Murugananth Gopal Raj

@ahalia.ac.in

Dean of Research, and Professor, Department of Electrical and Electronics Engineering
Ahalia School of Engineering and Technology

Murugananth Gopal Raj


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https://researchid.co/gmurugananth

RESEARCH, TEACHING, or OTHER INTERESTS

Multidisciplinary, Electrical and Electronic Engineering, Anthropology
21

Scopus Publications

155

Scholar Citations

7

Scholar h-index

4

Scholar i10-index

Scopus Publications

  • Efficient Detection of Denial-of-Service Attacks in Wireless Sensor Networks Depending on Binarized Simplicial Convolutional Neural Networks for Enhanced Security
    R. Vidhya, S. Varunadevi, Murugananth Gopal Raj
    International Journal of Communication Systems, 2026
    DoS attacks pose significant threats to wireless sensor networks (WSNs) by disrupting regular network availability. The existing systems face limitations such as limited power, storage, bandwidth, and processing capabilities, making them particularly vulnerable to security risks. Despite these constraints, an effective intrusion detection system (IDS) is essential for detecting such attacks. As denial‐of‐service (DoS) attacks become more frequent and sophisticated, the traditional intrusion detection systems are losing their effectiveness. To overcome these complications, Efficient Detection of Denial‐of‐Service Attacks in Wireless Sensor Networks using Binarized Simplicial Convolutional Neural Networks for Enhanced Security (ED‐DoS‐WSN‐BSCNN) is proposed. The input data are collected from the WSN‐DS dataset. The gathered data are given to the preprocessing stage with the help of the adaptive two‐stage unscented Kalman filter (ATSUKF) for data cleaning, data transformation, and normalization. Then the preprocessed data are given to the classification stage by using the binarized simplicial convolutional neural network (BSCNN) for classifying DoS attacks, such as normal, blackhole, grayhole, flooded, and TDMA. Finally, the Arctic tern optimizer (ATO) algorithm is employed to enhance the BSCNN that categorizes the types of DoS attacks accurately. The performance metrics like accuracy, precision, recall, specificity, F1‐score, computational time, and RoC are taken into account. The performance of the proposed technique is compared with other existing methods. The ED‐DoS‐WSN‐BSCNN technique is implemented in Python. The proposed technique attains 4.05%, 7.52%, and 2.91% higher accuracy, 4.10%, 7.61%, and 5.14% higher precision, 7.46%, 6.92%, and 2.88% higher recall, and 1.06%, 1.75%, and 2.31% higher specificity compared with existing methods: performance analysis of deep learning for DoS attacks identification in wireless sensor network (CNN‐DoS‐WSN), detection of DoS attack in wireless sensor networks: a lightweight machine learning approach (KNN‐DoS‐WSN), and extended evaluation on machine learning approach for DoS detection in Wireless Sensor Networks (RT‐DoS‐WSN), respectively.
  • Leveraging Artificial Neural Networks for Fruit Quality Prediction: Advancements in Food Technology and Quality Control
    Arvind Kumar Srivastava, M Soumya, Torthi Ravichandra, Vidhya R, Murugananth Gopal Raj, S. P. Santhoshkumar
    2025 Global Conference in Emerging Technology Ginotech 2025, 2025
    For the food and agriculture industries to guarantee consumer happiness and cut waste, accurate fruit quality prediction is essential. Artificial Neural Networks (ANNs) are used to evaluate fruit eminence based on characteristics such as color, consistency, volume, and chemical content is investigated in this paper. Current models do a good job of classifying fresh fruits, but they are not very good at spotting rotten ones, which is crucial for reducing waste and preserving quality control. This study fills this gap by compiling a dataset of both fresh and rotting fruits in order to establish a comprehensive strategy. To distinguish between them, the ANN model is trained on a variety of photos. Additionally, fruit maturity is evaluated using color changes and OpenCV, a popular computer vision toolkit. Fruit quality assessment and classification are improved by this integrated method. The suggested approach helps with fruit sorting and guarantees that buyers receive high-quality product, which benefits sectors like retail and agriculture. The ultimate objective of this project is to increase sustainability and efficiency in the food supply chain by automating quality monitoring throughout the application of state-of-the-art ML algorithms.
  • Application of Deep Convolutional Neural Networks (DCNNs) for Automated Classification of E-Waste Components: Focusing on Circuit Boards, Batteries, and Cables
    Frederick Ruby Helen, Sivaram Rajeyyagari, Murugananth Gopal Raj, Shamim Ahmad khan, Varunadevi S, I Infant raj
    2nd IEEE International Conference on Innovations in High Speed Communication and Signal Processing Ihcsp 2024, 2024
    The proliferation of electronic waste (e-waste) has become a pressing environmental concern, necessitating efficient methods for its classification and management. Though there are traditional methods which are used when sorting and recyling e-waste, they are time-consuming, costly and most of the time, are not accurate and hence, a lot of resources are wasted in the process. This research aims at extending the use of Deep Convolutional Neural Networks (DCNNs) in the classification of critical e-waste components namely circuit boards, batteries, and cables. The proposed method fully utilizes the capacity of extracting features of DCNNs in order to accurately detect and sort these components by means of the receiving visual information. For training and testing the DCNN model a dataset was created and preprocessed and the target images included circuit boards of different orientations and sizes, batteries and cables. The architecture of a network was created considering aspect of depth and computational complexity guarantying high accuracy and feasible time for great data set processing. In the evaluation process of the model, a comparison was made with various standard performance measures, with checklists such as accuracy, precision and recall and F1-score to rate the prowess of the proposed model in taking part in the classifying process of e-waste components. From the analysis, the proposed DCNN model reached classification accuracy over 95.9% on all the categories suggesting the model can be used as a tool to sort e-waste automatically. The paper also considers the issues of implementing such technology in the current recycling systems and the overall advantages, which will be the increase of the sorting efficiency, decreased labor expenses, as well as elevated recovery rates of materials demanded in the market.
  • Digital Investigation Forensic Model with P2P Timestamp Blockchain for Monitoring and Analysis
    Et al. Layth Almahadeen
    Journal of Electrical Systems, 2024
    Forensic analysis of Blockchain data is a new field in police work. It's now one of the largest problems facing law enforcement. The paper discussed the worldwide need for digital forensics in law enforcement and Blockchain forensics to counteract crimes committed using Blockchain technology. It's been said that we've entered a new age of technology that's heavily dependent on the principles of Blockchain. The research produced a set of guidelines for Digital Investigators. on addition, a theoretical framework grounded on the concept of regular activity has been developed, and a legislative framework has been proposed to ensure that its illegal purpose will always be punished severely.
  • AI-based domestic load scheduling and power management for renewable energy exporters
    C. Pradip, Murugananth Gopal Raj, S. John Alexis, A. Manickavasagam
    Marvels of Artificial and Computational Intelligence in Life Sciences, 2023
    Residential Photovoltaic systems (RPV) are flattering and widespread among customers due to government policies. The power sources available in RPV include a grid, a PV system and a battery. The principal cost of residential photovoltaic systems is a bit high. When more power is exported, the customer who has installed it will export more power for their benefit. It can be achieved by efficiently scheduling the three sources and managing the power export. Artificial Intelligence-based systems can effectively take care of it because they provide effective decision-making solutions.
  • AI-based energy management for domestic appliances
    Murugananth Gopal Raj, S. John Alexis, A. Manickavasagam, R. Reji
    Marvels of Artificial and Computational Intelligence in Life Sciences, 2023
    Energy conservation is the need of the hour for various reasons, including the depletion of fossil fuels. The domestic sector is the major consumer of generated electricity across the globe. Artificial Intelligence is a powerful decision-making tool. Building AI-based techniques will be effective in conserving energy for domestic appliances. The general framework of AI-based lighting, room comfort, refrigerator and other load systems have been addressed in this chapter. The AI-based systems can effectively manage the operation of these loads, thereby reducing energy consumption
  • HARNESSING PSO AND GA FOR CONGESTION CONTROL IN HIGH-SPEED WIRELESS SENSOR NETWORKS
    Vidhya Rathinasamy, Poonguzhali Krishnan, Geetha Ponnusamy, Murugananth Raj
    Comptes Rendus De L Academie Bulgare Des Sciences, 2023
    Sensor and sink nodes create wireless sensor networks. Traffic congestion caused by WSN data transfer causes bigger packet losses, low throughput and excessive energy consumption. This work proposes a hybrid congestion management approach using genetic algorithm and particle swarm optimization. The new approach is simulated and compared to established methods. The suggested system dramatically improved performance metrics. The suggested system of interest increased to 94% detection efficiency, 91% network lifespan, 106 J energy usage, and 22 packet loss rate. The hybrid approach avoided wireless sensor network congestion and managed traffic.
  • Development of Energy Management System for Micro Grid Operation
    S. Jayaprakash, B. Gopi, Murugananth Gopal Raj, S. Sujith, S. Deepa, S. Swapna
    Computer Systems Science and Engineering, 2023
    The introduction of several small and large-scale industries, malls, shopping complexes, and domestic applications has significantly increased energy consumption. The aim of the work is to simulate a technically viable and economically optimum hybrid power system for residential buildings. The proposed micro-grid model includes four power generators: solar power, wind power, Electricity Board (EB) source, and a Diesel Generator (DG) set, with solar and wind power performing as major sources and the EB supply and DG set serving as backup sources. The core issue in direct current to alternate current conversion is harmonics distortion, a five-stage multilevel inverter is employed with the assistance of an intelligent control system is simulated and the optimum system configuration is estimated to reduce harmonics and improve the power quality. The monthly demand for residential buildings is 13–15 Megawatts. So, almost 433 Kilo-Watts (KW) of electricity is required every day, and if it is used for 8 h per day, 50–60 KW of electricity is needed per hour. The overall micro-grid model’s operation and performance are established using MATLAB/SIMULINK software, and simulation results are provided. The simulation results show that the developed system is both cost-effective and environment friendly resulting in yearly cost reductions.
  • Improvement of power quality in grid system based on zeta converter integrated with PV supply
    B. Meenakshi, Murugananth Gopal Raj, C. Pradip, N. Saju
    Aip Conference Proceedings, 2022
    Renewable power grid integration is an option for the supply of constant electricity. The semiconductor technology-based advancement is improving loads of the power electronics penetration. This paper presents a new definition of optimum use of a unified conditioner for power efficiency. The show UPQC inverter is tested for simultaneous sag and swell compensation using three-leg inverters associated with the power transmission lines. The ZETA converter is proposed to enhance the dc-link capacitor voltage generated from the PV module’s renewable energy system. The converter is maintaining constant power through the MPPT based PI controller. The control of the shunt and series compensators is accomplished. The results are improved compared to the conventional control systems. The PV energy is fed to the converter, which powering the inverter. The power inverter injects power in the power system lines in the form of shunt and series compensators. The results are obtained using the Simulink environment.
  • Residential Feeder Energy Audit Analysis and Recommendation with Aid of Software
    K. Anitha, Shailesh, L. Ramesh, Murugananth Gopal Raj
    Lecture Notes in Electrical Engineering, 2022
  • Wind Energy Fed SEPIC Converter with PID Controller for High Performance
    N Saju, T Porselvi, Murugananth Gopal Raj, C Pradip, S. Kavitha
    6th International Conference on I Smac Iot in Social Mobile Analytics and Cloud I Smac 2022 Proceedings, 2022
  • Wind Energy Generation Based for Grid Connected System Using Zeta Converter and Terminal Sliding Mode Control
    C Pradip, N Saju, S V Tresa Sangeetha, Murugananth Gopal Raj
    Journal of Physics Conference Series, 2021
  • Random Forest-Based Method for Micro Grid System in Energy Consumption Prediction
    Murugananth Gopal Raj, C Pradip, N Saju, S V Tresa Sangeetha
    Journal of Physics Conference Series, 2021
  • Analysis of artificial intelligence of things
    R. Revathy, Murugananth Gopal Raj, M. Selvi, J. K. Periasamy
    International Journal of Electrical Engineering and Technology, 2020
  • Quality analysis of rice grains using ANN and SVM
    Journal of Critical Reviews, 2020
  • Particle swarm optimization algorithm controlled chopper driven PMDC motor
    Murugananth Gopal Raj
    Journal of Advanced Research in Dynamical and Control Systems, 2020
  • Antlion optimization algorithm controlled chopper driven PMDC motor
    Murugananth Gopal Raj
    Journal of Advanced Research in Dynamical and Control Systems, 2020
  • Experimental validation of fuzzy-tuned AWPI controller-based chopper driven PMDC motor
    G. Murugananth, K. Samidurai, S. Muthukrishnan, S. Vijayan
    Journal of Testing and Evaluation, 2015
  • Development of fuzzy controlled chopper drive for permanent magnet DC motor
    Gopal Raj Murugananth, Subramanian Vijayan
    JVC Journal of Vibration and Control, 2015
  • A novel accelerated fuzzy PI controller based chopper driven pmdc motor
    International Journal of Applied Engineering Research, 2015
  • Analysis of various anti-windup schemes used to control PMDC motors employed in orthopedic surgical simulators
    Life Science Journal, 2013

RECENT SCHOLAR PUBLICATIONS

  • Leveraging ClinicalBERT and EHR Data for Early Detection of Pregnancy Related Complications
    MGR Varunadevi S, Sivaganesan D
    International Conference on Edge AI, Intelligent Alanytics ans Smart … , 2026
    2026
  • Closed Loop Control for a Switched-Capacitor Configured Non-Isolated High Step-Up DC Converter
    P Endla, MN Kantha, M Ravindra, MG Rai, R Thumma, S Sivakami
    IEEE 2nd International Conference on Information Technology, Electronics and … , 2026
    2026
  • A Predictive LSTM Framework for Proactive Adaptive Traffic Signal Control
    PR Murugananth Gopal Raj, Sangeetha P S, Prreja V, Sunitha K G
    International Journal of Computer Applications 187 (74), 22-31 , 2026
    2026
  • Efficient Detection of Denial-of-Service Attacks in Wireless Sensor Networks Depending on Binarized Simplicial Convolutional Neural Networks for Enhanced Security
    MGR Vidhya Rathinasamy, Varunadevi S
    International Journal of Communication Systems 39 (1) , 2025
    2025
  • Bio-Inspired Approach for Estimation of Parkinson’s Disease Using Augmented Feature Selection Model
    V G, S., Selvakumarasamy , K. ., Sekar , P. ., Bharathi , G., Elamaran , V ...
    International Journal of Basic and Applied Sciences 14 (5), 535-548 , 2025
    2025
  • AI-Driven Predictive Maintenance in Smart Manufacturing Using Cyber-Physical Systems and Industrial IoT
    RS S. Meenakshi , Aaquib Hussain Ganai ,T P Saravanan ,A Shaji George ...
    IEEE International Conference on Communication and Smart Devices (ICCoSD … , 2025
    2025
    Citations: 2
  • Leveraging Artificial Neural Networks for Fruit Quality Prediction: Advancements in Advancements in Food Technology and Quality Control
    AK Srivastava, S M, T Ravichandra, V R, MG Raj, S S P
    2025 Global Conference in Emerging Technology (GINOTECH) 1 (1), 66 , 2025
    2025
    Citations: 1
  • Engineering Entrepreneurship and Intellectual Property Rights
    Varunadevi Murugananth, Murugananth Gopal Raj, Pradip C
    ISBN 978-93-6048-691-4 1, 345 , 2025
    2025
  • Application of Deep Convolution Networks (DCCNs) for Automated Classification of E-Waste Components: Focusing on Circuit Boards, Batteries and Cables
    Fredrick Ruby Helen, Sivaram Rajeyyagari, Muruganth Gopal Raj, Shanhim Ahmad ...
    2nd IEEE International Conference on Innovations in High Speed Communication … , 2024
    2024
  • Algorithmic Thinking With Python
    Reji R, Murugananth Gopal Raj, Remya R
    2024
  • The Effectiveness of Change Management Strategies in Enhancing Organizational Resilienc
    BTK Vani Sarada, Saurabh Verma, Ganesh Mergu, Renu Girotra, Kumari Shilpi ...
    Library Progress International 44 (3), 22690-22697 , 2024
    2024
  • Digital Investigation Forensic Model with P2P Timestamp Blockchain for Monitoring and Analysis
    SKY Layth Almahadeen, Renzon Daniel Cosme Pecho, Murugananth Gopal Raj ...
    Journal of Electrical Systems 20 (1), 09-17 , 2024
    2024
    Citations: 5
  • Harnessing PSO and GA for Congestion Control in High-speed Wireless Sensor Networks
    V Rathinasamy, P Krishnan, G Ponnusamy, M Raj
    Proceedings of the Bulgarian Academy of Sciences 76 (12), 1885–1892 , 2023
    2023
    Citations: 2
  • AI-Based Domestic Load Scheduling and Power Management for Renewable Energy Exporters
    C Pradip*, Murugananth Gopal Raj, S John Alexis, A Manickavasagam
    Marvels of Artificial and Computational Intelligence in Life Sciences, 104-120 , 2023
    2023
  • AI-Based Energy Management for Domestic Appliances
    Murugananth Gopal Raj*, S. John Alexis, A Manickavasagam, R Reji
    Marvels of Artificial and Computational Intelligence in Life Sciences, 88-103 , 2023
    2023
  • MATHEMATICS Through PYTHON
    MG Raj
    2023
  • Wind Energy Fed SEPIC Converter with PID Controller for High Performance
    N Saju, T Porselvi, MG Raj, C Pradip, S Kavitha
    2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile … , 2022
    2022
    Citations: 3
  • Development of Energy Management System for Micro Grid Operation
    SS S. Jayaprakash, B. Gopi, Murugananth Gopal Raj, S. Sujith, S. Deepa
    Computer Systems Science and Engineering 45 (3), 2537-2551 , 2022
    2022
    Citations: 12
  • Writing an Effective Research Paper – Means and Methods
    MG Raj
    2022
  • Improvement of power quality in grid system based on zeta converter integrated with PV supply
    B Meenakshi, MG Raj, C Pradip, N Saju
    AIP Conference Proceedings 2519 (1), 050009 , 2022
    2022

MOST CITED SCHOLAR PUBLICATIONS

  • A manual on environmental management audits to educational institutions and industrial sectors
    BM Gnanamangai, G Murugananth, S Rajalakshmi
    Laser Park Publishing House, Coimbatore, Tamil Nadu, India , 2021
    2021
    Citations: 26
  • QUALITY ANALYSIS OF RICE GRAINS USING ANN AND SVM
    DIVYA MOHAN, MURUGANANTH GOPAL RAJ
    Journal of Critical Reviews 7 (1), 2020 , 2019
    2019
    Citations: 22
  • Development of Energy Management System for Micro Grid Operation
    SS S. Jayaprakash, B. Gopi, Murugananth Gopal Raj, S. Sujith, S. Deepa
    Computer Systems Science and Engineering 45 (3), 2537-2551 , 2022
    2022
    Citations: 12
  • ANALYSIS OF ARTIFICIAL INTELLIGENCE OF THINGS
    JKP R Revathy, Murugananth Gopal Raj, M Selvi
    International Journal of Electrical Engineering and Technology 11 (4), 275 - 280 , 2020
    2020
    Citations: 11
  • Modeling and Simulation Five Level Inverter based UPFC System
    S Muthukrishnan, A Nirmalkumar, G Murugananth
    International Journal of Computer Applications 12 (11), 11-15 , 2011
    2011
    Citations: 9
  • Random Forest-Based Method for Micro Grid System in Energy Consumption Prediction
    Murugananth Gopal Raj, C Pradip, N Saju, S V Tresa Sangeetha
    Journal of Physics: Conference Series 1964 (052002), 1-5 , 2021
    2021
    Citations: 8
  • Energy Audit Procedures and Energy Savings Opportunities in Educational Institutions and Industrial Sectors
    TP Mythili Gnanamangai B, Rajalakshmi S, Ashutosh Kumar Srivastava ...
    International Journal of Advanced Research 10 (5), 592-601 , 2022
    2022
    Citations: 7
  • Analysis of closed loop chopper controlled drive for PMDC motors using PID controller
    G Murugananth, S Vijayan, S Muthukrishnan
    IOSR J. Electric. Electron. Eng. 2 (3), 32-34 , 2012
    2012
    Citations: 7
  • Digital Investigation Forensic Model with P2P Timestamp Blockchain for Monitoring and Analysis
    SKY Layth Almahadeen, Renzon Daniel Cosme Pecho, Murugananth Gopal Raj ...
    Journal of Electrical Systems 20 (1), 09-17 , 2024
    2024
    Citations: 5
  • Genetic Algorithm Based Speed Control of PMDC Motor Using Low Cost PIC 16F877A Microcontroller
    Murugananth Gopal Raj, Vijayakumar T, Muthukrishnan S
    Circuits & Systems 7, 1334 - 1340 , 2016
    2016
    Citations: 5
  • Experimental Validation of Fuzzy-Tuned AWPI Controller-Based Chopper Driven PMDC Motor
    G Murugananth
    Journal of Testing and Evaluation 43 (6), 1-12 , 2014
    2014
    Citations: 5
  • Analysis of various anti-windup schemes used to control PMDC motors employed in orthopedic surgical simulators
    G Murugananth, S Vijayan, S Muthukrishnan
    Life Science Journal 10 (1), 226-230 , 2013
    2013
    Citations: 5
  • Development of Closed Loop Chopper Controlled Drive for PMDC Motors used in Orthopaedic Surgical Simulators
    G Murugananth
    International Journal of Computer Science and Technology , 2012
    2012
    Citations: 5
  • BELBIC Tuned PI Controller Based Chopper Driven PMDC Motor
    SK Muthukrishnan Subramaniam, Murugananth Gopalraj, Saravana Sundaram Sakthivelu
    Circuits and Systems 7 (10.4236/cs.2016.79198.), 2273-2285 , 2016
    2016
    Citations: 4
  • Development of fuzzy controlled chopper drive for permanent magnetic DC motor
    G Murugananth
    Journal of Vibration and Control, 1077546313490184 , 2013
    2013
    Citations: 4
  • Wind Energy Fed SEPIC Converter with PID Controller for High Performance
    N Saju, T Porselvi, MG Raj, C Pradip, S Kavitha
    2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile … , 2022
    2022
    Citations: 3
  • Wind Energy Fed SEPIC Converter with PID Controller for High Performance
    N Saju, T Porselvi, MG Raj, C Pradip, S Kavitha
    2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile … , 2022
    2022
    Citations: 3
  • Performance Evaluation of PMDC Motor Using Anti-Windup PI Controller
    G Murugananth, S Vijayan
    Eur. J. Sci. Res. 85 (2), 218-224 , 2012
    2012
    Citations: 3
  • AI-Driven Predictive Maintenance in Smart Manufacturing Using Cyber-Physical Systems and Industrial IoT
    RS S. Meenakshi , Aaquib Hussain Ganai ,T P Saravanan ,A Shaji George ...
    IEEE International Conference on Communication and Smart Devices (ICCoSD … , 2025
    2025
    Citations: 2
  • Harnessing PSO and GA for Congestion Control in High-speed Wireless Sensor Networks
    V Rathinasamy, P Krishnan, G Ponnusamy, M Raj
    Proceedings of the Bulgarian Academy of Sciences 76 (12), 1885–1892 , 2023
    2023
    Citations: 2