Dr. R. Thanga Selvi

@srmist.edu.in

Assistant Professor, Computing Technologies / Engineering and Technology
SRM Institute of Science and Technology

Dr. R. Thanga Selvi


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https://researchid.co/golda.selvi

RESEARCH, TEACHING, or OTHER INTERESTS

Computer Science, Artificial Intelligence, Computational Theory and Mathematics, Computer Engineering
23

Scopus Publications

127

Scholar Citations

6

Scholar h-index

2

Scholar i10-index

Scopus Publications

  • Crossplane: A Unified Framework for Multi-Cloud Infrastructure Management
    Nikhil Kumar, R. Thanga Selvi
    Proceedings of 6th International Conference on Intelligent Communication Technologies and Virtual Mobile Networks Icicv 2025, 2025
    The implementation of hybrid cloud combined with multi-cloud systems makes it difficult to sustain infrastructure consistency across different cloud platform installations. When using classic Infrastructure as Code (IaC) tools organizations need to handle specific provider configurations at a high cost while facing decreased interoperability between providers. The research examines how Crossplane operates as a native Kubernetes control plane that delivers unified declarative scalable cloud infrastructure management capabilities. The project develops a Crossplane-based framework that enables users to control AWS resources through EKS cluster deployments and Crossplane AWS provider installation using S3 bucket declaration configuration. Experimental findings demonstrate that Crossplane operates efficiently to enforce infrastructure state consistency and maintains automated resource management with multiple cloud integration capabilities. Organizations can handle cloud-native resources effectively through Kubernetes management because Crossplane functions as a provider-agnostic system which fulfills automation needs.
  • Prediction of Nutrient Deficiency in Crops using Plant Health Data
    Thanga Selvi R, Parchuri Mohana Pravallika, Katta Manikanta Kumar, Devata Varalakshmi
    Proceedings of 6th International Conference on Intelligent Communication Technologies and Virtual Mobile Networks Icicv 2025, 2025
    Nutrition of a crop is very essential for the health conditions during its growth stages and yield. A plant development is dependent on various nutrients absorbed from the natural environment or fertilizer supplements. The shortage or lack of essentials nutrients in one of the crucial factors which impacts the overall crop yield. Computer vision based phenomena have become an emerging area in, which refers to nitrogen(N),phosphorus(P), and consists of potassium flora and means of the nutrient deficiency to find the accessibility growth, energy, and the roots consists of the photosynthesis, hence there nutrients are vital for it growth, energy transfer, and overall plant wellness deficiency might damage the flora and the fauna of nutrient deficiency of that would be farmers ran to identify and precise the nutrient deficiency. Definitely many NPK shortages can be fixed using methods. Distinguishing between the NPK and the default manager the artificial images may covert and predict the correct nutrient deficiencies in crop using the required plant health data. By using the machine learning can be able to detect the nutrient deficiencies in crop
  • Early Detection of Lung Cancer using Hybrid Histological Image Analysis with XGBoost and LightGBM in MATLAB
    R. Thangaselvi, K. Siva Naga Vamsi Krishna, O. Sudheer Kumar, A. Manisai Rishik
    Proceedings of 6th International Conference on Intelligent Communication Technologies and Virtual Mobile Networks Icicv 2025, 2025
    Lung cancer remains one of the deadliest diseases globally due to the lack of precise and early diagnostic methods. This study proposes a hybrid AI-driven framework for lung cancer detection using histological images, integrating deep learning-based and handcrafted feature extraction with ensemble machine learning models, XGBoost and LightGBM. The framework enhances image quality through noise reduction and contrast adjustment before extracting relevant features for classification. By combining predictions from both classifiers, the model improves accuracy, sensitivity, and specificity compared to traditional methods. Experimental results demonstrate the effectiveness of this approach in automating histopathological analysis, enabling faster and more reliable lung cancer detection, which can significantly enhance patient survival rates.
  • An Effective Real Time Crop Recommendation Using Machine Learning and Web Development
    R. Thanga Selvi, Angeline Lydia, Ponnapati Madhu Jashwanth, Mannepalli Umesh, Maram Suresh Reddy
    2025 IEEE International Conference on Advances in Computing Research on Science Engineering and Technology Acroset 2025, 2025
    Utilizing cutting-edge technologies, an effective crop recommendation system maximizes crop selection, boosts yields, and encourages sustainable farming methods. Comprehensive information on soil properties, weather trends, and past crop performance is gathered by the system. It evaluates this data to forecast which crops might thrive under particular circumstances using machine learning algorithms like Random Forest and Support Vector Machines. IoT sensors give the system up-to-date data by monitoring soil and environmental variables in real-time. Farmers are able to access recommendations, enter data, and obtain actionable insights thanks to the system's user-friendly interface. Principles of explainable AI guarantee clear and intelligible advice, fostering farmer confidence and efficient system utilization. In order to help farmers optimize yields, an intelligent crop recommendation system suggests crops that are most likely to flourish under the given circumstances, guaranteeing effective use of resources and encouraging sustainable farming. Future directions include integrating with other agricultural technologies, improving prediction models, and educating users, despite obstacles including assuring data quality, promoting acceptance, and scalability. By drastically cutting down on farming's trial-and- error process, this strategy ensures more efficient and sustainable agricultural methods while also saving time and money.
  • Mobility-Aware RPL Protocol to Enhance the Quality of Service Metrics in the Internet of Things
    P. Arivubrakan, T. Kujani, Sathiya Priya S, Thanga Selvi R, V. Usha, Bhuvanya. R
    3rd International Conference on Electronics and Renewable Systems Icears 2025 Proceedings, 2025
    Internet of Things (IoT) is an emerging technology in today’s era, to connect and communicate with embedded sensors and actuators through the Internet. Routing is essential for establishing the communication between the sender and receiver in a resource-constrained environment. RPL is the standardized routing protocol for low-power lossy networks, but it consumes more energy in their mobility environment. The proposed MT algorithm reduces the listen-only period and also optimizes the quality-of-service metric in the mobility environment by considering the objective function parameters as link quality and energy. The performance is simulated and analyzed in Contiki 3.0, Cooja simulator, where energy is reduced and the packet delivery ratio outperforms the proposed algorithm.
  • Securing sensitive patient data in healthcare settings using blockchain technology
    R. Thanga Selvi, R. Elakya, U. Vignesh
    Blockchain and Iot Approaches for Secure Electronic Health Records Ehr, 2024
    The utilization of electronic health record (EHR) has become common in the healthcare industry, enabling the storage and exchange of patients' medical information across different healthcare organizations. However, concerns regarding the security and privacy of patient data have arisen due to the centralized nature of conventional systems. To address these issues, a blockchain-based solution has been proposed to enhance data security and system efficiency. This chapter introduces a blockchain-based system designed to manage and secure patient data within a single record controlled by the patient. The Ethereum network was utilized to develop this decentralized system. The solution not only empowers users by granting them enhanced authority over their confidential information but also advocates for the incorporation of blockchain advancements within the healthcare domain. The proposed system offers improved data security and accessibility, addressing concerns related to the privacy and integrity of patient records in traditional EHR systems.
  • Synergizing AI and blockchain: Transforming aerospace engineering operations
    R. Elakya, R. Thanga Selvi, T. Manoranjitham, S. Shanthana
    AI and Blockchain Optimization Techniques in Aerospace Engineering, 2024
    The aerospace industry stands on the brink of transformative advancements with the convergence of artificial intelligence (AI) and blockchain technologies. The chapter commences by highlighting the imperative role of AI and blockchain in the aerospace sector. Subsequently, the chapter delves into the distinct applications of AI within aerospace engineering. Autonomous systems, empowered by AI, are explored for their influence on unmanned aerial vehicles (UAVs), spacecraft navigation, and decision-making. The integration of AI-driven predictive maintenance algorithms emerges as a pivotal strategy to optimize maintenance schedules, reduce downtime, and augment safety through accurate prognostics. Further, the utilization of AI for flight path optimization is detailed, showcasing its ability to reduce fuel consumption and minimize environmental impact. The role of AI extends to the realms of aerodynamics, design, and materials science, accelerating the creation of innovative aircraft and spacecraft designs.
  • An Efficient River Water Quality Prediction and Classification Model using Metaheuristics based Kernel Extreme Learning Machine
    R. Thanga Selvi, T.C. Subbu Lakshmi, R. AntoArockia Rosaline
    E3s Web of Conferences, 2024
    In the previous years, water quality has been susceptible to different pollutants. Also, the various environmental conditions like vegetation, climate and basin lithology affects the quality of the river water naturally. So, the prediction of water quality (WQ) becomes a major process to control and basin lithology affects the quality of the river water naturally pollution. The rise of artificial intelligence (AI) manners can be utilized for designing predictive methods for water quality index (WQI) and classification. This study focuses on the design of metaheuristics-based kernel extreme learning machine (MBKELM) for river water quality prediction and classification. The proposed MBKELM model aims to predict and classify the quality of river water into different classes. In addition, a prediction and classification model using KELM is derived to appropriately determine the water quality. Moreover, the parameter tuning of the KELM model takes place by pigeon optimization algorithm (POA). A wide range of experimental analyses was performed on benchmark datasets and the experimental outcomes reported the supremacy of the MBKELM technique over the recent techniques. The results stated that the proposed MBKELM model has accomplished minimal MSE and RMSE values. On examining the results in terms of MSE on training set, the MBKELM model has accomplished a lower MSE of 0.00257 whereas the existing model has gained a higher MSE of 0.00336. Also, on examining the results in terms of RMSE on testing set, the MBKELM manner has accomplished a lesser RMSE of 0.05070 whereas the existing model algorithm has gained a higher RMSE of 0.05800.
  • Ensemble of Deep Learning Enabled Tamil Handwritten Character Recognition Model
    R. Thanga Selvi
    Lecture Notes in Electrical Engineering, 2024
  • Cooperative Task Execution in Insect-Inspired Robot Swarms Using Reinforcement Learning
    Exploring the Micro World of Robotics Through Insect Robots, 2024
  • Quantum Resnet18 for Classifying and Predicting the Maize Leaf Diseases
    T. Kujani, Bhuvanya. R, Sathya T, P. Arivubrakan, V. Usha, Thangaselvi. R
    2024 International Conference on Recent Advances in Electrical Electronics Ubiquitous Communication and Computational Intelligence Raeeucci 2024, 2024
  • An Optimal Bidirectional Gated Recurrent Neural Network Model for Crop Yield Prediction
    R. ThangaSelvi, M. Sathish
    Proceedings 5th International Conference on Smart Systems and Inventive Technology Icssit 2023, 2023
  • Improvement of Graph-Based Assets using Blockchain Quality Control
    R. Thanga Selvi, T. C. Subbu Lakshmi, D. Karunkuzhali, R. Anto Arockia Rosaline
    International Conference on Innovative Data Communication Technologies and Application Icidca 2023 Proceedings, 2023
  • Real-Time Vehicle Speed Monitoring and Alerting System to Prevent Road Accidents
    W. Deva Priya, S. Yuvaraj, V. Sujatha, R. Thanga Selvi
    Proceedings of the 4th International Conference on Smart Electronics and Communication Icosec 2023, 2023
  • Advanced ML Techniques for Real-Time Air Quality Prediction in Megacities: A Comparative Study
    U. Vignesh, R. Elakya, R.Thanga Selvi, S. Shanthana
    2nd International Conference on Automation Computing and Renewable Systems Icacrs 2023 Proceedings, 2023
  • Privacy-Preserving Data Mining Process in Industry
    T.C. Subbu Lakshmi, R. Anto Arockia Rosaline, R. Thanga Selvi, D. Karunkuzhali, S. Lavanya
    Proceedings of the International Conference on Intelligent and Innovative Technologies in Computing Electrical and Electronics Iciitcee 2023, 2023
  • Robust Node Localization with Intrusion Detection for Wireless Sensor Networks
    R. Punithavathi, R. Thanga Selvi, R. Latha, G. Kadiravan, V. Srikanth, Neeraj Kumar Shukla
    Intelligent Automation and Soft Computing, 2022
  • An optimal artificial neural network based big data application for heart disease diagnosis and classification model
    R. Thanga Selvi, I. Muthulakshmi
    Journal of Ambient Intelligence and Humanized Computing, 2021
  • Modelling the map reduce based optimal gradient boosted tree classification algorithm for diabetes mellitus diagnosis system
    R. Thanga Selvi, I. Muthulakshmi
    Journal of Ambient Intelligence and Humanized Computing, 2021
  • An Extensive Survey on Recent Machine Learning Algorithms for Diabetes Mellitus Prediction
    R. Thanga Selvi, I. Muthulakshmi
    Lecture Notes on Data Engineering and Communications Technologies, 2020
  • An Extensive Survey on Evolutionary Algorithm Based Kidney Disease Prediction
    R. Thanga selvi, I. Muthulakshmi
    2019 International Conference on Recent Advances in Energy Efficient Computing and Communication Icraecc 2019, 2019
  • A state of art heart disease prediction techniques based on evolutionary algorithms
    International Journal of Pharmaceutical Research, 2019
  • Improving the efficiency of MapReduce scheduling algorithm in Hadoop
    R. Thangaselvi, S. Ananthbabu, S. Jagadeesh, R. Aruna
    Proceedings of the 2015 International Conference on Applied and Theoretical Computing and Communication Technology Icatcct 2015, 2016

RECENT SCHOLAR PUBLICATIONS

  • Medicine recommendation system using machine learning
    RT Selvi, D Ghosh, A Ranjan, A Rana
    Artificial Intelligence and Sustainable Innovation, 550-556 , 2026
    2026
  • An Effective Real Time Crop Recommendation Using Machine Learning and Web Development
    RT Selvi, A Lydia, PM Jashwanth, M Umesh, MS Reddy
    2025 IEEE International Conference on Advances in Computing Research On … , 2025
    2025
  • Crossplane: A Unified Framework for Multi-Cloud Infrastructure Management
    N Kumar, RT Selvi
    2025 6th International Conference on Intelligent Communication Technologies … , 2025
    2025
  • Cooperative Task Execution in Insect-Inspired Robot Swarms Using Reinforcement Learning
    R Elakya, S Surya, G Abinaya, T Manoranjitham, RT Selvi
    Exploring the Micro World of Robotics Through Insect Robots, 197-212 , 2025
    2025
  • An efficient river water quality prediction and classification model using metaheuristics based kernel extreme learning machine
    RT Selvi, TC Subbu Lakshmi, R AntoArockia Rosaline
    E3S web of conferences 477, 00046 , 2024
    2024
    Citations: 3
  • Securing Sensitive Patient Data in Healthcare Settings Using Blockchain Technology
    RT Selvi, R Elakya, U Vignesh
    Blockchain and IoT Approaches for Secure Electronic Health Records (EHR), 73-88 , 2024
    2024
    Citations: 2
  • Leveraging Blockchain Technology and Smart Contracts for Intelligent Supply Chain Management
    R Elakya, RT Selvi, S Girirajan, A Vidhyavani
    Bio-Inspired Optimization Techniques in Blockchain Systems, 167-191 , 2024
    2024
    Citations: 1
  • Synergizing AI and Blockchain: Transforming Aerospace Engineering Operations
    R Elakya, RT Selvi, T Manoranjitham, S Shanthana
    AI and Blockchain Optimization Techniques in Aerospace Engineering, 193-209 , 2024
    2024
    Citations: 1
  • Advanced ml techniques for real-time air quality prediction in megacities: A comparative study
    U Vignesh, R Elakya, RT Selvi, S Shanthana
    2023 2nd International Conference on Automation, Computing and Renewable … , 2023
    2023
    Citations: 3
  • Real-Time Vehicle Speed Monitoring and Alerting System to Prevent Road Accidents
    WD Priya, S Yuvaraj, V Sujatha, RT Selvi
    2023 4th International Conference on Smart Electronics and Communication … , 2023
    2023
    Citations: 4
  • Improvement of Graph-Based Assets using Blockchain Quality Control
    RT Selvi, TCS Lakshmi, D Karunkuzhali, RAA Rosaline
    2023 International Conference on Innovative Data Communication Technologies … , 2023
    2023
    Citations: 3
  • Privacy-preserving data mining process in industry
    TCS Lakshmi, RAA Rosaline, RT Selvi, D Karunkuzhali, S Lavanya
    2023 International Conference on Intelligent and Innovative Technologies in … , 2023
    2023
    Citations: 5
  • An optimal bidirectional gated recurrent neural network model for crop yield prediction
    R ThangaSelvi, M Sathish
    2023 5th International Conference on Smart Systems and Inventive Technology … , 2023
    2023
    Citations: 6
  • Robust Node Localization with Intrusion Detection for Wireless Sensor Networks.
    R Punithavathi, RT Selvi, R Latha, G Kadiravan, V Srikanth, NK Shukla
    Intelligent Automation & Soft Computing 33 (1) , 2022
    2022
    Citations: 40
  • Histogram of Gradients with Deep Features in Coronavirus-19 Diagnosis and Classification Model
    RT SELVI
    Artificial Intelligence and Evolutionary Computations in Engineering Systems … , 2022
    2022
    Citations: 2
  • Ensemble of deep learning enabled Tamil handwritten character recognition model
    R Thanga Selvi
    International Conference on Big Data, Machine Learning, and Applications … , 2021
    2021
    Citations: 1
  • Modelling the map reduce based optimal gradient boosted tree classification algorithm for diabetes mellitus diagnosis system
    RT SELVI
    Journal of Ambient Intelligence and Humanized Computing 12 (2), 1717-1730 , 2021
    2021
    Citations: 31
  • AN EFFICIENT ANALYSIS AND INTRUSION DETECTION SYSTEM TO PREVENT THE NETWORK ATTACKS FOR SAFE DATA TRANSMISSION
    RT SELVI
    Journal of Natural Remedies 21 (10), 79-90 , 2021
    2021
  • An Efficient Zernike Moments with Logistic Regression Classifier based Skin Lesion Diagnosis using Dermoscopic Images
    RT SELVI
    European Journal of Molecular & Clinical Medicine 7 (9), 1732-1742 , 2020
    2020
  • An optimal artificial neural network based big data application for heart disease diagnosis and classification model. J Ambient Intell Human Comput
    R Thanga Selvi, I Muthulakshmi
    Springer, Berlin , 2020
    2020
    Citations: 7

MOST CITED SCHOLAR PUBLICATIONS

  • Robust Node Localization with Intrusion Detection for Wireless Sensor Networks.
    R Punithavathi, RT Selvi, R Latha, G Kadiravan, V Srikanth, NK Shukla
    Intelligent Automation & Soft Computing 33 (1) , 2022
    2022
    Citations: 40
  • Modelling the map reduce based optimal gradient boosted tree classification algorithm for diabetes mellitus diagnosis system
    RT SELVI
    Journal of Ambient Intelligence and Humanized Computing 12 (2), 1717-1730 , 2021
    2021
    Citations: 31
  • Intelligent Communication Technologies and Virtual Mobile Networks: ICICV 2019
    S Balaji, Á Rocha, YN Chung
    Springer , 2019
    2019
    Citations: 9
  • An optimal artificial neural network based big data application for heart disease diagnosis and classification model. J Ambient Intell Human Comput
    R Thanga Selvi, I Muthulakshmi
    Springer, Berlin , 2020
    2020
    Citations: 7
  • An optimal bidirectional gated recurrent neural network model for crop yield prediction
    R ThangaSelvi, M Sathish
    2023 5th International Conference on Smart Systems and Inventive Technology … , 2023
    2023
    Citations: 6
  • Improving the efficiency of MapReduce scheduling algorithm in Hadoop
    RT SELVI
    2015 International Conference on Applied and Theoretical Computing and … , 2015
    2015
    Citations: 6
  • Privacy-preserving data mining process in industry
    TCS Lakshmi, RAA Rosaline, RT Selvi, D Karunkuzhali, S Lavanya
    2023 International Conference on Intelligent and Innovative Technologies in … , 2023
    2023
    Citations: 5
  • Real-Time Vehicle Speed Monitoring and Alerting System to Prevent Road Accidents
    WD Priya, S Yuvaraj, V Sujatha, RT Selvi
    2023 4th International Conference on Smart Electronics and Communication … , 2023
    2023
    Citations: 4
  • An efficient river water quality prediction and classification model using metaheuristics based kernel extreme learning machine
    RT Selvi, TC Subbu Lakshmi, R AntoArockia Rosaline
    E3S web of conferences 477, 00046 , 2024
    2024
    Citations: 3
  • Advanced ml techniques for real-time air quality prediction in megacities: A comparative study
    U Vignesh, R Elakya, RT Selvi, S Shanthana
    2023 2nd International Conference on Automation, Computing and Renewable … , 2023
    2023
    Citations: 3
  • Improvement of Graph-Based Assets using Blockchain Quality Control
    RT Selvi, TCS Lakshmi, D Karunkuzhali, RAA Rosaline
    2023 International Conference on Innovative Data Communication Technologies … , 2023
    2023
    Citations: 3
  • Securing Sensitive Patient Data in Healthcare Settings Using Blockchain Technology
    RT Selvi, R Elakya, U Vignesh
    Blockchain and IoT Approaches for Secure Electronic Health Records (EHR), 73-88 , 2024
    2024
    Citations: 2
  • Histogram of Gradients with Deep Features in Coronavirus-19 Diagnosis and Classification Model
    RT SELVI
    Artificial Intelligence and Evolutionary Computations in Engineering Systems … , 2022
    2022
    Citations: 2
  • Leveraging Blockchain Technology and Smart Contracts for Intelligent Supply Chain Management
    R Elakya, RT Selvi, S Girirajan, A Vidhyavani
    Bio-Inspired Optimization Techniques in Blockchain Systems, 167-191 , 2024
    2024
    Citations: 1
  • Synergizing AI and Blockchain: Transforming Aerospace Engineering Operations
    R Elakya, RT Selvi, T Manoranjitham, S Shanthana
    AI and Blockchain Optimization Techniques in Aerospace Engineering, 193-209 , 2024
    2024
    Citations: 1
  • Ensemble of deep learning enabled Tamil handwritten character recognition model
    R Thanga Selvi
    International Conference on Big Data, Machine Learning, and Applications … , 2021
    2021
    Citations: 1
  • An Extensive Survey on Evolutionary Algorithm Based Kidney Disease Prediction
    RT SELVI
    2019 International Conference on Recent Advances in Energy-efficient … , 2019
    2019
    Citations: 1
  • An Extensive Survey on Recent Machine Learning Algorithms for Diabetes Mellitus Prediction
    RT SELVI
    Intelligent Communication Technologies and Virtual Mobile Networks, 328-335 , 2019
    2019
    Citations: 1
  • A State of art Heart Disease Prediction Techniques based on Evolutionary Algorithms
    RT SELVI
    International Journal Of Pharmaceutical Research(IJPR) 11 (1), 682-687 , 2019
    2019
    Citations: 1
  • Medicine recommendation system using machine learning
    RT Selvi, D Ghosh, A Ranjan, A Rana
    Artificial Intelligence and Sustainable Innovation, 550-556 , 2026
    2026