BHUVANESWARI E

@ebhuvaneswari@panimalar.ac.in

Associate Professor
Panimalar Engineering College

BHUVANESWARI E


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https://researchid.co/ebhuvana

RESEARCH, TEACHING, or OTHER INTERESTS

Artificial Intelligence, Computer Science Applications, Multidisciplinary, Computer Networks and Communications
27

Scopus Publications

177

Scholar Citations

6

Scholar h-index

6

Scholar i10-index

Scopus Publications

  • A High-Precision Approach of Coconut Tree Disease Detection using Enhanced Yolov9
    E. Kodhai, E. Bhuvaneswari, Robin Britto. V, Sumathi. S
    Ksii Transactions on Internet and Information Systems, 2026
    Accurate detection and categorisation of coconut tree diseases are vital for enhancing agricultural output and sustaining farming practices.This study presents an advanced framework combining Enhanced YOLOv9 with EfficientNet for robust disease feature extraction.Our approach employs pseudo-labelling via Region Proposal Network (RPN) during the training phase to generate approximate bounding boxes for unannotated images.The EfficientNet backbone improves inter-class distinction and intra-class variability handling.During inference, the anchor-free detection head directly predicts disease region centers and dimensions without anchor priors, while Feature Pyramid Network (FPN) enables multi-scale feature aggregation for comprehensive detection of lesions ranging from small spots to large infected areas.Advanced data augmentation and a hybrid loss function enhance model generalization and detection capabilities.Experimental results demonstrate that our model achieves 97.34% accuracy, 99.8% precision, 94.67% recall, and a 97.17% F1 score, outperforming state-of-the-art architectures.This work presents an effective tool for fieldbased disease detection and classification, supporting timely interventions in coconut cultivation.
  • Adaptive RL-Based AI for Real-Time Dynamic Navigation in Autonomous Robot
    Antonia Anne Mary A., V. Anjana Devi, Bhuvaneswari E.
    Iet Conference Proceedings, 2026
    Autonomous robot navigation necessitates effective path planning strategies. This project undertakes the implementation and evaluation of a reinforcement learning-based navigation framework using Proximal Policy Optimization (PPO) and Soft Actor-Critic (SAC), integrated with multi-sensor fusion and ROS-based control. All algorithms are implemented primarily in Python. A*, Dijkstra, RRT, RRT*, and DQN are evaluated within a custom 2D grid-based simulation environment. Additionally, Dijkstra's algorithm is demonstrated in a 3D physics-based simulation using the PyBullet library. Key performance metrics, including path length, computation time (search/inference), training time and convergence (for DQN), and success rate, are systematically measured and analyzed across various environmental configurations. This work provides a practical comparison of these distinct approaches, highlighting the inherent trade-offs between optimality guarantees, computational efficiency, exploration capabilities, and adaptive learning potential for foundational robotic path planning problems in static environments In simulation, PPO achieved a 92.1% success rate with a mean path length of 14.3 m, while SAC achieved 85.2% and 15.6 m respectively, demonstrating the benefits of the proposed integration.
  • Automated Trajectory Optimization Framework for Extended Space Missions
    Antonia Anne Mary A., V. Anjana Devi, Bhuvaneswari E.
    Iet Conference Proceedings, 2026
    Long-duration space missions demand highly efficient and adaptive trajectory planning to minimize fuel consumption, extend mission life, and ensure robustness against dynamic space environments. Traditional optimization techniques often struggle with the vast and complex search spaces involved in interplanetary travel. This paper explores a hybridized approach that integrates Deep Reinforcement Learning (DRL) with Genetic Algorithms (GA) and Particle Swarm Optimization (PSO) to optimize spacecraft trajectories. DRL provides the capability to learn optimal policies in high-dimensional, continuous action spaces, while GA and PSO contribute global search capabilities and convergence efficiency. The proposed framework leverages DRL's adaptive learning with the exploratory strengths of GA and PSO to find fuel-efficient and time-optimal trajectories under multi-constraint environments. A deep neural network architecture is employed to model the policy and value functions in the DRL agent, which interacts with a high-fidelity physics-based environment simulating the space mission dynamics. GA and PSO are used to pre-train and periodically guide the DRL policy, seeding it with high-potential solutions and avoiding premature convergence. This hybrid strategy addresses the curse of dimensionality and the sparse reward challenges typical in trajectory optimization problems. This study underscores the viability and effectiveness of integrating biologically inspired optimization algorithms with modern reinforcement learning techniques for aerospace applications.
  • Establishing a Secure Data Transfer Framework for Legacy Cloud Migration
    Antonia Anne Mary A., V. Anjana Devi, Bhuvaneswari E.
    Iet Conference Proceedings, 2026
    With more enterprises moving to the cloud in order to obtain better scalability, cost savings, and agility, this project provides a secure and systematic model of migrating legacy applications with low operational impact. We used a hybrid method, with rebuild and rehosting strategies, to enable a smooth deployment on AWS, using JPetStore, a Java based E-commerce application. The second step of the rebuild was aimed at updating the architecture of the application, optimizing the database settings and compatibility with cloud-native services. In an endeavor to improve portability and consistency, we implemented the Docker-based containerization, which allows the smooth deployment of it in various environments. AWS infrastructure was equipped with the important services, EC2 which provides scaled computing power, S3 which provides storage and RDS which provides managed database services to provide a resilient and robust cloud environment. Security was at the first priority as the application was secured by means of end-to-end encrypted data transfers, IAM-based authentication, and granular access control mechanisms. After migration, performance testing and optimization were performed intensively to ensure functionality and test scalability under different load conditions and underpin anticipated cost efficiencies. This project does not only provide a scalable, secure and repeatable cloud migration architecture, but It also demonstrates industry best practices of migrating older systems to the cloud to unlock the benefits of the cloud, including a higher level of security, better use of resources and more business responsiveness. The framework would be a worthy roadmap to those organizations that have decided to participate in similar cloud migration undertakings.
  • Mamdani Fuzzy Inference System Based on Multi-Textural Biomarkers for Alzheimer’s Stage Detection
    A. R. Kavitha, M. Ramya, T. N. Charanya, P. Lita Pansy, E. Bhuvaneswari
    Lecture Notes in Networks and Systems, 2026
  • Multi-Agent Soft Actor-Critic with Graph Attention Networks for Adaptive Traffic Signal Optimisation (MASAC-GAT)
    R. M. Bommi, E. Bhuvaneswari, M. Rohini, G. Uganya
    Eai Endorsed Transactions on Internet of Things, 2025
    INTRODUCTION: Adaptive Traffic Signal Optimisation (ATSO) is a challenging problem for urban traffic networks, having important implications for congestion reduction, traffic efficiency, and environmental conservation. Conventional traffic signal control techniques, i.e., fixed-time and rule-based control, fail to respond to dynamic traffic behaviour efficiently. OBJECTIVES: Recent developments in Reinforcement Learning (RL) have been promising for ATSO but are plagued by poor scalability, lack of coordination in multi-intersection networks, and inefficiency in dealing with continuous action spaces. METHODS: Furthermore, most RL-based solutions are based on simplistic state representation and fail to incorporate complex interdependencies between traffic signals. Considering these limitations, this paper introduces a new framework, Multi-Agent Soft Actor-Critic with Graph Attention Networks (MASAC-GAT), which unites the sample efficiency and stability of Soft Actor-Critic (SAC) with the relational modelling ability of Graph Attention Networks (GATs). RESULTS: The proposed method exhibited significant performance gains on three important traffic metrics: Signal Adjustment Efficiency (92%), Average Waiting Time (20–35 seconds), and Congestion Prediction Accuracy (93%), outperforming DQL, PPO, A2C, GNN-based variants, and knowledge sharing DDPG (KS-DDPG). Through minimised redundant signal changes and reduced vehicle delays, the method ushers in the next generation of smart transportation systems. CONCLUSION: The proposed method facilitates decentralised yet coordinated control of traffic signals by utilising local observations and global context. The proposed method unites real-time traffic observations, e.g., traffic volume, vehicle speeds, weather, accident reports, and signal status, into a customised OpenAI Gym environment for training and evaluation.
  • A deep learning-driven multi-layer digital twin framework with miot for precision oncology in cancer diagnosis
    Golden Nancy, E. Bhuvaneswari, Venkatesan R.
    Journal of Intelligent Systems and Internet of Things, 2025
  • Real-Time Sign Language Recognition System for Physically Challenged Community Using Deep Learning Technique
    V. Anjana Devi, E. Bhuvaneswari, Rama Krishna Tummala
    Lecture Notes in Electrical Engineering, 2025
  • Edgeguardmed: Transformer-Based Intrusion Detection with Packet-Flow Fusion for Resilient IoMT
    E. Bhuvaneswari, G. Uthradevi, A. Mary Joy Kinol, P. Shanthi
    Biomedical Materials and Devices, 2025
  • Predicting Stock Market Trends using Sentiment Analysis on News and Social Media
    Arjun S, Bhuvaneswari E, Balachandar J, Gomathi T, Surendran R
    Proceedings of 3rd International Conference on Augmented Intelligence and Sustainable Systems Icaiss 2025, 2025
    This research will analyze the efficiency of using sentiment analysis on news articles and social media to predict stock market trends. By analyzing public sentiment from sthis study'sces like Twitter, Reddit, and major financial news platforms, this research will try to capture the psychological influence that the market has on stock prices. Work use Natural Language Processing (NLP) techniques to label textual data as positive, negative, or neutral and aggregate sentiment scores over specific time intervals. These scores are added to the machine learning model: logistic regression, random forest, and Long Short-Term Memory (LSTM). Thus, the proposed approach along with the developed model is tested for determining its predictability pothis researchr when historical data are involved using various evaluation measures for quantifying its predictive pothis researchr after being trained and validated, showing very good and reliable results with better precision obtained by the integration of features based on sentiment analysis. This method brings out the strength of sentiment analysis as an ancillary tool for financial prediction. Investors can gain good knowledge about market trends by tracking the dynamics of public sentiments.
  • A human-centered hybrid AI framework for optimizing emergency triage in resource-constrained settings
    E. Bhuvaneswari, K.D.V. Prasad, Mohd Ashraf, Sachin Jadhav, TK Rama Krishna Rao, Tirukoti Sudha Rani
    Intelligence Based Medicine, 2025
  • A Novel Approach for Multi-User Authentication Framework for Biometric Applications Using Fusion Methods
    V. Arulkumar, E. Bhuvaneswari, S. Sridhar, V. Uma, P. Nancy
    Aip Conference Proceedings, 2024
  • Scalable Local Recoding Anonymization to Preserve Privacy in Big Data Mining
    E. Bhuvaneswari, R. Kalaiselvi, K. Rama Devi, Rama Krishna Tummala, G. Shanthi
    Aip Conference Proceedings, 2024
  • Ontology Based Patient Information Discovery Using IoT Healthcare Monitoring System
    V. Arulkumar, G. Kalpana, C. Selvan, E. Bhuvaneswari, G. Divya
    Aip Conference Proceedings, 2024
  • Single Image Dehazing using a Channel and Pixel Attention Network
    V. Anjana Devi, E. Bhuvaneswari, A. Antonia Anne Mary
    2nd International Conference on Emerging Trends in Information Technology and Engineering Ic Etite 2024, 2024
  • Iterative Deepening Chess Engine with Alpha Beta Pruning
    E. Kodhai, E. Bhuvaneswari, V. Anjana Devi, S.T. Preethi
    2024 International Conference on Smart Technologies for Sustainable Development Goals Icstsdg 2024, 2024
  • Smart Detection Framework for Rapid Emergency Response
    Arjun S, Bhuvaneshwari E, Sundara Rajulu Navaneethakrishnan, Sathish Kumar P. J, Surendran R
    2nd International Conference on Sustainable Computing and Smart Systems Icscss 2024 Proceedings, 2024
  • Convergence of Modern Technologies for Data Architectures
    Wakeel Ahmad, V Arulkumar, K Parthiban, E Bhuvaneswari, Mohammad Arif, K S Guruprakash
    Wireless Communication Technologies Roles Responsibilities and Impact of Iot 6g and Blockchain Practices, 2024
  • An Enhancement in Data Security Using Trellis Algorithm with DNA Sequences in Symmetric DNA Cryptography
    K. Rama Devi, E. Bhuvaneswari
    Wireless Personal Communications, 2023
  • Detection and Categorization of Brain Tumors Through Deep Learning
    V. Anjana Devi, E. Bhuvaneswari, Rama Krishna Tummala
    2023 International Conference on Data Science Agents and Artificial Intelligence Icdsaai 2023, 2023
  • Decentralized Hybrid Intrusion Detection System for Cyber Attack Identification using Machine Learning
    V. Anjana Devi, E. Bhuvaneswari, Rama Krishna Tummala
    2023 International Conference on Data Science Agents and Artificial Intelligence Icdsaai 2023, 2023
  • Fuzzy Search with Multi-Keyword Security and Improved Service Quality
    E. Bhuvaneswari, V. Anjana Devi, R. Gowri
    2023 International Conference on Data Science Agents and Artificial Intelligence Icdsaai 2023, 2023
  • MRI VOLUMETRIC ANALYSIS FOR EARLY DETECTION OF ALZHEIMER’S DISEASE USING OPTIMISED FUZZY TECHNIQUES UNDER ECOLOGY SCENARIO
    Journal of Environmental Protection and Ecology, 2023
  • Unsupervised Feature Learning for Text Pattern Analysis with Emotional Data Collection: A Novel System for Big Data Analytics
    Yusuf Perwej, E. Bhuvaneswari, Saroj Kumar, V. Arulkumar, P. Nancy
    2022 International Conference on Advanced Computing Technologies and Applications Icacta 2022, 2022
  • Security Enhancement Using Quantum Cryptography in WSN
    Subhash Chandra Gupta, Bhopendra Singh, Mohd. Amjad, M. Gopianand, E. Bhuvaneswari
    2021 7th International Conference on Advanced Computing and Communication Systems Icaccs 2021, 2021
  • Plant growth promoting effects of multi-trait rhizobacteria on Vigna radiata
    Indian Journal of Environmental Protection, 2018
  • Privacy preserving with M-SVM classifier of tumor classification in mammography images using multiple Otsu'S thresholding technique
    E. Bhuvaneswari, T. Ravi
    Journal of Computational and Theoretical Nanoscience, 2018

RECENT SCHOLAR PUBLICATIONS

  • Adaptive RL-based AI for real-time dynamic navigation in autonomous robot
    VA Devi, E Bhuvaneswari
    International Conference on Advancing Technology in Engineering and Science … , 2025
    2025
  • Automated trajectory optimization framework for extended space missions
    VA Devi, E Bhuvaneswari
    International Conference on Advancing Technology in Engineering and Science … , 2025
    2025
  • Establishing a secure data transfer framework for legacy cloud migration
    VA Devi, E Bhuvaneswari
    International Conference on Advancing Technology in Engineering and Science … , 2025
    2025
  • Mamdani Fuzzy Inference System Based on Multi-Textural Biomarkers for Alzheimer’s Stage Detection
    AR Kavitha, M Ramya, TN Charanya, PL Pansy, E Bhuvaneswari
    International Conference on ICT for Sustainable Development, 37-57 , 2025
    2025
  • Advanced Brain Tumour Detection Using YOLOv11 with Swin Transformer and Transfer Learning
    E Bhuvaneswari, GA Ranjath, SA Steni Dev, V Vishva, RF Valan, V Harish
    International Conference on Web Intelligence and Human-Machine Interaction … , 2025
    2025
    Citations: 1
  • A deep learning-driven multi-layer digital twin framework with miot for precision oncology in cancer diagnosis
    VR Golden Nancy 1 , E. Bhuvaneswari 2
    Journal of Intelligent Systems and Internet of Things 17 (1), 16-26 , 2025
    2025
    Citations: 4
  • A human-centered hybrid AI framework for optimizing emergency triage in resource-constrained settings
    E Bhuvaneswari, KDV Prasad, M Ashraf, S Jadhav, TKRK Rao, TS Rani
    Intelligence-Based Medicine 12, 100311 , 2025
    2025
    Citations: 14
  • Community Using Deep Learning
    VA Devi, E Bhuvaneswari, RK Tummala
    Signal Processing, Telecommunication and Embedded Systems with AI and ML … , 2024
    2024
  • Iterative Deepening Chess Engine with Alpha Beta Pruning
    E Kodhai, E Bhuvaneswari, VA Devi, ST Preethi
    2024 International Conference on Smart Technologies for Sustainable … , 2024
    2024
  • Smart Detection Framework for Rapid Emergency Response
    SR Arjun S,Bhuvaneshwari E,Sundara Rajulu Navaneethakrishnan,Sathish Kumar P. J
    2nd International Conference on Sustainable Computing and Smart Systems … , 2024
    2024
    Citations: 3
  • 5 Convergence of Modern Technologies for Data
    W Ahmad, V Arulkumar, K Parthiban, E Bhuvaneswari, M Arif, ...
    Wireless Communication Technologies: Roles, Responsibilities, and Impact of … , 2024
    2024
  • Convergence of Modern Technologies for Data Architectures
    W Ahmad, V Arulkumar, K Parthiban, E Bhuvaneswari, M Arif, ...
    Wireless Communication Technologies, 82-100 , 2024
    2024
    Citations: 42
  • Influence of Soret and Dufour Impacts on Casson Fluid Flow in a Channel Embedded in a Porous Mediu
    NMK Azhagu Ramar1 , E. Bhuvaneswari 2 , R. Nirmalkumar3 , P. Abhilash4 , M ...
    Advances in Nonlinear Variational Inequalities-DOI: https://doi.org/10.52783 … , 2024
    2024
  • Single image dehazing using a channel and pixel attention network
    VA Devi, E Bhuvaneswari, AAA Mary
    2024 Second International Conference on Emerging Trends in Information … , 2024
    2024
    Citations: 3
  • Scalable local recoding anonymization to preserve privacy in big data mining
    E Bhuvaneswari, R Kalaiselvi, KR Devi, RK Tummala, G Shanthi
    AIP Conference Proceedings 2742 (1), 020022 , 2024
    2024
    Citations: 1
  • Ontology based patient information discovery using iot healthcare monitoring system
    V Arulkumar, G Kalpana, C Selvan, E Bhuvaneswari, G Divya
    AIP Conference Proceedings 2742 (1), 020006 , 2024
    2024
  • A novel approach for multi-user authentication framework for biometric applications using fusion methods
    V Arulkumar, E Bhuvaneswari, S Sridhar, V Uma, P Nancy
    AIP Conference Proceedings 2742 (1), 020008 , 2024
    2024
  • Wireless Communication Technologies
    A Wakeel, V Arulkumar, K Parthiban, E Bhuvaneswari, A Mohammad, ...
    CRC Press, , 2024
    2024
    Citations: 34
  • Decentralized hybrid intrusion detection system for cyber attack identification using machine learning
    VA Devi, E Bhuvaneswari, RK Tummala
    2023 International Conference on Data Science, Agents & Artificial … , 2023
    2023
    Citations: 15
  • Fuzzy Search with Multi-Keyword Security and Improved Service Quality
    E Bhuvaneswari, VA Devi, R Gowri
    2023 International Conference on Data Science, Agents & Artificial … , 2023
    2023

MOST CITED SCHOLAR PUBLICATIONS

  • Convergence of Modern Technologies for Data Architectures
    W Ahmad, V Arulkumar, K Parthiban, E Bhuvaneswari, M Arif, ...
    Wireless Communication Technologies, 82-100 , 2024
    2024
    Citations: 42
  • Wireless Communication Technologies
    A Wakeel, V Arulkumar, K Parthiban, E Bhuvaneswari, A Mohammad, ...
    CRC Press, , 2024
    2024
    Citations: 34
  • Unsupervised Feature Learning for Text Pattern Analysis with Emotional Data Collection: A Novel System for Big Data Analytics
    PN Yusuf Perwej, E Bhuvaneswari, Saroj Kumar, V Arulkumar
    2022 International Conference on Advanced Computing Technologies and … , 2022
    2022
    Citations: 28
  • Decentralized hybrid intrusion detection system for cyber attack identification using machine learning
    VA Devi, E Bhuvaneswari, RK Tummala
    2023 International Conference on Data Science, Agents & Artificial … , 2023
    2023
    Citations: 15
  • A human-centered hybrid AI framework for optimizing emergency triage in resource-constrained settings
    E Bhuvaneswari, KDV Prasad, M Ashraf, S Jadhav, TKRK Rao, TS Rani
    Intelligence-Based Medicine 12, 100311 , 2025
    2025
    Citations: 14
  • An Enhancement in Data Security Using Trellis Algorithm with DNA Sequences in Symmetric DNA Cryptography
    EB K. Ramadevi
    Wireless Personal Communications 129 (DOI:10.1007/s11277-022-10102-8), 387–398 , 2022
    2022
    Citations: 13
  • An Improvised Ensemble Mechanism for Improving Bandwidth in Optical Network
    NK V. Anjana Devi 1, Rama krishna Tummala 2, E. Bhuvaneswari 1
    ICTACT Journal on Communication Technology,Pagination: 13 (No 4 (2022 … , 2022
    2022
    Citations: 5
  • A deep learning-driven multi-layer digital twin framework with miot for precision oncology in cancer diagnosis
    VR Golden Nancy 1 , E. Bhuvaneswari 2
    Journal of Intelligent Systems and Internet of Things 17 (1), 16-26 , 2025
    2025
    Citations: 4
  • Detection and categorization of brain tumors through deep learning
    VA Devi, E Bhuvaneswari, RK Tummala
    2023 International Conference on Data Science, Agents & Artificial … , 2023
    2023
    Citations: 4
  • Security Enhancement Using Quantum Cryptography in WSN
    SC Gupta, B Singh, M Amjad, M Gopianand, E Bhuvaneswari
    19-20 March 2021 , 2021
    2021
    Citations: 4
  • Smart Detection Framework for Rapid Emergency Response
    SR Arjun S,Bhuvaneshwari E,Sundara Rajulu Navaneethakrishnan,Sathish Kumar P. J
    2nd International Conference on Sustainable Computing and Smart Systems … , 2024
    2024
    Citations: 3
  • Single image dehazing using a channel and pixel attention network
    VA Devi, E Bhuvaneswari, AAA Mary
    2024 Second International Conference on Emerging Trends in Information … , 2024
    2024
    Citations: 3
  • WITHDRAWN: Depression detection using data mining algorithms from social media context
    RK Tummala, E Bhuvaneswari, TJ John, SP Karthi, KP Arjun
    Materials Today: Proceedings , 2021
    2021
    Citations: 3
  • WITHDRAWN: Convolutional neural network use chest radiography images for identification of COVID-19
    D Murali, E Bhuvaneswari, S Parvathi, ANS Kumar
    Materials Today: Proceedings , 2020
    2020
    Citations: 3
  • Advanced Brain Tumour Detection Using YOLOv11 with Swin Transformer and Transfer Learning
    E Bhuvaneswari, GA Ranjath, SA Steni Dev, V Vishva, RF Valan, V Harish
    International Conference on Web Intelligence and Human-Machine Interaction … , 2025
    2025
    Citations: 1
  • Scalable local recoding anonymization to preserve privacy in big data mining
    E Bhuvaneswari, R Kalaiselvi, KR Devi, RK Tummala, G Shanthi
    AIP Conference Proceedings 2742 (1), 020022 , 2024
    2024
    Citations: 1
  • Adaptive RL-based AI for real-time dynamic navigation in autonomous robot
    VA Devi, E Bhuvaneswari
    International Conference on Advancing Technology in Engineering and Science … , 2025
    2025
  • Automated trajectory optimization framework for extended space missions
    VA Devi, E Bhuvaneswari
    International Conference on Advancing Technology in Engineering and Science … , 2025
    2025
  • Establishing a secure data transfer framework for legacy cloud migration
    VA Devi, E Bhuvaneswari
    International Conference on Advancing Technology in Engineering and Science … , 2025
    2025
  • Mamdani Fuzzy Inference System Based on Multi-Textural Biomarkers for Alzheimer’s Stage Detection
    AR Kavitha, M Ramya, TN Charanya, PL Pansy, E Bhuvaneswari
    International Conference on ICT for Sustainable Development, 37-57 , 2025
    2025