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检索条件"任意字段=3rd IEEE International Conference on Distributed Computing in Sensor Systems"

共 5112 条记录，以下是1-10 订阅

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The Application of Digital Empowerment Combined with Intelligent Algorithms of Computer Technology in Decision Support systems 3

The Application of Digital Empowerment Combined with Intelli...

引用

3rd international conference on Integrated Circuits and Communication systems, ICICACS 2025

作者： Lu, Wan Chen, Li Gao, Fei Wang, Chang Wuhan Windoor Information & Technology Co. Ltd Hubei Wuhan China

ISBN: (纸本)9798331508456

Traditional decision support systems (DSS) show obvious limitations in dealing with increasingly complex and dynamic decision-making scenarios. By integrating graph neural networks (GNNs) and expert systems (ESs), this paper constructs a new IDSS framework aimed at improving decision-making efficiency and accuracy. In terms of research methods, large-scale distributed computing is performed in the cloud based on parallel computing technology;the logical reasoning of expert systems and the self-learning ability of graph neural networks are combined to achieve dynamic updates and efficient processing of data by unstructured knowledge bases. Compared with traditional DSS, the accuracy of IDSS based on the fusion of GNNs and ES in financial forecasting and risk assessment scenarios is improved to more than 90%, and resource utilization is significantly optimized. This study shows that the integrated application of intelligent algorithms has broad prospects in improving the dynamic adaptability of decision support systems and coping with complex decision-making environments. © 2025 ieee.

关键词： distributed cloud

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Quality of Service in Wireless sensor Networks: A Comparison of Routing Protocols based on Machine Learning 3

Quality of Service in Wireless Sensor Networks: A Comparison...

引用

3rd international conference on Electronics and Renewable systems, ICEARS 2025

作者： Prabha, K. Lakshmi Vijayasri, P. Saumiya, S. Chennai Institute of Technology Department of Electronics and Communication Engineering Chennai India

ISBN: (纸本)9798331509675

This paper focuses on the improvement of Quality of Service (QoS) in Wireless sensor Networks by using Machine Learning (ML) techniques to optimize routing protocols. It addresses the essential QoS challenges such as network lifespan, energy efficiency, delay minimization, and packet loss reduction using ML-based methods against those of conventional routing techniques. The study sheds light on how ML could be used to detect and overcome bottlenecks in the performance of a network to improve the overall efficiency. Simulation results show the massive improvements in QoS parameters, thereby strongly reaffirming the feasibility and potential of the ML-driven approaches to overcome the inherent limitations of traditional routing protocols in WSNs. © 2025 ieee.

关键词： Packet loss

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Automated Mining Equipment Monitoring: Enhancing Efficiency through sensor Technology and Predictive Maintenance 3

Automated Mining Equipment Monitoring: Enhancing Efficiency ...

引用

3rd international conference on Electronics and Renewable systems, ICEARS 2025

作者： Dharun Anand, S. Divakar, S. Cephas, I. Ganiss Roger, L. St. Joseph's Institute of Technology Department of Electrical and Electronics Engineering OMR Chennai India

ISBN: (纸本)9798331509675

The mining industry is pivotal to the economy, yet it faces significant challenges in maintaining equipment reliability and efficiency. Downtime of machinery can lead to substantial financial losses, operational delays, and safety risks. Mining operations are inherently complex, involving significant investments in machinery and equipment [1]. The efficiency and reliability of mining equipment are crucial for maintaining operational profitability and safety. With advancements in sensor technology and data analytics, automated equipment monitoring systems are becoming pivotal in enhancing operational effectiveness. This paper presents a comprehensive design for a system that utilizes sensors for real-time monitoring of mining equipment performance and health. By implementing predictive maintenance alerts, this system aims to mitigate downtime and enhance operational efficiency in mining operations [2]. © 2025 ieee.

关键词： Predictive maintenance

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Dynamic Topology Optimizing Magnetic Circuits for Underwater systems for Improved Performance and Efficiency 3

Dynamic Topology Optimizing Magnetic Circuits for Underwater...

引用

3rd international conference on Electronics and Renewable systems, ICEARS 2025

作者： Sathish, K. Saveetha School of Engineering Department of Electronics and Communications Engineering Chennai602105 India

ISBN: (纸本)9798331509675

This study explores the dynamic topology optimization of magnetic circuits for underwater systems, aiming to enhance both performance and efficiency through advanced computational techniques. By optimizing the magnetic flux density, minimizing material volume, and improving the BL (force) factor, the methodology ensures superior system functionality. The results reveal significant achievements, including a magnetic flux density of up to 1.8 Tesla, a 30% reduction in material volume, and a 25% enhancement in the BL factor, enabling higher electromagnetic force generation. The optimization framework also successfully satisfies threshold conditions for magnetic saturation and structural integrity, demonstrating its robustness and suitability for underwater environments. These findings underscore the transformative potential of topology optimization in designing sustainable and efficient magnetic systems, especially for operation in challenging underwater conditions. © 2025 ieee.

关键词： Wireless sensor networks

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Detection of Moving Objects with Ultrasonic Radar 3

Detection of Moving Objects with Ultrasonic Radar

引用

3rd international conference on Intelligent systems, Advanced computing, and Communication, ISACC 2025

作者： Nalla, Suresh Rakshitha, K. Kumar, K. Sai Samad, M.D. Nalla Narasimha Reddy Education Society's Group of Institutions ECE Dept Telangana Hyderabad 500088 India

ISBN: (纸本)9798331523893

An electronic device such as a radar is one which uses electromagnetic waves to measure the height, range, direction, or the speed of an object, which could be either static or in motion. There is a growing demand for efficient object detection systems in robotics, autonomous vehicles, and smart surveillance. This paper presents an ultrasonic sensor-based system for object detection in 360-degrees. The system is supposed to provide continuous rotation during which the environment would be fully scanned so that immediate detection of different objects of metallic as well as non-metallic can be done. Experimental results demonstrate the system's capability to accurately detect objects at various distances and orientations with a focus on minimizing measurement errors and enhancing detection efficiency. Finally, the proposed method significantly improves the reliability of object detection in dynamic environments. © 2025 ieee.

关键词： Arduino Uno 328 Buzzer Geared motor Java Application LED Motor Driver Ultrasonic sensor

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Energy-Efficient Routing Optimization for IoT-Based Multilevel Heterogeneous Wireless sensor Networks using Firefly Algorithm and Hybrid Clustering 3

Energy-Efficient Routing Optimization for IoT-Based Multilev...

引用

3rd international conference on Electronics and Renewable systems, ICEARS 2025

作者： Shilpa, Challa Venkata Ashokkumar, N. Srinivas, Cherukuri Reddy, Guttireddy Krishna Chaitanya Gowd, Chitrala Rajasekhar Rao, Y. Mallikarjuna Department of Ece AndhraPradesh Tirupati517102 India Santhiram Engineering College Department of Ece Andrapresh Nandyal India

ISBN: (纸本)9798331509675

Based on the Internet of Things (IoT) the heterogeneous wireless sensor networks (HWSN) have gained popularity and are crucial for developing a variety of human-centered applications. The researchers have proposed a number of ways for energy usage minimization and achieve energy-efficient network operations but most of these attempts concentrate on using the clustering technique, although it is very effective but most of them require the recurrent cluster creation which draws a lot of energy from nodes throughout the clustering process. In this work, an Energy-Efficient Hybrid Clustering Technique (EEHCT) has been presented for IoT-based HWSN and Firefly Optimization (FFO) to optimize the routing. The nodes energy usage is ideal when the route to Base Station (BS) is optimal increasing the number of packets transmitted and alive nodes in the network and performed 90.27% than the existing methods in terms of network lifetime. © 2025 ieee.

关键词： Energy utilization

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Enhanced Clustering Framework for Unveiling Hidden Patterns in IoT-Based Structured and Unstructured Data 3

Enhanced Clustering Framework for Unveiling Hidden Patterns ...

引用

3rd international conference on Intelligent systems, Advanced computing, and Communication, ISACC 2025

作者： Das, Prabhat Kovuri, Karthik Saha, Sajal The Assam Kaziranga University Department of IT India Adamas University Department of CSE India The Assam Kaziranga University Department of CSE India

ISBN: (纸本)9798331523893

Clustering algorithms play a pivotal role in uncovering hidden patterns and relationships within diverse datasets. This study discusses about an enhanced real-time clustering approach based on the Birch methodology, optimized for analyzing both structured and unstructured data. Structured data, consisting of IoT sensor readings, and unstructured image data, captured using Raspberry Pi devices deployed in various locations, were analyzed to identify meaningful patterns. For structured data, the algorithm effectively clustered environmental parameters, revealing correlations and anomalies. For unstructured data, high-dimensional image features extracted using a pre-trained VGG16 model were clustered, uncovering patterns in texture, color, and structure. Experimental results demonstrate the algorithm's scalability and efficiency, achieving high-quality clusters with average Silhouette Scores of 0.87 and 0.81 for structured and unstructured datasets, respectively. These findings highlight the algorithm's adaptability and its potential for real-time analytics in diverse applications such as environmental monitoring and image-based decision-making systems. © 2025 ieee.

关键词： BIRCH Clustering IoT sensor Data Structured Data Unstructured Data

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A sensor-Driven Automated Hydroponic System for Optimized Plant Growth in Diverse Environments 3

A Sensor-Driven Automated Hydroponic System for Optimized Pl...

引用

3rd international conference on Intelligent and Innovative Technologies in computing, Electrical and Electronics, IITCEE 2025

作者： Joshitha, C. Ranga, Bobba Pandu Reddy, Bandi Harshini Nitin Koneru Lakshmaiah Education Foundation Department of Electronics and Communication Engineering Telangana Hyderabad500075 India

ISBN: (纸本)9798331515911

This research paper presents the design and implementation of an automated hydroponic system capable of managing both closed and open setups in indoor and outdoor environments. The system integrates sensors and microcontrollers to monitor, control, and display key parameters like temperature, humidity, Total Dissolved Solids (TDS) in the nutrient solution, water level, and pH. Through automated monitoring and control, it reduces the need for human intervention, ensuring optimal growth conditions and continuous plant health. The project is driven by the vision of enabling agriculture in any environment, regardless of geographical constraints. Hydroponics, a soil-less method of growing plants, forms the core of the system, allowing for cultivation beyond traditional soil-based farming. By applying these techniques, the system aims to overcome the limitations of conventional agriculture, enabling the growth of various plant species in diverse locations. Through the integration of microcontrollers and sensors, this automated hydroponic system ensures continuous monitoring and precise control of environmental conditions, significantly reducing the need for manual intervention. This research contributes to the advancement of agricultural technology by providing a sustainable solution to enhance food production while addressing the challenges faced by traditional farming. By leveraging automation and sensor technology, the system optimizes resource usage, reduces environmental impact, and empowers individuals to cultivate crops with minimal expertise. © 2025 ieee.

关键词： Hydroponics

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Cloud-Enhanced Transfer Learning Framework for Medical Image Analysis: Advancing Diagnostic Speed and Accuracy in Healthcare 3

Cloud-Enhanced Transfer Learning Framework for Medical Image...

引用

3rd international conference on Integrated Circuits and Communication systems, ICICACS 2025

作者： Prabu, S. Chandra, N. Subhash Bhavani, M. Varma, V. K. Chaitanya Soni, Mukesh Mahendra Institute of Technology Department of Electronics and Communication Engineering Namakkal India Cvr College of Engineering Department of Computer Science and Engineering Mangalpalle India Rajalakshmi Institute of Technology Department of Artificial Intelligence and Data Science Chennai India Sagi Rama Krishnam Raju Engineering College Department of Mechanical Engineering Bhimavaram India Dr. D. Y. Patil Vidyapeeth Dr. D. Y. Patil School of Science & Technology Pune India

ISBN: (纸本)9798331508456

When it comes to medical image analysis, problems arise due to the scarce amount of data and computational resources in medical environments. This is because, as earlier stated, cloud settings demand efficient models capable of delivering more reliable diagnostic results without straining the cloud's computing resources. In this work, we presented a transfer learning based on DenseNet-201 as well ResNet-152 architectures with a new large dataset containing 15,000 medical images of different modality. By utilizing the distributed cloud computing and hypermeters precision strategy, the proposed model was found to have 95.8 % of accuracy, 94.2% sensitivity, and 96.3%specificity. It also reduced the processing time by sixty-eight percent over standard methods across the facilities. Five different datasets validated the proposed approach, achieving an external accuracy of 92.4%, indicating improved generalization performance. The enhancement of accuracy to approximately 90% and the reduction in required computation demonstrate its feasibility for extensive clinical applications on the cloud, spanning across hospitals. © 2025 ieee.

关键词： distributed cloud

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Design and Computational Study of a Two Dimensional Photonic Crystal Based Ethanol sensor 3

Design and Computational Study of a Two Dimensional Photonic...

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3rd international conference on Integrated Circuits and Communication systems, ICICACS 2025

作者： Sreekanth, D. Soma, Savita Sonth, Mahesh V. Guru Nanak Dev Engineering College Bidar Visvesvaraya Technological University Karnataka Belagavi India CMR Technical Campus Hyderabad India Guru Nanak Dev Engineering College Department of Ece Bidar India Secs Jspm University Department of E&tc Pune India

ISBN: (纸本)9798331508456

This research article provides a computational study of light interaction with two dimensional photonic crystal (PhC) structure. This PhC structure is used to measure ethanol percentage in liquid water by identifying and computing mid gap wavelength shift. Analysis of the Maxwell's equations that govern the photon behaviour in the periodic structure is discussed in detail for PhC structures. The photonic band gap (PBG) which prohibits the photon momentum in certain directions in the crystal is computed using plane wave expansion (PWE) method by deriving solutions to the eigenvalue equation. A two dimensional (2D) PhC structure is designed by taking 18 × 17 number of holes on a dielectric slab. This holes on the dielectric configuration is used to sense the ethanol level in liquid water. The PBG width for the design in transverse electric mode is [ωa/2πc] ranging from 0.3841 to 0.4428. The band gap size Δλ 480 nm and mid gap wavelength λc= 2391.2 nm is achieved from the structure. The sensor achieves a sensitivity of 10645.24 nm/RIU and a transmission ratio more than 94%. This structure is a suitable candidate for ethanol sensing applications as it offers a wide bandgap for light propagation. © 2025 ieee.

关键词： Eigenvalues and eigenfunctions

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