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3rd International Conference on electronics and Renewable Systems, ICEARS 2025

作者： Tamilselvi, M. Saveetha School of Engineering Department of Electronics and Communication Engineering Chennai India

ISBN: (纸本)9798331509675

Unmanned Aerial Vehicles (UAVs), also called drones, are planes operated by unmanned aircraft and controlled remotely via built-in computers or remote control. Their applications span from surveillance to delivery, and even agriculture to communications. Battery life and range limitations may limit the operational time of UAVs. They can create privacy issues, security risks, and potential threats to air traffic and public safety if not properly regulated. NB-IoT networks are addressed by the USC-WBND approach using semi-permanent scheduling (SPS) and shorter transmission time intervals (TTI). Using a fixed 1ms TTI can reduce latency and allocate resources more efficiently while decreasing the number of OFDM symbols. Relay requests for scheduling resources are eliminated in SPS, resulting in reduced latency for devices with regular transmissions. Moreover, the user's information, login details, and device settings along with GPS tracking are all managed by a cloud-based display platform, which allows for tailored access and precise location tracking. By visualizing UAV distribution in 2D and 3D, it is possible to select the most suitable drone locations to minimize interference and enhance coverage. A 2D technique is concerned with determining height and location, while another 3D approach employs a game of matching to find the most suitable UAVs for different user densities and interference. This mathematical modeling and algorithm aim to find the best placement for UAVs, maximize coverage by IoT nodes, and provide optimal service quality. The proposed strategies improve network efficiency, reduce interference, and optimize the placement of data transmission relays, providing significant advances in smart city environments. The main issues in NB-IoT and UAV deployments are addressed through this comprehensive approach, which seeks to address network performance problems by enhancing connectivity and decreasing latency. IoT communication is a crucial aspect of smart

关键词： Drones

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Innovative Wireless communication Solutions: IoT Mobility in Smart Cities, and 5G-V2X Resource Management 3

Innovative Wireless Communication Solutions: IoT Mobility in...

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3rd International Conference on electronics and Renewable Systems, ICEARS 2025

作者： Tamilselvi, M. Saveetha School of Engineering Department of Electronics and Communication Engineering Chennai India

ISBN: (纸本)9798331509675

In this article, an Innovative Wireless communication Solutions - 5G Resource Management (IWCS-5GRM) model is developed for healthcare and vehicular communication systems. The treatment process involves the use of an Artificial Pancreas Device (APD), which integrates Continuous Glucose Monitoring (CGM), insulin pumps, and Internet of Things (IoT) technology to automate glucose management. This device mimics the functions of a healthy pancreas, providing real-time monitoring of glucose and insulin regulation, improving diabetes management, and enabling remote treatment. When it communicates with vehicles, the model uses vehicle-to-vehicle (V2V) communication systems with transceivers, algorithms of Virtual Traffic Lights (VTL), and Dedicated Short Range communication (DSRC) to improves data traffic, diminish data collision, and improvise traffic safety. Experimental evidence indicates that the ns3 simulation environment exhibits a significant performance improvement when compared to current protocols, including EIFV, EEFM, and UVAC. By achieving lower routing load, increased packet transmission speed, network capacity, lower Routing burden, and improved data transfer, IWCS-5GRM is highly regarded for its usefulness in both traffic management and healthcare. This comprehensive approach combines advanced IoT technologies with custom algorithms to optimize system performance and user satisfaction in various application scenarios. © 2025 IEEE.

关键词： Resource allocation

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Advanced communication Protocols for IoT Environments: Privacy-Preserving and UAV-based MAC Optimization 3

Advanced Communication Protocols for IoT Environments: Priva...

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3rd International Conference on electronics and Renewable Systems, ICEARS 2025

作者： Nirmala, P. Saveetha School of Engineering Department of Electronics and Communication Engineering Chennai India

ISBN: (纸本)9798331509675

Internet of Things (IoT) and UAVs function as a robust network, with serving as mobile data collectors or transmitters for IoT devices. The integration enhances data collection, communication, and monitoring capabilities in remote or expansive regions. The ability to produce large amounts of data and monitor real-time is a key advantage of IoT devices over UAVs, which offer positioning and coverage flexibility. Together, they enable efficient and dynamic control of complex systems in various applications such as agriculture, disaster management, and smart cities. The utilization of a hybrid network model and intricate collaborative communication resource allocation system are the hallmarks of ACPE-UMO. To enhance network performance and reliability, the resource allocation system utilizes elements such as service information for relay nodes to be selected based on Relay Delay Parameters (RDP), along with channel information like peers. To achieve efficient clustering and termination probability implementation of MAC protocols, the hybrid network model utilizes UAVs to implement CSMA/CA protocol and the Markov chain model to gather data from IoT devices. Our strategy incorporates both traditional methods of communication and creative techniques for maximizing coverage and data collection efficiency. Ubuntu OS software ns3 tests demonstrate that the ACPE-UMO model is an excellent candidate. Compared with existing protocols such as CCQP, AASD, and PEFR, ACPE-UMO achieves a higher throughput of 450.31 Kbps, a better packet ratio of 90.64%, a lower average delay of 250.96 ms, higher network latency of 480.36 Kbps and significant. reduced network congestion of 215.12 packets. These results demonstrate that ACPE-UMO is a highly effective means of improving network performance and reliability across multiple communication domains. © 2025 IEEE.

关键词： Resource allocation

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Revolutionary Solutions for Vehicular Networks: Pollution Monitoring and Cluster-based Resource Management 3

Revolutionary Solutions for Vehicular Networks: Pollution Mo...

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3rd International Conference on electronics and Renewable Systems, ICEARS 2025

作者： Shifani, S. Agnes Saveetha School of Engineering Department of Electronics and Communication Engineering Chennai India

ISBN: (纸本)9798331509675

The Vehicular Ad Hoc Network (VANET) is a trending technology that connects vehicles and infrastructure to improve traffic safety, traffic efficiency, and entertainment services. We developed a Revolutionary Solutions for Vehicular Networks Pollution Monitoring and Cluster-Based Resource Management (RS-PMCRM) model is an innovative IoT-based system that utilizes gas sensors and RFID to monitor real-time vehicle pollution. Displays in LCD, the system notifies vehicle owners of pollution levels and sends notifications for further analysis to authorities. An empirical analysis based on PVMS data of 8900 vehicles in Changsha, China shows that vehicles are parked for an average of 22.63 hours per day. The RS-PMCRM model optimizes V2X communication by calculating the SINR values for cluster heads (CHs), cluster members (CMs), and eNodeBs forming V2V clusters with vehicle-based greedy repetition. method metrics like speed and distance. The proposed system improves network efficiency and achieves a high packet delivery ratio of 95.47%, network throughput of 386.25 Kbps, low average delay of 105.87 ms, high energy efficiency of 354.78 Joules, and low packet cost of 154.96. Comparative analysis with existing BICO, TSRT, and AIOM models shows the excellent performance of RS-PMCRM in all evaluated parameters, making it a robust solution for pollution control and vehicle network optimization. Significant improvements in vehicle communication, energy efficiency, and network performance have been observed. © 2025 IEEE.

关键词： Vehicular ad hoc networks

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Blockchain-Enabled Intelligent Vehicle communication Systems: Trust Bit Rewards and Clustering for Autonomous Vehicles 3

Blockchain-Enabled Intelligent Vehicle Communication Systems...

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3rd International Conference on electronics and Renewable Systems, ICEARS 2025

作者： Nirmala, P. Saveetha School of Engineering Department of Electronics and Communication Engineering Chennai India

ISBN: (纸本)9798331509675

In the absence of a permanent infrastructure, the networks are utilized for temporary events, military operations, and disaster recovery. A Blockchain-Enabled Intelligent Vehicle communication Systems: Trust Bit Rewards and Clustering for Autonomous Vehicles (BIVC-CA), an algorithm designed to ensure secure communication between devices and optimize efficient routing in intelligent vehicle systems, is also used to provide quick emergency response. Using blockchain, each vehicle is given its own Bit Trust ID to track its past data and calculate its trust levels. This system ensures transparency and trust between vehicles through cryptographic processes such as key generation, secure message encryption, and message verification, which improve overall communication security. It also includes an Emergency Vehicle communication System (EUC) that uses OBU devices and sensors to detect collisions and send GSM-based rescue messages, greatly improving road safety and the efficiency of emergency operations. The road-based clustering model optimizes route selection considering traffic conditions and distances and organizes vehicles into clusters to ensure effective communication and coordination. Using the path distance algorithm, clustering is achieved by computing the similarity of routes and grouping accordingly for efficient route management with minimal network congestion. In addition, the model introduces a comprehensive network architecture that integrates vehicle cloud technology and blockchain technology, enabling intelligent vehicles to make quick decisions based on real-time data. With these integrated components, the BIVC-CA model provides a reliable framework for secure data transmission, intelligent routing, and rapid emergency response. This framework will ultimately improve the efficiency of intelligent vehicle systems and contribute to the development of advanced vehicle networks and smarter transportation solutions. We calculated the results with routing expe

关键词： Blockchain

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Compact Monopole Antenna with Cross Shaped Slot for Microwave Brain Tumor Detection Applications

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Progress in Electromagnetics Research B 2025年 110卷 43-56页

作者： Asok, Athul O. Sowmya, Mohanan Faisa, Valiyaveetil U. Fathima, Fahima K. Harikrishnan, A.I. Sumi, Mohan Dey, Sukomal Department of Electrical Engineering Indian Institute of Technology Kerala Palakkad678623 India Department of Electronics and Communication Engineering NSS College of Engineering Kerala Palakkad678008 India

The early detection of brain tumors presents significant challenges due to the complexity of the brain as well as the need for noninvasive diagnostic tools. This study introduces a novel antenna design optimized for noninvasive brain tumor detection. In this work, a cross slotted circular patch with a rectangular slot in the ground plane is designed in the simulator for brain tumor detection. The designed antenna operates from 1.76 GHz to 13.6 GHz with an impedance matching of greater than −10 dB. The antenna attains a peak gain of 5.8 dBi at 8 GHz. The antenna has been fabricated using the Monolithic Microwave Integrated Circuit (MMIC) technology and then tested in an anechoic chamber environment. The simulated and measured antenna performance parameters are found in agreement. The developed antenna has been used to image a target containing liquid inside a bottle covered by foam material. The liquid inside the bottle mimics the tumor material as its dielectric constant is comparable to a realistic tumor material. The target has been successfully reconstructed using the Delay and Sum (DAS) approach. © (2025), (Electromagnetics Academy). All rights reserved.

关键词： Monopole antennas

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A fine-tuned transformer model for brain tumor detection and classification

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Multimedia Tools and Applications 2025年第15期84卷 15597-15621页

作者： Srinivas, B. Anilkumar, B. devi, NLakshmi Aruna, V.B.K.L. Andhra Pradesh Vizianagaram535005 India Electronics and Communication Engineering GMR Institute of Technology Andhra Pradesh Razam532127 India Computer Science and Engineering GMR Institute of Technology Andhra Pradesh Razam532127 India Electronics and Communication Engineering V R Siddhartha Engineering College Andhra Pradesh Vijayawada520007 India

The identification and classification of brain tumors from medical images is a challenging task, which plays a crucial role in treatment planning. In recent times, the transformer models earned greater attention in image classification tasks because of their tendency to learn complex and spatial interconnections in medical images. In this study, a novel fine-tuned transformer model was developed by combining the benefits of a data-efficient image transformer (DeiT) and the firefly algorithm (FA) for the precise classification of tumors. This framework utilizes the transformer's self-attention and feed-forward layers to learn and capture complex patterns and high-level features. It employs the Firefly fitness solution to fine-tune the DeiT architecture by updating its hyperparameters, thereby maximizing the system performance and reducing training loss. The novelty of the paper lies in its proposal and implementation of a fine-tuned transformer model specifically tailored for the detection and classification of brain tumors. By leveraging the capabilities of transformer architectures, such as the data-efficient image transformer (DeiT), the proposed model can effectively capture intricate spatial dependencies and complex patterns within brain MRI images. The experimental analysis utilizes the benchmark brain tumor MRI database from the Kaggle source and the developed model achieved greater classification accuracy of 99.7%. In addition, a comprehensive comparative analysis was performed with existing models to demonstrate the robustness of the proposed work. This intensive analysis verifies that this model facilitates the accurate and timely detection of brain tumors in medical diagnosis. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Image classification

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An Image Processing-Based Statistical Method for Estimating Nutrient Deficiencies in Grape Plants During the Growing Season

Informatica (Slovenia)

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Informatica (Slovenia) 2025年第1期49卷 105-116页

作者： Macriga, G. Adiline Subbiah, Sankari Sudha, G. Saranya, S. Department of Information Technology Sri Sai Ram Engineering College Chennai India Department of Electronics and Communication Engineering Sri Sai Ram Engineering College Chennai India

Agriculture plays a very important role in the provision of food surplus to expanding population, contribution to capital formation, providing raw material to industries, market for industrial products and major contribution in international trade. To enhance the quality and quantity of the agriculture product there is a need to adopt the new technology. Image processing approach is non-invasive technique which provides consistent, reasonably accurate, less time consuming and cost-effective solution for farmers to manage fertilizers and pesticides. The objective of this study is to analyze the nutrition of grape plant using Wavelength algorithmand statistical method regression analysis is used in our work for the nutrient estimation. The relative requirements of nitrogen, phosphorus and potassium in grapes vary with the growth stages of grapes. There is a high-level requirement of N during the vegetative growth stage, P requirement is high during flowering stage and K requirement is more in crop maturity stage. So pruning was carried out in two stages i.e., in April and in October. This study is carried out in grape farms of Theni District of Tamil Nadu for estimating the macro nutrition nitrogen (N), phosphorus (P) and potassium (K) to analyze the yield. The results showed that the overall identification accuracies of NPK deficiencies were 86.15, 87.69, 90.00 and 89.23% for the two pruning stages. © 2025 Slovene Society Informatika. All rights reserved.

关键词： Population statistics

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Bayesian Inverse Learning and Online Changepoint Detection of Cognitive Radar Strategies

IEEE Transactions on Radar Systems

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IEEE Transactions on Radar Systems 2025年 3卷 562-575页

作者： Anoop, C.V. Aprem, Anup National Institute of Technology Calicut Department of Electronics and Communication Engineering Kozhikode673601 India

In this article, we introduce an online electronic countermeasure framework for learning the strategies and detecting changes in the strategy of an adversarial cognitive radar (CR) in an inverse learning framework. We model the CR as a rational, constrained utility-maximizing agent and formulate the problem in the revealed preference setting. The utility of CR is modeled as a random direction vector, that follows the von Mises-Fisher distribution with unknown parameters, and we use Bayesian machine learning with revealed preference characterization to learn the radar’s utility, and extend it to the detection of changes in strategy in an online setting. The main contributions of the article are: 1) the development of Bayesian machine learning algorithms—HBOIL and HBOCPD, for inverse learning and detection of changes in strategies of an adversarial CR, respectively;2) HBOIL and HBOCPD use a Hamiltonian Monte Carlo (HMC) sampling algorithm that exploits the Afriat’s theorem in revealed preference as well as a subsetting structure that arises in the posterior, and hence is devoid of the computational burden of solving optimization problems in existing techniques;3) numerical results demonstrate the ability to characterize and determine the changes in the beam allocation strategy of a CR in noise-free and noisy adversarial settings. HBOIL and HBOCPD are robust to observation noise compared to the existing approaches;4) HBOIL outperforms classical machine learning approaches in predicting optimal radar responses;and 5) HBOCPD performs, on an average, five times faster compared to the classical offline generalized likelihood ratio (GLR) approach, while using less restrictive assumptions. © 2023 IEEE.

关键词： Hamiltonians

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Physics of 2D Materials for Developing Smart Devices

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Nano-Micro Letters 2025年第8期17卷 449-490页

作者： Neeraj Goel Rahul Kumar Department of Electronics and Communication Engineering Netaji Subhas University of TechnologyDwarkaNew Delhi 110078India Institute of Infrastructure Technology Research and Management Ahmedabad 380026India

Rapid industrialization advancements have grabbed worldwide attention to integrate a very large number of electronic components into a smaller space for performing multifunctional *** fulfill the growing computing demand state-of-the-art materials are required for substituting traditional silicon and metal oxide semiconductors ***-dimensional(2D)materials have shown their tremendous potential surpassing the limitations of conventional materials for developing smart *** their ground-breaking progress over the last two decades,systematic studies providing in-depth insights into the exciting physics of 2D materials are still ***,in this review,we discuss the importance of 2D materials in bridging the gap between conventional and advanced technologies due to their distinct statistical and quantum ***,the inherent properties of these materials could easily be tailored to meet the specific requirements of smart ***,we discuss the physics of various 2D materials enabling them to fabricate smart *** also shed light on promising opportunities in developing smart devices and identified the formidable challenges that need to be addressed.

关键词： 2D materials Heterostructures Smart devices Van der Waals Flexible electronics

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