. distributed scheduling algorithms, on the other hand, do not rely on a centralized controller. Instead, they use distributed algorithms to make scheduling decisions. These algorithms are typically more efficient and require less communication and computation resources. They are also better suited to large networks, since they do not require a centralized controller © 2023 ieee.

关键词： sensor nodes

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Evaluation of Occupancy Detection with distributed Environmental sensors for IoT Applications 20

Evaluation of Occupancy Detection with Distributed Environme...

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20th Annual international conference on distributed computing in Smart sensor systems and the Internet of Things (DCOSS-IoT)

作者： Bovo, Matteo Agyeman, Rockson Arif, Muhammad Rinner, Bernhard Univ Udine Dipartimento Matemat Informat & Fis Udine Italy Univ Klagenfurt Inst Networked & Embedded Syst Klagenfurt Austria AAU SAL USE Lab Silicon Austria Labs Klagenfurt Austria

ISBN: (纸本)9798350369458;9798350369441

Occupancy refers to the presence of people in rooms and buildings. It is an essential input for IoT applications, including controlling lighting, heating, access, and monitoring space limitation policies. Occupancy information can also be used to improve users' comfort and to reduce energy waste in buildings. This paper evaluates the performance and resource consumption of recent machine learning techniques for occupancy detection and measurement by exploiting data from distributed environmental sensors. This evaluation is founded on a dataset captured by our dedicated sensor network for indoor monitoring, comprising temperature, humidity, and carbon dioxide (CO2) sensors. Using different sensor modalities and spatio-temporal data selections, we compare eight classification algorithms based on the accuracy achieved and the required runtimes. Binary classification for occupancy detection (OD) achieves accuracies over 90% for individual modalities and close to 100% for modality combinations. Multi-class classification for occupancy measurements (OM) shows as clear ranking of the sensor modalities, and gradient boosting algorithms are superior when combining sensor modalities and fusing data from multiple sensors.

关键词： sensor network indoor environments multiclass classification sensor fusion smart rooms

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distributed Data Acquisition: Enhancing sensor Networks with CAN Over Powerline (DC-BUS) for Efficient and Robust System Integration of Launch Vehicles 2

Distributed Data Acquisition: Enhancing Sensor Networks with...

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2nd international conference on Recent Trends in Microelectronics, Automation, computing, and Communications systems, ICMACC 2024

作者： Teja Pedapudi, Sai Ravi Chattopadhyay, Joydeb Skyroot Aerospace Private Limited Department of Avionics Hyderabad India

ISBN: (纸本)9798350366570

In traditional launch vehicle systems, a centralized data acquisition approach is followed, where various sensors are directly connected to a data acquisition system (DAQ) which supplies the excitation signal to the sensor and also does the job of filtering, signal conditioning, digitizing and packetization of the sensor signal which is then sent to Telemetry Package which in turn transmits this information to the ground stations via RF Signals. As the sensors and signal processing system are not collocated, there is a large amount of cabling from the sensor to the DAQ with power and signal causing weight penalty and Electromagnetic Interference (EMI) related issues. A failure of DAQ results in disruption of the entire sensor network. A smart sensor approach is reported in literature, in which the team developed a smart sensor integrated with an ADC and Microcontroller which transmits the data over an RS-485 Bus. Though this approach solves some of the aforesaid problems but needs additional powerlines distribution and suffers from undefined protocol. This paper proposes the use of Controller Area Network (CAN) Over Powerline (DC-BUS) bus for supplying power and acquiring data from the sensors and distributing the data acquisition resulting in a more reliable and robust sensor network for Launch Vehicles. © 2024 ieee.

关键词： CAN bus Data Acquisition System (DAQ) Launch Vehicles RS-485 sensors Weight reduction

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distributed Radar Angle Measurement Based on Deep Learning 2

Distributed Radar Angle Measurement Based on Deep Learning

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2nd international conference on Signal Processing and Intelligent computing, SPIC 2024

作者： Xiao, Jiacheng Zhang, Hongyan Li, Peng Lin, Sen Shenyang Ligong University School of Automation and Electrical Engineering Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China

ISBN: (纸本)9798350368888

distributed radar systems are pivotal in modern military and civilian contexts, with phased array radar technology greatly impacting angle measurement precision for target tracking and identification. This article presents a novel angle measurement approach for distributed radar systems, harnessing deep learning. This technique not only heightens angle measurement precision but also optimizes network efficiency, enhancing overall system performance. To validate our method, we conducted extensive experiments involving diverse angle targets, both large and small, consistently achieving outstanding results across scenarios. This underscores the method's exceptional accuracy and robustness in real-world situations. In summary, our innovative distributed radar angle measurement technique, driven by deep learning, promises improved accuracy and efficiency, bolstering the capabilities of distributed radar systems across applications. © 2024 ieee.

关键词： Angle measurement

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AI-Integrated sensor Data Analytics for Real-Time Decision-Making in Wireless sensor Networks 2

AI-Integrated Sensor Data Analytics for Real-Time Decision-M...

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2nd international conference on Machine Learning and Autonomous systems, ICMLAS 2025

作者： Wasim Haidar, S.K. Wilfred Blessing, N.R. Chaubey, Sudhakar Kumar Mehmood, Zahid Kavitha, S.J. Sutherlin Subitha, G. College of Computing and Information Sciences University of Technology and Applied Sciences Salalah Oman College of Computing and Information Sciences University of Technology and Applied Sciences Ibri Oman College of Computing and Information Sciences University of Technology and Applied Sciences Shinas Oman Vels Institute of Science Technology and Advanced Studies Department of Computer Science and Engineering Tamil Nadu Chennai India Stella Mary's College of Engineering Department of Computer Science and Engineering Aruthenganvilai India

ISBN: (纸本)9798331505745

The study compares the performance of Wireless sensor Networks (WSNs) with 20, 30, 40, and 50 nodes in real-time AI-enhanced sensor analytics using the AODV routing protocol. All configurations showed a consistent Packet Delivery Ratio (PDR) of 100%. However, the end-to-end delay increased slightly from 0.2 sec (20 nodes) to 0.3 sec (30, 40, 50 nodes), indicating that larger networks result in longer paths. Throughput decreased from 2560 bps at 20 nodes to 1706.67 bps in larger configurations, probable due to network congestion. Energy efficiency also decreased as the number of nodes increased, suggesting higher energy consumption per transmission. © 2025 ieee.

关键词： sensor nodes

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The Smart Optimization of Security systems in Wireless Personal sensor Networks 2

The Smart Optimization of Security Systems in Wireless Perso...

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2nd ieee international conference on distributed computing and Electrical Circuits and Electronics, ICDCECE 2023

作者： Das, Sunanda Sindhu Madhuri, G. Department of Computer Science and Engineering Bangalore India

ISBN: (纸本)9798350347456

Wireless personal sensor networks (WPSNs) are an emerging technology that provides a platform for monitoring and collecting data from a variety of sources. These networks are used to monitor environmental, health, and even lifestyle factors. As the use of WPSNs continues to grow, it is important to consider the security implications of using these networks. WPSNs rely on a variety of technologies to ensure secure communication between devices. These include encryption, authentication, secure protocols, and secure key management. Encryption is used to protect data from being intercepted and decoded by an unauthorized user. Authentication is used to verify the personality of the user and the device attempting to access the WPSN. Secure protocols are used to ensure secure communication between the devices and the server. Finally, secure key management is used to manage and store the encryption keys used to protect the data. In addition to encryption, authentication, and secure protocols, WPSNs must also be designed with a robust access control system. Access control systems are used to limit access to the WPSN based on user credentials and other factors. This assist ensure that authorized users alone can access the data stored on the WPSN. © 2023 ieee.

关键词： Authentication

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Artificial Intelligence Enabled Cognitive computing for AlN/β-Ga2O3 HEMT 2

Artificial Intelligence Enabled Cognitive Computing for AlN/...

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2nd international conference on Computational Intelligence, Communication Technology and Networking, CICTN 2025

作者： Verma, Yogesh Kumar Bhatia, Kamal Khushboo Bhanot, Aastha Roy, Trijeeta Sinha, Supriya Laksh School of Electronics and Electrical Engineering Lovely Professional University Jalandhar India School of Computer Science and Engineering Lovely Professional University Jalandhar India

ISBN: (纸本)9798331530389

HEMT devices have potential to handle the fast processing in applications such as real-time diagnostics utilizing the artificial-intelligence (AI) enhanced abilities. Along-with this HEMT devices can be extensively used in radar and defense systems to obtain faster response time and threat detection. This integration of AI and cognitive computing enables pattern-recognition and adaptive learning. The cognitive computing techniques integrated with HEMT enables the real-time analysis and predictions. For precise sensor data the amplification should be done at either no or very less noise levels. © 2025 ieee.

关键词： Gallium compounds

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