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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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A robust framework for Alzheimer’s disease detection and staging: incorporating multi-feature integration, MRMR feature selection, and Random Forest classification

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Multimedia Tools and Applications 2024年 1-29页

作者： HK, Ravikiran R, Deepak H A, Deepak M S, Prapulla Kumar S, Sharath G H, Yogeesh Department of Electronics and Communication Engineering Navkis College of Engineering Karnataka Hassan573217 India Department of Electronics and Communication Engineering BGS Institute of Technology Adichunchanagiri University B.G Nagar Karnataka Mandya571448 India Department of Computer Science Malnad College of Engineering Karnataka Hassan573202 India Department of Electronics and Communication Engineering Government Engineering College KarnatakaChamarajanagar 571313 India

In advancing Alzheimer’s disease detection, this study presents a potent hybrid approach that leverages sophisticated features. Commencing with the TVL1 norm, the method reduces noise and enhances relevant information within neuroimaging data. Further cartoon features from the TVL1 norm are extracted as texture features. GLSZM features unveil critical texture pattern variations, an early hallmark of Alzheimer’s, by meticulously analyzing the size and distribution of homogeneous zones in the brain. Simultaneously, level-set segmented image features provide invaluable structural insights into the brain’s morphology. Integrating a Convolutional Neural Network (CNN) empowers the system to decipher intricate spatial patterns. At the same time, minimum redundancy and maximum relevance (MRMR) feature selection meticulously curates the most salient and non-redundant features. Finally, a Random Forest classifier seamlessly harmonizes these diverse feature sources, culminating in a robust model that can discern subtle signatures of Alzheimer’s disease. The novel approach not merely presents a rapid and precise module for Alzheimer’s disease (AD) diagnosis. Still, it also provides the capacity for both comprehensive global classification ("Normal vs. Mild Cognitive Impairment (MCI) vs. AD") and precise local classification. The latter facet addresses the intricate undertaking of differentiating MCI into three categories: Very Mild Dementia (VMD), mild dementia (MD), and Moderate Dementia (MoD) as early AD stages. Moreover, the study undertakes a comparative analysis of the proposed methodology against previous techniques in the field. The reported results demonstrate exceptional accuracy and robustness, with an overall testing accuracy of 93.11%, showcasing the method’s effectiveness in AD diagnosis and staging. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Convolutional neural networks

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Signal design for MIMO dual-function systems with permutation learning

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Science China(Information Sciences) 2023年第10期66卷 297-315页

作者： Jing YANG Xianxiang YU Minghui SHA Wen FAN Guolong CUI School of Electrical and Information Engineering Zhengzhou University School of Information and Communication Engineering University of Electronic Science and Technology of China Beijing Institute of Radio Measurement The 54th Research Institute of China Electronics Technology Group Corporation

This paper addresses the signal matrix synthesis in the multi-input-multi-output(MIMO) dualfunction system aimed at obtaining the desired radar beampattern while embedding communication symbols into the permutation matrix of each pulse. To this end, transmit beampattern peak mainlobe to sidelobe level ratio(PMSR) is considered the figure of merit. Besides, the phases of the codebook induced by the designed weight vectors impinged on the directions of the communication receivers and eavesdroppers are restricted to be uniformly distributed and totally the same, respectively. To handle the resulting design problem, an iterative algorithm is devised to account for the coupled quadratic fractional programming objective function with multi-equality constraints, capitalizing on the alternating direction method of multipliers(ADMM) framework. As to the demodulation process for permutation learning, a novel algorithm based on the alternating direction penalty method(ADPM) framework is proposed to handle the mix-boolean optimization problem with the correlation between the communication dictionary and permutation of the received filtered data maximized. Finally, numerical results highlight the effectiveness of the conceived algorithms in comparison with the existing counterparts.

关键词： dual function radar and communication (DFRC) system multi-input multi-output (MIMO) radar beampattern alternating direction method of multipliers (ADMM) permutation learning mix-boolean optimization problem alternating direction penalty method (ADPM)

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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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Performance analysis of lung cancer detection and classification using efficientNet: a deep learning model

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Multimedia Tools and Applications 2024年 1-15页

作者： A, Priya P, Shyamala Bharathi Department of Electronics Communication and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Tamil Nadu Chennai India

Lung cancer is one among the serious critical diseases worldwide. According to World Health Organisation (WHO), there are about 7.6 million death cases annually worldwide because of lung tumor and its accurate diagnosis of disease also crucial. Moreover, humanity related to cancer is projected to begin to grow to about 17 million worldwide in 2030. Computed tomography (CT) scans may offer valuable information in the lung disorders diagnosis across multiple imaging modalities. Discovering early stage lung cancer is the best way to treat it. In this proposed research, a deep learning based pre-trained model called EfficientNet with convolution neural networks for the classifications of lung cancer using the CT images. The CT lung images are gathered from The Cancer Imaging Archive database. By using these images the proposed model is evaluated and validated with the performance analysis. The goal is to identify lung cancer using CT images, that can be useful in determining that the patient is affected by cancer or not. The performance metrics used in this work are accuracy, sensitivity, specificity, precision and f1-score and the results obtained are compared with existing techniques for validation. The method achieved 99.28% training accuracy for training and 98.03% accuracy for training. Overall the efficiency of the proposed model is better than other compared techniques. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Lung cancer

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A Squared Shaped Ring Loaded with Improved Radiation 2-Element Waveguide Array for Radar Applications 3

A Squared Shaped Ring Loaded with Improved Radiation 2-Eleme...

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3rd International Conference on Artificial Intelligence For Internet of Things, AIIoT 2024

作者： Chandra, Avinash Harish, S.S. Kumar, Rajkishor Patil, Hemprasad Yashwant Kumar, Kundan Vellore Institute of Technology School of Electronics Engineering Vellore India National Institute of Technology Department of Electronics and Communication Engineering Jalandhar India

ISBN: (纸本)9798350372120

In this work a frequency selective resonator (FSS) immersed dual band, rectangular slot array has been presented. Two squared shaped ring frequency selective surfaces are interested on sides of travelling slots to obtain dual-band behavior. The presented array have input reflection coefficient ranges from 8.3-8.52 GHz and 11.7-12.12 GHz respectively. The presented array have higher front to back ration and 8-10 dBi gain, which is suitable for X-band application particular in radar. © 2024 IEEE.

关键词： Frequency selective surfaces

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Achieving Secured Medical Network (SMN) through Stateless Mechanism and SkeyM in Medical-Internet of Things (M-IoT)

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Journal of engineering and Applied Science 2024年第1期71卷 128页

作者： Nithya, S. Palanisamy, SatheeshKumar Nivethitha, T. Department of Computer Science and Engineering Kumaraguru College of Technology Tamil Nadu Coimbatore641049 India Department of Electronics and Communication Engineering BMS Institute of Technology and Management Karnataka Bengaluru560064 India Department of Electronics and Communication Engineering Sri Eshwar College of Engineering Tamil Nadu Coimbatore641202 India

Medical Internet of Things (M-IoT) synchronizes medical devices in a network to provide smart healthcare monitoring to doctors and to provide an interactive model for patients. This embedded networked system gained lots of importance in the last few years. Now almost every hospital adopts M-IoT. Though it had a lot of challenges in the initial stages of implementation such as feasibility, accuracy, and autonomy, now it has bridged the flaws with the help of several researchers in this field. But still, M-IoT lags behind in security and privacy aspects due to which attackers can intrude on the network and exploit patients’ health data. By examining the various intensive security threats imposed on M-IoT a unique way of handling and transferring data over the network is proposed in this paper. From our research findings, this would resolve the data security issues in M-IoT and commence the next advancements. © The Author(s) 2024.

关键词： Internet of things

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Efficiency Enhancement of Perovskite Photovoltaic Cells by Incorporation of NiO2 HTL 4

Efficiency Enhancement of Perovskite Photovoltaic Cells by I...

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4th International Conference on Power, Control and Computing Technologies, ICPC2T 2025

作者： Kumar, Raushan Priyadarshi, Alok Kumar, Shivam Kumar, Abhishek Department of Electronics and Communication Engineering School of Engineering SR University Telangana Warangal506371 India Department of Electrical Engineering National Institute of Technology Jamshedpur India Department of Electronics and Communication Engineering National Institute of Technology Jamshedpur India

ISBN: (纸本)9798331530402

In order to achieve high hole capturing rates and minimal minority carrier loss in PV cells, the hole transport layer (HTL) materials in Copper Zinc Tin Sulfide (CZTS) photovoltaic cells (PCs) are essential. Up to this point, CZTS cells based on HTL materials with high minority carrier loss minimization have only been developed. In order to create an effective CZTS PV cell, numerous researchers are looking into wide energy bandgap HTL materials. This paper proposes a novel wide bandgap NiO2 as a HTL nanomaterial for a high-efficiency photovoltaic cell. Additional analysis, energy band alignment matching, layer thickness and doping density optimization, and base-based proposed PV cell construction. The CZTS/NiO2 based PV cell performs better, with Voc=1127 mV, Jsc=28.17, FF=84.26%, efficiency=26.74%, and EQE=82%. © 2025 IEEE.

关键词： Semiconductor doping

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