Computer Networks and Communications, Computer Science, Computer Engineering, Artificial Intelligence
14
Scopus Publications
87
Scholar Citations
5
Scholar h-index
4
Scholar i10-index
Scopus Publications
An IoT and Blockchain Framework for Secure Agricultural Food Supply Chains R. Kesavan, R. Palanikumar Proceedings of the 6th International Conference on Smart Electronics and Communication Icosec 2025, 2025 The agricultural food supply system suffers from a lack of overall transparency, excessive food waste, and inadequate monitoring, among other problems. This work proposes a system that leverages blockchain (BC) technology and the Internet of Things (IoT) to enhance the efficiency, security, and traceability of agricultural food supply chains. Developing a distributed network mostly aims to track food in real time from farm to consumer. BC technology checks and maintains data on storage, transportation, and environmental conditions; IoT sensors track and record data on these aspects as well. The recommended strategy helps with data tampering. The results include decreased spoil ability, on-time delivery, and better data correctness. At last, IoT combined with BC offers a reliable and open foundation for upgrading agricultural supply chain systems.
Optimization of Renewable Energy Resources using an Internet-of-Things and Machine Learning Algorithm Ramathilagam A, Mary Nivetha J, Deepshiha Narayan G, Palanikumar R, Arunkumar R International Conference on Advanced Computing Technologies Icoact 2025, 2025 Energy power development and the heavy reliance on traditional sources are creating challenges for sustainable growth. Solar power offers a clean and promising alternative, but it is not without its own set of issues, such as intermittent supply and inefficiency. This paper introduces a smarter way to manage renewable energy: a system designed to combine solar energy generation, storage, and automated management to address these gaps. By using real-time monitoring and advanced technologies, such as Support Vector Machines (SVM) and Maximum PowerPoint Tracking (MPPT), the system helps users make the most of their energy. What makes it even better is its ability to send unused energy back to the grid after meeting household or industrial needs, thereby allowing users to earn subsidies to contribute to a cleaner energy network. This paper outlines a practical, forward-thinking approach to renewable energy that is not only about efficiency but also about creating a sustainable future for all.
Revolutionizing Legal Workflows: Advanced AI Techniques for Document Summarization, Legal Translation, and Conversational Assistance Arun Kumar R, Aswanth V R, Saikrishna V, Sairam N, Palanikumar R International Conference on Advanced Computing Technologies Icoact 2025, 2025 The increasing complexity and volume of legal documents necessitate more efficient processing and analysis. we propose an AI-driven approach to streamline legal services by integrating advanced natural language processing (NLP) models for summarization, translation, and conversational assistance. We utilize the allenai/led-base-16384 model for summarization of extensive legal documents, Facebook M2M-100 for multi-lingual translation, and mistralai/Mistral-7B-Instruct-v0.2 for legal conversational AI. The proposed system enhances legal services by providing quick, accurate summaries, translations, and AI-driven legal advice, thereby improving accessibility and reducing time and cost for legal professionals. Experimental results demonstrate the efficiency and accuracy of the system on various legal documents, highlighting its potential to revolutionize legal workflows.
A Hybrid Statistical and Web-based Framework for Accurate Sales Forecasting using SARIMAX Rajasathiya K, Palanikumar R, Elango R, Brindha G, Sudha Juliet P, Ramya R 4th International Conference on Automation Computing and Renewable Systems Icacrs 2025 Proceedings, 2025 This paper presents an intelligent, data-driven forecasting system based on the Seasonal AutoRegressive Integrated Moving Average with Exogenous Variables (SARIMAX) model. The proposed system integrates machine learning algorithms with modern web technologies to create an end-to-end forecasting platform that is accurate, scalable, and user-friendly. The system utilizes the seasonal autoregressive moving average model to capture both seasonal trends and external factors influencing sales. The optimal parameters are auto-tuned using AIC minimization, and the model generates future sales forecasts with confidence intervals indicating prediction reliability. Through this implementation, the system demonstrates how statistical forecasting techniques can be combined with modern Web frameworks to provide practical, explainable, and efficient business intelligence tools.
Stacking Ensemble Learning for High-Accuracy Classification and Analysis of Darknet Traffic using the CIC-Darknet2020 Dataset K. Manikandan, R. Palanikumar, R. Saravanan, M. Shenbagaraj, J. Sujith Ayyanar, K. Rajasathiya, R. Saravanakumar Proceedings of IEEE International Conference for Women in Innovation Technology and Entrepreneurship Icwite 2025, 2025 The “darknet,” a section of the internet that consumers often do not perceive as accessible for machine-tomachine communication, is sometimes mentioned by cyber intelligence organizations. Evaluating the possible risks to the network must precede any initiatives to enhance its defenses. This study introduces a unique method for machine learning classification called stacking ensemble learning, aimed at assessing and categorizing darknet data. This study attained a 98% accuracy rate in differentiating between Darknet and benign traffic using ensembles of artificial intelligence methodologies and the recently released CIC-Darknet2020 dataset. It had a 97 % success rate in accurately identifying the specific program type accountable for the Darknet traffic. To further our understanding of Darknet traffic patterns, we used a game-theory-based approach to assess the outcomes of the features' influence on machine learning models. The dataset's producers have confirmed that our analysis is unprecedented, to the best of anyone's knowledge.
Deep Learning-Driven AI System for Multimodal Detection and Classification of Harmful Content on Social Networks R. Kesavan, R. Palanikumar, S. Surya Prakash, V. Vairamuthu, P. Vinoth, M. Stella Inba Mary, R. Saravanakumar Proceedings of IEEE International Conference for Women in Innovation Technology and Entrepreneurship Icwite 2025, 2025 This article addresses the significant issue of using deep learning techniques to detect and classify dangerous material in the framework of social networks. The ultimate goal of this project is to develop an artificial intelligence (AI) system that can identify unsuitable content across various media formats, including text, audio, and images. The system may identify potentially unsafe items using technologies such as Optical Character Recognition (OCR), Google Text-to-Speech (GTTS), and Natural Language Processing (NLP). Nowadays, this field of research must cope with problems including biased model outcomes and small datasets. The study comprehensively evaluates the efficacy of various strategies using standard measures, including accuracy, precision, recall, and F1measure. The findings indicate that, particularly with the Recurrent Neural Network (RNN) architecture, deep learning models are very successful. By facilitating the early detection and prevention of cyberbullying, our study contributes substantial new information towards the goal of creating safer and more inclusive societies, skillfully extracting data from social media platforms. Our models outperform prior research in identifying and classifying foul language thanks to our use of sophisticated preprocessing techniques and meticulous hyperparameter adjustment.
A Review of Machine Learning and IoT Approaches for the Soil Quality Assessment in Agricultural and Land Management Rajasathiya K, Palanikumar R Proceedings of the 4th International Conference on Ubiquitous Computing and Intelligent Information Systems Icuis 2024, 2024 This research paper examines several soil qualities, such as texture, structure, density, porosity, wetness, and pH, and how these affect agricultural productivity and soil management. It discusses how to analyze soil texture using mechanical screening and sedimentation techniques, as well as the link between soil density and pore space. The paper highlights the importance of soil moisture in plant growth and discusses various methods for monitoring soil moisture, including remote sensing. Additionally, it looks into how soil pH affects plant health and offers helpful suggestions for adjusting soil pH to maximize growing conditions. The literature review focuses on advances in machine learning and IoT technologies that improve soil analysis and prediction, emphasizing its potential for precision agriculture and sustainable land management. The conclusion emphasizes the need of understanding soil parameters in order to maximize agricultural outputs and the usefulness of advanced modelling approaches in establishing sustainable agricultural practices. This study finally demonstrates the importance of exact soil data for good agricultural decision-making and environmental management.
Cardiovascular Abnormalities Classification Model Using Machine Learning and Signal Processing Techniques International Journal of Intelligent Systems and Applications in Engineering, 2024
21 Efficient Trade Optimization Using Artificial Intelligence and Amazon Web Service Platform R Palanikumar, R Kirthika, R Arunkumar, A Ramathilagam Artificial Intelligence and Robotics: Transformative and Computational … , 2026 2026
A Hybrid Statistical and Web-based Framework for Accurate Sales Forecasting using SARIMAX K Rajasathiya, R Palanikumar, R Elango, G Brindha, P Sudha Juliet, ... 2025 4th International Conference on Automation, Computing and Renewable … , 2025 2025
Hybrid DL Model-based Effective Intrusion Detection System in IoT Networks B Sujitha, R Palanikumar, K Rajasathiya 2025 Third International Conference on Emerging Applications of Material … , 2025 2025
Deep Learning-Driven AI System for Multimodal Detection and Classification of Harmful Content on Social Networks R Kesavan, R Palanikumar, SS Prakash, V Vairamuthu, P Vinoth, ... 2025 IEEE International Conference for Women in Innovation, Technology … , 2025 2025
Stacking Ensemble Learning for High-Accuracy Classification and Analysis of Darknet Traffic using the CIC-Darknet2020 Dataset K Manikandan, R Palanikumar, R Saravanan, M Shenbagaraj, ... 2025 IEEE International Conference for Women in Innovation, Technology … , 2025 2025
An IoT and Blockchain Framework for Secure Agricultural Food Supply Chains R Kesavan, R Palanikumar 2025 6th International Conference on Smart Electronics and Communication … , 2025 2025
Optimization of Renewable Energy Resources using an Internet-of-Things and Machine Learning Algorithm A Ramathilagam, M Nivetha, R Palanikumar, R Arunkumar 2025 International Conference on Advanced Computing Technologies (ICoACT), 1-5 , 2025 2025 Citations: 1
Revolutionizing Legal Workflows: Advanced AI Techniques for Document Summarization, Legal Translation, and Conversational Assistance A Kumar, VR Aswanth, V Saikrishna, N Sairam, R Palanikumar 2025 International Conference on Advanced Computing Technologies (ICoACT), 1-4 , 2025 2025 Citations: 2
A review of machine learning and IoT approaches for the soil quality assessment in agricultural and land management K Rajasathiya, R Palanikumar 2024 4th International Conference on Ubiquitous Computing and Intelligent … , 2024 2024 Citations: 2
Performance Analysis of Predicting Brain Age Using Deep Learning Algorithms K Selvi Priya, C BalaSubramanian, A Ramathilagam, R Palanikumar, ... International Conference on Frontiers of Intelligent Computing: Theory and … , 2024 2024
Decentralized Social Networking Platform KJ R Palanikumar, Abinash S, Jeeva V International Journal of Scientific Research in Engineering and Management … , 2024 2024
AUTOMATIC HEAD LAMP CONTROLLER USING ARDUINO WITH ANTI COLLISION SYSTEM PR Marieswaran M, Raju SV, Maruthu U International Research Journal of Modernization in Engineering Technology … , 2024 2024
Real-time Classification of Brain States in Functional MRI Using Dynamic Connectivity Patterns and Machine Learning NHAR Gnanajeyaraman Rajaram, R.Palanikumar, Vinoth Pandian, A.Selvarani Journal of Electrical Systems 20 (5), 2095-2103 , 2024 2024
Comprehensive Survey of Deep Learning-Based Intrusion Detection and Prevention Systems for Secure Communication in the Internet of Things KM V. G. Saranya Vaishalini, A. Ramathilagam, R. Palanikumar, P. Raghavan, P ... International Journal of Intelligent Systems and Applications in Engineering … , 2024 2024 Citations: 8
Cardiovascular Abnormalities Classification Model Using Machine Learning and Signal Processing Techniques R 9. Venkataramanaiah, B., Anuradha, M., Balasubramanian, K., Gnanaprakasam ... International Journal of Intelligent Systems and Applications in Engineering … , 2024 2024 Citations: 12
Faulty node detection and recovery scheme for large‐scale wireless sensor network using hosted cuckoo optimization algorithm R Palanikumar, K Ramasamy, P Srinivasa Ragavan International journal of communication systems 35 (9), e5143 , 2022 2022 Citations: 20
Credit Card Fraud Detection using Random Forest Algorithm GM Palanikumar R, Archana V International Conference on Recent Trends in Engineering & Technology , 2022 2022
Prediction of Microbial Spoilage and Shelf-Life of Bakery wares uinsg Classifier and Clustering Algorithms PS Palanikumar R International Conference on Recent Innovations in Science and Engineering … , 2022 2022
IoT based Aquaponics monitoring and control system using Raspberry Pi AR Palanikumar R International Conference on Recent Innovations in Science and Engineering … , 2022 2022
Fault node detection using matrix calculus algorithm and reward andpunishment method in sensor networks R Palanikumar Ph.D Thesis , 2020 2020
MOST CITED SCHOLAR PUBLICATIONS
Effective failure nodes detection using matrix calculus algorithm in wireless sensor networks R Palanikumar, K Ramasamy Cluster Computing 22 (Suppl 5), 12127-12136 , 2019 2019 Citations: 22
Faulty node detection and recovery scheme for large‐scale wireless sensor network using hosted cuckoo optimization algorithm R Palanikumar, K Ramasamy, P Srinivasa Ragavan International journal of communication systems 35 (9), e5143 , 2022 2022 Citations: 20
Software defined network based self-diagnosing faulty node detection scheme for surveillance applications R Palanikumar, K Ramasamy Computer Communications 152, 333-337 , 2020 2020 Citations: 18
Cardiovascular Abnormalities Classification Model Using Machine Learning and Signal Processing Techniques R 9. Venkataramanaiah, B., Anuradha, M., Balasubramanian, K., Gnanaprakasam ... International Journal of Intelligent Systems and Applications in Engineering … , 2024 2024 Citations: 12
Comprehensive Survey of Deep Learning-Based Intrusion Detection and Prevention Systems for Secure Communication in the Internet of Things KM V. G. Saranya Vaishalini, A. Ramathilagam, R. Palanikumar, P. Raghavan, P ... International Journal of Intelligent Systems and Applications in Engineering … , 2024 2024 Citations: 8
Revolutionizing Legal Workflows: Advanced AI Techniques for Document Summarization, Legal Translation, and Conversational Assistance A Kumar, VR Aswanth, V Saikrishna, N Sairam, R Palanikumar 2025 International Conference on Advanced Computing Technologies (ICoACT), 1-4 , 2025 2025 Citations: 2
A review of machine learning and IoT approaches for the soil quality assessment in agricultural and land management K Rajasathiya, R Palanikumar 2024 4th International Conference on Ubiquitous Computing and Intelligent … , 2024 2024 Citations: 2
KNN Based Power Efficiency in Wireless Sensor Networks J Hemalatha, RP Kumar, K Ramasamy International Journal of Science, Engineering and Computer Technology 3 (1/2 … , 2013 2013 Citations: 2
Optimization of Renewable Energy Resources using an Internet-of-Things and Machine Learning Algorithm A Ramathilagam, M Nivetha, R Palanikumar, R Arunkumar 2025 International Conference on Advanced Computing Technologies (ICoACT), 1-5 , 2025 2025 Citations: 1
21 Efficient Trade Optimization Using Artificial Intelligence and Amazon Web Service Platform R Palanikumar, R Kirthika, R Arunkumar, A Ramathilagam Artificial Intelligence and Robotics: Transformative and Computational … , 2026 2026
A Hybrid Statistical and Web-based Framework for Accurate Sales Forecasting using SARIMAX K Rajasathiya, R Palanikumar, R Elango, G Brindha, P Sudha Juliet, ... 2025 4th International Conference on Automation, Computing and Renewable … , 2025 2025
Hybrid DL Model-based Effective Intrusion Detection System in IoT Networks B Sujitha, R Palanikumar, K Rajasathiya 2025 Third International Conference on Emerging Applications of Material … , 2025 2025
Deep Learning-Driven AI System for Multimodal Detection and Classification of Harmful Content on Social Networks R Kesavan, R Palanikumar, SS Prakash, V Vairamuthu, P Vinoth, ... 2025 IEEE International Conference for Women in Innovation, Technology … , 2025 2025
Stacking Ensemble Learning for High-Accuracy Classification and Analysis of Darknet Traffic using the CIC-Darknet2020 Dataset K Manikandan, R Palanikumar, R Saravanan, M Shenbagaraj, ... 2025 IEEE International Conference for Women in Innovation, Technology … , 2025 2025
An IoT and Blockchain Framework for Secure Agricultural Food Supply Chains R Kesavan, R Palanikumar 2025 6th International Conference on Smart Electronics and Communication … , 2025 2025
Performance Analysis of Predicting Brain Age Using Deep Learning Algorithms K Selvi Priya, C BalaSubramanian, A Ramathilagam, R Palanikumar, ... International Conference on Frontiers of Intelligent Computing: Theory and … , 2024 2024
Decentralized Social Networking Platform KJ R Palanikumar, Abinash S, Jeeva V International Journal of Scientific Research in Engineering and Management … , 2024 2024
AUTOMATIC HEAD LAMP CONTROLLER USING ARDUINO WITH ANTI COLLISION SYSTEM PR Marieswaran M, Raju SV, Maruthu U International Research Journal of Modernization in Engineering Technology … , 2024 2024
Real-time Classification of Brain States in Functional MRI Using Dynamic Connectivity Patterns and Machine Learning NHAR Gnanajeyaraman Rajaram, R.Palanikumar, Vinoth Pandian, A.Selvarani Journal of Electrical Systems 20 (5), 2095-2103 , 2024 2024
Credit Card Fraud Detection using Random Forest Algorithm GM Palanikumar R, Archana V International Conference on Recent Trends in Engineering & Technology , 2022 2022
