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9th International Conference on communication and electronics Systems, ICCES 2024

作者： Kannappan, A. Kolagani, Nagesh Kandaswamy, Vijay Anand Vishnupriyan, J. Saveetha School of Engineering Simats Department of Electronics and Communication Engineering Chennai India Saveetha School of Engineering Simats Department of Computer Science and Engineering Chennai India Chennai Institute of Technology Department of Electrical and Electronics Engineering Chennai India

ISBN: (纸本)9798350377972

Physically Underwater communication adopt the bio inspired genetic bee colony formed network communication structures. Underwater environment condition communication is established between the Transmitting node and in between several clustering relay nodes to reach receiver nodes. Transmitting nodes are placed on sea bed areas at certain depth and clustering relay nodes are placed in various underwater depth conditions dipping the sensor nodes. Also, underwater battery life is very hard and battery replacement is a very tough task. Hence, an alternate solution of optimization battery capacity utilization is used. This optimization algorithm improves Packet delivery ratio by comparing genetic bee algorithm with Ant colony algorithm. Hence, equivalence of two algorithms implemented in underwater conditions. The genetic bee colony Algorithm produces better output results more than 4 to 6 percentage compared to ant colony parameter output. The genetic bee colony algorithm offers a maximum clustering node technique compared to ant colony algorithm. Its greater support for saving energy consumption extending battery life. © 2024 IEEE.

关键词： Ant colony optimization

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SDN-enabled Smart Building Energy Management for Hybrid Solar-Geothermal Integrated System 2

SDN-enabled Smart Building Energy Management for Hybrid Sola...

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2nd IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation, IATMSI 2024

作者： Jahan, Nushrat Abir, Md. Abu Baker Siddiki Khulna University of Engineering & Technology Department of Electrical and Electronic Engineering Khulna9203 Bangladesh Khulna University of Engineering & Technology Institute of Information and Communication Technology Khulna9203 Bangladesh

ISBN: (纸本)9798350360523

To provide a reliable, resilient, cost-effective, and environment friendly energy solution, the hybrid solar-geothermal integrated energy system has shown promises in recent time. By addressing the limitations of conventional nonrenewable energy systems, the combination of solar and geothermal energy can offer a more sustainable, efficient, and secure source of energy for future. However, implementing a building energy management model for a hybrid solar geothermal integrated system poses several issues, such as integration complexity, control strategy complications, optimal resource allocation, data accessibility and reliability, and energy storage challenges. As a result, a centralized controlled, programmable, and robust networking platform is required for hybrid solar-geothermal integrated system. In this regard, software-defined networking (SDN)-based energy management system (EMS) can be employed that can offer programmable, autonomous, and intelligent decision-making features. Therefore, to ensure intelligent harmonize renewable energy sources, optimize energy distribution, and enhance energy efficiency, this paper provides an SDN-enabled smart building EMS for hybrid solar-geothermal integrated system. Additionally, a new robust energy management algorithm is also developed which can dynamically manage the hybrid EMS utilizing the real-time date. Moreover, for evaluating the performance of the SDN-empowered architecture, an investigation based on simulation is executed. which demonstrates that the proposed model is capable of generating 1000 W solar energy as well as the geothermal system provides a daily heat exchange rate of 45.12 W. © 2024 IEEE.

关键词： Energy management systems

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SAHARA: A Cloud - based Remote Health - Vitals Monitoring System 2

SAHARA: A Cloud - based Remote Health - Vitals Monitoring Sy...

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2nd International Conference on Networking, Embedded and Wireless Systems, ICNEWS 2024

作者： Gupta, Arbind Kumar Nagaraja, J. Padma, Chennagiri Rajarao Mahesh Kumar, N. Roopa, M.S. Dayananda Sagar College of Engineering Department of Computer Science and Engineering Bengaluru India Dayananda Sagar College of Engineering Department of Medical Electronics Engineering Bengaluru India Dayananda Sagar College of Engineering Department of Electronics and Communication and Engineering Bengaluru India Nitte Meenakshi Institute of Technology Department of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798350367461

The healthcare landscape in India, like in many countries, faces disparities between urban and rural areas. While major cities boast advanced medical infrastructure, rural regions struggle with limited healthcare access, insufficient doctor-to-patient ratios, and poor road connectivity. The COVID-19 pandemic has emphasized the importance of robust healthcare systems. This paper proposes a cost-effective telehealth system to bridge this urban-rural healthcare gap. This paper discusses the historical development of telehealth technology, highlighting its early phases, rapid development, and current technological maturity. It then presents a novel system model "Sahara", focusing on the integration of temperature and pulse sensors to record patient health vitals. The system utilizes portable devices equipped with sensors to collect patient health data, which is wirelessly transmitted to the cloud. Doctors and caregivers can access this data through a secure web interface for remote diagnosis and treatment. The system ensures a simple user interface, is independent of electricity, and provides a low-cost solution for aggregating patient data. By leveraging readily available technology, this system has the potential to significantly improve healthcare access in rural India. The paper also reviews the evolution of telehealth technologies, highlighting the challenges and opportunities in the field. The system transfers these physiological data to the cloud using a WiFi module and stores them in Amazon Web Services (AWS). The data is accessible to authorized doctors and caretakers through a web interface. The paper also describes the implementation details of the system, both from the front-end and back-end perspectives, including user registration, appointment scheduling, and data integration. Finally, it discusses the results of the system and its potential impact on rural healthcare in India, emphasizing the role of telemedicine in improving healthcare accessibility, redu

关键词： electronic health record

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Self-Power Devices for A Wireless Sensor System Measuring the Shaft Alignment 9

Self-Power Devices for A Wireless Sensor System Measuring th...

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9th International Conference on computer and communication engineering, ICCCE 2023

作者： Hoang, Van Ai Kim, Yang Gon Lee, Young Chui Mokpo National Maritime University Department of Marine Electronic Communication and Computer Engineering Mokpo Korea Republic of

ISBN: (纸本)9798350325218

In this work, we propose an energy harvester (EH) designed for wireless sensor system (WSS) applications on marine propulsion shafts. Two EH designs are presented: a flexible PCB-based EH and an EH with an integrated rotor and stator. The flexible PCB-based EH utilizes multiple magnets and flexible PCBs, achieving an average power of 2117.45 mW at a low speed of 100 rpm with a 3 mm air gap. This EH demonstrates that it is possible to implement a self-power WSS for real-time monitoring of a marine propulsion shaft. The second EH with a hollow circular tube, eight coils with 3,000 winding turns, and a 1.25T spherical magnet generates an average power of 303.21 mW at 100 rpm. The tube provides the fastest rolling of the magnet inside the tube which ultimately increases the electromotive force induced in the coils. This outstanding accomplishment demonstrates the potential of the proposed EH to create WSSs for marine shaft monitoring systems by collecting rotational energy during ship operations. © 2023 IEEE.

关键词： Stators

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Exploring Large Scale Docker Image Vulnerability and Storage Performance Analysis Using High Performance Container-Based Docker Environment

Exploring Large Scale Docker Image Vulnerability and Storage...

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2024 International Conference on System, Computation, Automation and Networking, ICSCAN 2024

作者： Kavya Sri, B. Mahalakshmi, K. Anna University Faculty of Information and Communication Engineering Chennai India Kit - Kalaignarkarunanidhi Institute of Technology Department of Computer Science and Engineering Coimbatore India

ISBN: (纸本)9798331510022

In modern cloud environments, Docker containers have become a cornerstone for efficient application deployment, enabling microservices architectures and seamless scalability. However, large-scale Docker environments present significant challenges, particularly in terms of security vulnerabilities and storage performance. This paper explores vulnerability analysis and storage performance optimization in high-performance, container-based Docker environments. Docker swarm is a container orchestration platform which could be very useful for maintaining the docker containers at scale even at distributed environment, these tools also provide us a great features for managing the rolling updates and health check in the lifecycle of containers. We perform a comprehensive evaluation of Docker image vulnerabilities using automated scanning tools, assessing common vulnerabilities and exposures (CVEs) across large image repositories. Additionally, we investigate storage performance bottlenecks and analyse the impact of various storage drivers on container efficiency. Our findings offer critical insights into balancing performance and security in high-scale Docker deployments, proposing strategies for mitigating risks and enhancing resource management. The results guide container orchestration decisions for enterprises aiming to deploy secure, high-performance systems. © 2024 IEEE.

关键词： Bottles

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Stock values predictions using deep learning based hybrid models

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CAAI Transactions on Intelligence Technology 2022年第1期7卷 107-116页

作者： Konark Yadav Milind Yadav Sandeep Saini Department of Electronics and Communication Engineering The LNM Institute of Information TechnologyJaipurIndia Department of Computer Science and Engineering Rajasthan Technical UniversityKotaRajasthanIndia

Predicting the correct values of stock prices in fast fluctuating high-frequency financial data is always a challenging task.A deep learning-based model for live predictions of stock values is aimed to be developed *** authors'have proposed two models for different *** first one is based on Fast Recurrent Neural Networks(Fast RNNs).This model is used for stock price predictions for the first time in this *** second model is a hybrid deep learning model developed by utilising the best features of FastRNNs,Convolutional Neural Networks,and Bi-Directional Long Short Term Memory models to predict abrupt changes in the stock prices of a *** 1-min time interval stock data of four companies for a period of one and three days is *** with the lower Root Mean Squared Error(RMSE),the proposed models have low computational complexity as well,so that they can also be used for live *** models'performance is measured by the RMSE along with computation *** model outperforms Auto Regressive Integrated Moving Average,FBProphet,LSTM,and other proposed hybrid models on both RMSE and computation time for live predictions of stock values.

关键词： companies price stock

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An Eagle-Eye Vision: Advancements in Avian Species Classification 2

An Eagle-Eye Vision: Advancements in Avian Species Classific...

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2nd International Conference on Automation, Computing and Renewable Systems, ICACRS 2023

作者： Kanaga Priya, P. Vinu, M.S. PrasannaBlessy, M. Kirupa, P. Gayathri, R. Selvakumar, N. Department of Computer Science and Engineering KPR Institute of Engineering and Technology Coimbatore India Department of Computer Science and Engineering Nehru Institute of Engineering and Technology Coimbatore India Department of Computer Science and Engineering RVS Technical Campus Coimbatore India Department of Computer Science and Engineering SNS College of Engineering Coimbatore India Department of Electronics and Communication Engineering Coimbatore Institute of Engineering and Technology Coimbatore India

ISBN: (纸本)9798350340235

Avian species taxonomy is an important activity in the domain of ornithology, wildlife preservation, and ecological research. Convolutional Neural Networks (CNNs) a widely used tool for automating categorization jobs in recent years. This abstract provides an overview of applying Eagle-Eye CNN to the classification of bird species. The methodology originates with image pre-processing, comprising scaling, normalization, and augmentation, to strengthen model resilience. Subsequently, the feature extraction is accomplished inside the CNN architecture layers. Moreover, the use of transfer learning harnesses the proposed CNN model, fine-tuned for the particular job of the Eagle-Eye vision engine for bird species classification. The proposed pre-trained model can also be used for other classification tasks. This technique attains a remarkable accuracy of 89% due to its large dataset and holds potential for further applications across avian taxonomy. In summary, CNNs offer an effective avenue for automated bird or avian classification, permitting more efficient and exact bird behavior study thus enhancing avian conservation attempts. © 2023 IEEE.

关键词： Accuracy Avian classification Bird Convolutional Neural Network Eagle-Eye vision engine

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Enhanced Route Optimization for Wireless Networks Using Meta-Heuristic engineering

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computer Systems Science & engineering 2022年第10期43卷 17-26页

作者： S.Navaneetha Krishnan P.Sundara Vadivel D.Yuvaraj T.Satyanarayana Murthy Sree Jagadeesh Malla S.Nachiyappan S.Shanmuga Priya Department of Electronics and Communication Engineering SACS MAVMM Engineering CollegeMaduraiIndia Department of Computer Science and Engineering SACS MAVMM Engineering CollegeMaduraiIndia Department of Computer Science Cihan University-DuhokKurdistan RegionIraq Department of Computer Science and Engineering Bapatla Engineering College BapatlaAndhra PradeshIndia Department of Computer Application National Institute of TechnologyThiruchirapalliIndia School of Computer Science and Engineering Vellore Institute of TechnologyChennaiIndia Department of Computer Science and Engineering M.I.E.T Engineering CollegeTrichyIndia

Wireless Sensor Networks(WSN)are commonly used to observe and monitor precise *** consist of a large number of inexpensive sensor nodes that have been separated and distributed in different *** base station received the amount of data collected by the numerous *** current developments designate that the attentFgion in applications of WSNs has been increased and extended to a very large *** Trust-Based Adaptive Acknowledgement(TRAACK)Intrusion-Detection System for Wireless Sensor Networks(WSN)is described based on the number of active positive deliveries and The Kalman filter used in Modified Particle Swarm Optimization(MPSO)has been proposed to predict knot *** were run for non-malicious networks(0%malicious)and different percentages of malicious nodes were *** findings suggest that the proposed method TRAACK Modified Particle Swarm Optimization(MPSO)packet delivery rate outperforms TRAACKPSO by 3.3%with 0%malicious ***,the packet delivery rate of TRAACKMPSO is 30%malicious,3.5%better than TRAACKPSO in WSN.

关键词： Trust-based adaptive acknowledgment(TRAACK) modified particle swarm optimization(MPSO) intrusion detection system(IDS) kalman filter

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Unsupervised Fuzzy Clustering-Based Vehicle Detection and Segmentation in Infrared Thermography 5th

Unsupervised Fuzzy Clustering-Based Vehicle Detection and Se...

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5th International Conference on Advances in Distributed Computing and Machine Learning, ICADCML 2024

作者： Ganesan, P. Leo Joseph, L.M.I. Sivakumar, V.G. Thulasi Prasad, S. Sathish, B.S. Sajiv, G. Department of Electronics and Communication Engineering Vidya Jyothi Institute of Technology Hyderabad India Department of Electronics and Communication Engineering SR University Telangana Warangal India Department of Computer Science Engineering AI Sri Venkateshwara College of Engineering Bengaluru India Saveetha School of Engineering SIMATS Chennai India

ISBN: (纸本)9789819718405

The identification of vehicles is indispensable task in this fast moving world where attentiveness is most important than ever before. The suggested methodology explains the effectiveness of fuzzy clustering algorithms for unsupervised vehicle recognition and segmentation in infrared thermography. The method takes use of the natural temperature variations that exist between moving objects and their environment, allowing for precise border delineation. Fuzzy clustering has shown to be a flexible method that offers a framework to organize pixels with comparable properties. By taking into account the uncertainty present in thermal imaging, fuzzy clustering presents a viable solution in the context of vehicle recognition and segmentation. Infrared thermography is more effective in challenging scenarios such as darkness, smoke, or dust. It is also well-suited for real-time scenarios due to fast thermal response. The proposed methodology finds applications in transportation management, security systems, industrial monitoring, and various thermal inspections. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Fuzzy clustering

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Development of an Ontology-Based Technique for Labeling Land Cover Classes with Minimum Utilization of SAR Features

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SN computer Science 2023年第6期4卷 731页

作者： Gupta, Shruti Singh, Dharmendra Kumar, Sandeep Computer Science and Engineering and Information Technology Department Jaypee Institute of Information Technology Noida India Electronics and Communication Engineering Department Indian Institute of Technology Roorkee Roorkee India Computer Science and Engineering Department Indian Institute of Technology Roorkee Roorkee India

The availability of satellite imagery to "domain" experts, along with advancements in image processing and analysis techniques, has revolutionized numerous fields, enabling better understanding, planning, and management of our planet's resources. However, formalizing the knowledge gained from domain experts is essential for preserving, sharing, and leveraging their expertise. In this context, knowledge representation methods like ontology play a significant role in the development of applications based on satellite image analysis. Land cover labeling is one of the significant applications of satellite image analysis and plays a vital role in various domains by providing valuable information about the Earth's surface. Although several works have been reported to focus on land cover land use classification and labeling, very few are properly documented or formalized. Therefore, in this paper, an LCL (land cover labeling) ontology has been proposed for labeling the land cover classes using PALSAR-I satellite data. The ontology is based on an adaptive algorithm, as the labeling criterion is independent of specific range values and depends on feature image statistics. For algorithm development, four types of features, namely, polarimetric features, texture features, color features, and wavelet features were examined. For selecting optimal feature set, random forest was utilized and, consequently, for further labeling the classes a set of rules has been formed by applying Otsu thresholding on the selected class-wise feature sets. The derived rules were finally formalized to develop the ontology for labeling the land cover classes. The proposed ontology was applied to distinct study sites using PALSAR-I data which resulted in a satisfactory classification accuracy of around 85%. © 2023, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.

关键词： Color features Ontology PALSAR Polarimetric features Random forests Texture features Wavelet features

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