Edwin Singh C

@veltech.edu.in

Assistant Professor/ Computer Science & Engineering
Vel Tech University

Edwin Singh C


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https://researchid.co/cedwinsingh

RESEARCH INTERESTS

Wireless Networks, MANET, Machine Learning
22

Scopus Publications

120

Scholar Citations

5

Scholar h-index

4

Scholar i10-index

Scopus Publications

  • Leakage current mitigation and efficiency enhancement in transformerless 3-level NPC PV inverters
    Revathi Dhanapalan, Sivasankari Balan, Jayapriya Mangalaraj, Edwin Singh Chinna Thurai
    Bulletin of Electrical Engineering and Informatics, 2026
    In this research explores the design and performance of a transformerless (TL) three-level neutral point clamped (NPC) inverter for grid-connected photovoltaic (PV) systems. In the push toward more compact, cost-effective, and efficient renewable energy systems, TL inverter topologies have emerged as a strong alternative to conventional systems that use line-frequency transformers. The proposed topology includes two separate PV sources interfaced through dedicated boost converters, which then feed into a common NPC inverter, enhancing flexibility and maximum power point tracking (MPPT) performance. Comprehensive simulations were performed using MATLAB/Simulink to evaluate grid compatibility, total harmonic distortion (THD), and transient behavior under fluctuating irradiance levels. Results validate the efficacy of the system in maintaining grid compliance, lowering leakage current, and achieving high-quality power output. Compared to traditional two-level inverters or transformer-based alternatives, the proposed system demonstrates a clear performance advantage in both efficiency and reliability.
  • Enhancing Safety in Railway Stations Using Unsupervised Machine Learning
    C. Edwin Singh, Udayakumar Allimuthu, Saravanan Matheswaran, Pothuri Chaitanya
    Lecture Notes in Networks and Systems, 2026
  • Design and Evaluation of a Trace-Driven Cache Simulator Supporting Set-Associative and V-Way Cache Architectures
    Saravanan Matheswaran, Posa Venkata Durga Vamsi, Myndhala Dhanush Chowdary, Udayakumar Allimuthu, C. Edwin Singh
    Proceedings of 8th International Conference on Intelligent Sustainable Systems Iciss 2026, 2026
    Modern processors increasingly suffer from cache due to conflict misses arising from the rigid placement constraints imposed. By conventional set-associative cache architectures. Although Advanced designs such as the V-Way cache improve place ment flexibility through decoupled tag-data storage and in increased effective associativity, practical tools for studying their Alternative behaviors are considerably limited in their application. This paper presents a Light weight, open-source, trace-driven cache simulator supporting both classical setassociative caches as well as the V-Way cache architecture. Tracedriven simulation is utilized to allow for deterministic, reproducible analysis of cache placement and replacement behavior without full-system complexity or cycle-accurate modeling. Unlike traditional set-local LRU Implement replacement; the V-Way cache uses reuse-based global victim selection with configurable Tag Duplication Ratio (TDR) to by reducing conflict misses and replacement pressures. The simulator offers detailed performance data, such as miss rates, WriteBacks, victim numbers, and victim distance analysis, enabling f refined architectural assessment. Experimental evaluation with “”. The traces of memory access of V-Way show There is a significant reduction in conflict misses and dirty eviction due to caching. compared with setassociative architectures, with further enhancements increases as TDR increases. The proposed simulator is a research-ready platform for cache architecture exploration and educational use. The results show that increased placement <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{f}$</tex> lexibility is beneficial to replacement efficiency as well as reducing conflict. misses. These observations validate the applicability of trace-driven simulation. process simulation for evaluating placement-flexible cache architectures.
  • Strip Dilated CNN for High-Accuracy Water Quality Monitoring in Smart Aquaculture
    Prathusha P, Vallimayil S, Muthuselvi R, Edwin Singh C, Ahilan A
    Conference Proceedngs Wccst 2026 World Conference on Computational Science and Technology, 2026
    Aquaculture is a vital financial and food resource in many nations. However, it is labor-intensive and costly, requiring expensive materials and the expertise of aquaculture specialists. Ensuring high water quality is crucial for the expansion of aquaculture. Therefore, in this paper a novel method has been proposed for effective assessment of water quality in aquafarming. A diverse array of sensors collects continuous data on constraints such as pH, temperature, DO, and salinity within fish tanks. Principal Component Analysis (PCA) is applied to preprocess the sensor data, enhancing its quality, and reducing noise. Subsequently, a Strip CNN model is employed to classify water quality into 3 categories like excellent, fair, or poor quality, enabling timely alerts via mobile notifications to prevent potential harm to aquatic organisms. Assessed using a number of criteria, including recall, f1-score, specificity, precision, and accuracy. When comparing the proposed approach to the current the accuracy gains were 6.35%, 3.36%, and 5.27% correspondingly.
  • Cloud-Driven Face Recognition: The Future of Smart Surveillance
    C Edwin Singh, R Harsh
    Proceedings of 6th International Conference on Intelligent Communication Technologies and Virtual Mobile Networks Icicv 2025, 2025
    This paper proposes a cloud-based facial recognition platform aimed at satisfying the increasing requirement for intelligent surveillance in cities. The main purpose is to support real-time and scalable identity confirmation through live CCTV streams. Lightweight AI models like Ultralight and YOLO Face are used for low-latency face detection, while classification algorithms such as K-Nearest Neighbors (KNN) or Convolutional Neural Networks (CNN) are used for accurate identification of persons. The approach utilizes cloud deployment and multithreading to execute video frames in parallel, which drastically minimizes latency and enhances responsiveness. The major findings prove the system’s capability to manage real-time monitoring in multiple locations with high computational effectiveness. Through the use of cloud infrastructure, the solution bypasses local hardware constraints and provides a flexible, scalable, and robust platform for the purpose of improving public safety and automated city surveillance.
  • Impact of Pollutants in Surface Water Ecosystem using Hybrid Stochastic Geometry
    Udayakumar Allimuthu, C. Edwin Singh, Saravanan Matheswaran
    Wseas Transactions on Environment and Development, 2025
    The structural and ecological functions and the physical environment factor for the surroundings are used to compare the interrelated components to manage the boundaries and the terrestrial aspect of the aquatic systems. The problem of freshwater contamination can be evaluated to produce the marine ecosystem, and the marine ecosystem can be elaborated. By changing the chemical and biological characteristics, the water purity and the components of the water can be evaluated. The materials used in the research are MnWO4 / g-C3N4, BiVO4 / g-C3N4, ZnWO4 / g-C3N4, and CuWO4 / g-C3N4 used to obtain the 4-chlorophenol (4-CP), and Rhodamine B (RhB) by using the Photocatalytic Mechanism, the method of Hybrid Stochastic geometry. It consists of an Enhanced Reaction and Diffusion mathematical statement that can be proposed for dissolving oxygen using the Combined Phase Space Method equations. This study focused on modeling a time series on a suspension matter using the Bayesian Structural Time Series technique (BSTS). The statistical results were based on simulation procedures that employed the Kalman filter and the Monte Carlo Markov Chain (MCMC). The nutrients that tend to the 0 contractions in the study produce the eutrophication of the incorporating that can be managed in the population, and the recycling of the Photocatalytic chemicals was evaluated. Maintaining the standard model for the pollution on the surface of the water and modeling the ecosystem can be done to elaborate the surface of the water mode.
  • Workplace Stress Detection and Mental Health Prediction Using Machine Learning
    Saravanan Matheswaran, Kalpana M.S, Udayakumar Allimuthu, C. Edwin Singh
    Proceedings of the 2025 11th International Conference on Communication and Signal Processing Iccsp 2025, 2025
  • Real-Time Object Recognition and Distance Sensing using Machine Learning-Enabled Smart Assistive System to Empower Visually Challenged People
    Saravanan Matheswaran, Udayakumar Allimuthu, C.Edwin Singh, Aravind R
    Proceedings of 2025 International Conference on Signal Processing Computation Electronics Power and Telecommunication Iconscept 2025, 2025
    Visually challenged people often have trouble seeing and understanding the real world. What are the nearest objects available in and around them? to locate is very difficult. The goal of the object detection system is to give people who are blind or have low vision a way to get help that is portable, cheap, and easy to use. The system uses a camera to look for things in real time and then sends that information to the user through headphones on a smartphone. For the benefit of visually challenged people, an auditory device such as speakers or headphones would offer information about items. The suggested approach aids in the identification and avoidance of items both indoors and outdoors, impacting the day-to-day activities and professional performance of those with vision impairments. People with vision impairments would find it highly useful to have information about items in their immediate surroundings in their everyday lives.
  • Energy-Efficient Routing with LSTM-Attention DQN for Anomaly Detection in Networks
    Marri Umarani, Chaithanya Kumar Viralam Ramamurthy, C. Edwin Singh, Shermin Shamsudheen, G. Vallathan
    2025 International Conference on Emerging Technologies in Engineering Applications Icetea 2025 Proceedings, 2025
    Energy-efficient routing is significant to extend the lifespan of IoT networks, which are typically constrained by limited energy resources. Anomaly detection in communication networks is essential for identifying security threats such as DoS, R2L, Probe, and U2R attacks. This paper proposes an Energy Efficient Routing with LSTM-Attention Mechanism-based DQN for efficient and accurate anomaly detection. By integrating Long Short-Term Memory (LSTM) with an Attention Mechanism and Deep Q-Networks (DQN), the system improves detection performance while ensuring energy efficiency. The system is evaluated against traditional approaches, including AK-NN, DPC-DBN, Decision Trees (DT), and RNN-LSTM, using performance metrics such as precision, recall, F-measure, and accuracy. The results show significant improvements: precision (1.08), recall (0.44), F-measure (0.83), and accuracy (0.52) over conventional models. These findings highlight the proposed system's ability to detect various attacks effectively, while optimizing energy consumption. Its significance lies in providing a robust, scalable, and real-time solution for anomaly detection, particularly in resource-constrained environments, making it a valuable tool for modern network security.
  • A Deep Learning Framework for Radar Signal Analysis with Spatio-Temporal Fusion
    L.Uma Maheshwari, Senthilkumar Meyyappan, M. Suguna, C. Edwin Singh, G. Vallathan, Kalyan S. Kasturi
    Proceedings of the 4th International Conference on Innovative Mechanisms for Industry Applications Icimia 2025, 2025
    In modern wireless and sensing systems, effective communication and radar signal sensing are critical. Traditional methods, relying on engineered features or standalone neural networks, struggle with multi-modal data and low signal-to-noise ratios (SNR). They fail to capture spatial and temporal relationships and lack inter-modal connections. To overcome these issues, a novel CNN-LSTM framework has been proposed. It uses convolutional neural networks (CNN) for spatial feature extraction and long short- term memory networks (LSTM) to model temporal dependencies, refining features across modalities. By integrating IQ data, spectrograms, and cyclic spectrum representations, the model ensures robust signal sensing, even in challenging conditions. Experiments show the method achieves over 99.6% sensing accuracy in Gaussian and Rician channels and outperforms traditional approaches in low SNR environments, down to -5 dB. These results highlight the framework's potential to enhance communication and radar signal sensing.
  • Deep Learning Assisted Blockchain for Secure Routing in Wireless Sensor Networks
    Balamurali Pydi, A. Sarfaraz Ahmed, C. Edwin Singh, R. Raja Kumar, S. Sweetlin Susilabai, Jafar Ahmad Abed Alzubi
    Lecture Notes in Networks and Systems, 2025
  • AI-BASED ENVIRONMENTAL MONITORING USING WIRELESS SENSOR NETWORK
    Journal of Environmental Protection and Ecology, 2025
  • Deep Learning-Enabled Fetal Health Classification Through Sensor-Fused IoT Environment
    Prince Samuel Selvan, Santosh Reddy Addula, C. Edwin Singh, Muthukumaran Narayanaperumal, Nikhil Kumar Marriwala, Ahilan Appathurai
    Lecture Notes in Networks and Systems, 2025
  • On Road Vehicle Breakdown Assistance by Using Machine Learning
    C.Edwin Singh, Udayakumar Allimuthu, Saravanan Matheswaran, P.Siva Naga Alekhya, SK Reshma Farzana, B. Pavithra
    Proceedings of the 2025 11th International Conference on Communication and Signal Processing Iccsp 2025, 2025
  • Trust aware fuzzy clustering based reliable routing in Manet
    C Edwin Singh, S Sharon Priya, B Muthu Kumar, K Saravanan, A Neelima, B Gireesha
    Measurement Sensors, 2024
  • Hybrid Visual Verification
    S.Nikkath Bushra, A. Syed Ismail, P. Sasigresa, Edwin Singh C
    Proceedings of the 14th International Conference on Cloud Computing Data Science and Engineering Confluence 2024, 2024
  • Locating Patient Health Data Theft Using Gradient Boosting with Hybrid Microwave Transmission-Based Wearable Device
    Udayakumar Allimuthu, Edwin Singh C., V. Sivaraman, Konagalla Ratnavathi, Y. Pavan Kumar Reddy, O. Vamsi Krishna, Addanki Venkata Surekha
    2024 International Conference on Signal Processing Computation Electronics Power and Telecommunication Iconscept 2024 Proceedings, 2024
  • Fuzzy based intrusion detection system in MANET
    C. Edwin Singh, S. Maria Celestin Vigila
    Measurement Sensors, 2023
  • An Investigation of Machine Learning-Based IDS for Green Smart Transportation in MANET
    C. Edwin Singh, J. Amar Pratap Singh
    Eai Springer Innovations in Communication and Computing, 2023
  • WOA-DNN for Intelligent Intrusion Detection and Classification in MANET Services
    C. Edwin Singh, S. Maria Celestin Vigila
    Intelligent Automation and Soft Computing, 2023
  • An investigation of machine learning-based intrusion detection system in mobile ad hoc network
    C. Edwin Singh, S. Maria Celestin Vigila
    International Journal of Intelligent Engineering Informatics, 2023
  • Enhancing Lifespan and Energy Efficiency in Mobile Smart Dust Networks
    Rajesh Dennison, Ramesh Dennison, Giji Kiruba Dasebenezer, Edwin Singh Chinnathurai
    Ingenierie Des Systemes D Information, 2023

RECENT SCHOLAR PUBLICATIONS

  • Design and Evaluation of a Trace-Driven Cache Simulator Supporting Set-Associative and V-Way Cache Architectures
    S Matheswaran, PVD Vamsi, MD Chowdary, U Allimuthu, CE Singh
    2026 8th International Conference on Intelligent Sustainable Systems (ICISS … , 2026
    2026
  • Leakage current mitigation and efficiency enhancement in transformerless 3-level NPC PV inverters
    ESCT Revathi Dhanapalan, Sivasankari Balan, Jayapriya Mangalaraj
    Bulletin of Electrical Engineering and Informatics 15 (2), 1548 - 1557 , 2026
    2026
  • Real-Time Object Recognition and Distance Sensing using Machine Learning-Enabled Smart Assistive System to Empower Visually Challenged People
    S Matheswaran, U Allimuthu, CE Singh
    2025 International Conference on Signal Processing, Computation, Electronics … , 2025
    2025
  • A Deep Learning Framework for Radar Signal Analysis with Spatio-Temporal Fusion
    LU Maheshwari, S Meyyappan, M Suguna, CE Singh, G Vallathan, ...
    2025 4th International Conference on Innovative Mechanisms for Industry … , 2025
    2025
  • Deep Learning-Enabled Fetal Health Classification Through Sensor-Fused IoT
    PS Selvan, SR Addula, CE Singh, M Narayanaperumal, NK Marriwala, ...
    Mobile Radio Communications and 5G Networks: Proceedings of Fifth MRCN 2024, 157 , 2025
    2025
    Citations: 2
  • Deep Learning Assisted Blockchain for Secure Routing in Wireless Sensor
    B Pydi, AS Ahmed, CE Singh, RR Kumar, SS Susilabai, JAA Alzubi
    Mobile Radio Communications and 5G Networks: Proceedings of Fifth MRCN 2024, 383 , 2025
    2025
  • Enhancing Safety in Railway Stations Using Unsupervised Machine Learning
    CE Singh, U Allimuthu, S Matheswaran, P Chaitanya
    International Conference on Data Science and Applications, 217-228 , 2025
    2025
  • Cloud-Driven Face Recognition: The Future of Smart Surveillance
    CE Singh, R Harsh
    2025 6th International Conference on Intelligent Communication Technologies … , 2025
    2025
    Citations: 1
  • Energy-Efficient Routing with LSTM-Attention DQN for Anomaly Detection in Networks
    M Umarani, CKV Ramamurthy, CE Singh, S Shamsudheen, G Vallathan
    2025 International Conference on Emerging Technologies in Engineering … , 2025
    2025
  • On Road Vehicle Breakdown Assistance by Using Machine Learning
    CE Singh, U Allimuthu, S Matheswaran, PSN Alekhya, SKR Farzana, ...
    2025 11th International Conference on Communication and Signal Processing … , 2025
    2025
  • Workplace Stress Detection and Mental Health Prediction Using Machine Learning
    S Matheswaran, MS Kalpana, U Allimuthu, CE Singh
    2025 11th International Conference on Communication and Signal Processing … , 2025
    2025
    Citations: 1
  • Bacteria Foraging Optimized Self Secure Routing in Vehicular Ad Hoc Network
    CE Singh, BR Reddy
    International Journal of Data Science and Artificial Intelligence 3 (03), 91-96 , 2025
    2025
    Citations: 1
  • Impact of pollutants in surface water ecosystem using hybrid stochastic geometry
    U Allimuthu, CE Singh, S Matheswaran
    WSEAS Transactions on Environment and Development 21 (10.37394), 232015.2025 , 2025
    2025
    Citations: 7
  • Deep Learning Assisted Blockchain for Secure Routing in Wireless Sensor Networks
    B Pydi, A Sarfaraz Ahmed, C Edwin Singh, R Raja Kumar, ...
    International Conference on Mobile Radio Communications & 5G Networks, 383-394 , 2024
    2024
  • Deep Learning-Enabled Fetal Health Classification Through Sensor-Fused IoT Environment
    PS Selvan, SR Addula, CE Singh, M Narayanaperumal, NK Marriwala, ...
    International Conference on Mobile Radio Communications & 5G Networks, 157-169 , 2024
    2024
    Citations: 5
  • Locating patient health data theft using gradient boosting with hybrid microwave transmission-based wearable device
    U Allimuthu, E Singh, V Sivaraman, K Ratnavathi, YPK Reddy, ...
    2024 International Conference on Signal Processing, Computation, Electronics … , 2024
    2024
    Citations: 3
  • Trust aware fuzzy clustering based reliable routing in Manet
    CE Singh, SS Priya, BM Kumar, K Saravanan, A Neelima, B Gireesha
    Measurement: Sensors 33, 101142 , 2024
    2024
    Citations: 22
  • Hybrid Visual Verification
    SN Bushra, AS Ismail, P Sasigresa, E Singh
    2024 14th International Conference on Cloud Computing, Data Science … , 2024
    2024
    Citations: 1
  • Enhancing lifespan and energy efficiency in mobile smart dust networks
    R Dennison, R Dennison, GK Dasebenezer, ES Chinnathurai
    Ingenierie des Systemes d'Information 28 (5), 1317 , 2023
    2023
    Citations: 2
  • An investigation of machine learning-based ids for green smart transportation in MANET
    CE Singh, JAP Singh
    Artificial Intelligence for Smart Healthcare, 59-74 , 2023
    2023
    Citations: 4

MOST CITED SCHOLAR PUBLICATIONS

  • Fuzzy based intrusion detection system in MANET
    CE Singh, SMC Vigila
    Measurement: Sensors 26, 100578 , 2023
    2023
    Citations: 34
  • WOA-DNN for Intelligent Intrusion Detection and Classification in MANET Services.
    C Edwin Singh, SM Celestin Vigila
    Intelligent Automation & Soft Computing 35 (2) , 2023
    2023
    Citations: 23
  • Trust aware fuzzy clustering based reliable routing in Manet
    CE Singh, SS Priya, BM Kumar, K Saravanan, A Neelima, B Gireesha
    Measurement: Sensors 33, 101142 , 2024
    2024
    Citations: 22
  • An investigation of machine learning-based intrusion detection system in mobile ad hoc network
    CE Singh, SMC Vigila
    International Journal of Intelligent Engineering Informatics 11 (1), 54-70 , 2023
    2023
    Citations: 14
  • Impact of pollutants in surface water ecosystem using hybrid stochastic geometry
    U Allimuthu, CE Singh, S Matheswaran
    WSEAS Transactions on Environment and Development 21 (10.37394), 232015.2025 , 2025
    2025
    Citations: 7
  • Deep Learning-Enabled Fetal Health Classification Through Sensor-Fused IoT Environment
    PS Selvan, SR Addula, CE Singh, M Narayanaperumal, NK Marriwala, ...
    International Conference on Mobile Radio Communications & 5G Networks, 157-169 , 2024
    2024
    Citations: 5
  • An investigation of machine learning-based ids for green smart transportation in MANET
    CE Singh, JAP Singh
    Artificial Intelligence for Smart Healthcare, 59-74 , 2023
    2023
    Citations: 4
  • Locating patient health data theft using gradient boosting with hybrid microwave transmission-based wearable device
    U Allimuthu, E Singh, V Sivaraman, K Ratnavathi, YPK Reddy, ...
    2024 International Conference on Signal Processing, Computation, Electronics … , 2024
    2024
    Citations: 3
  • Deep Learning-Enabled Fetal Health Classification Through Sensor-Fused IoT
    PS Selvan, SR Addula, CE Singh, M Narayanaperumal, NK Marriwala, ...
    Mobile Radio Communications and 5G Networks: Proceedings of Fifth MRCN 2024, 157 , 2025
    2025
    Citations: 2
  • Enhancing lifespan and energy efficiency in mobile smart dust networks
    R Dennison, R Dennison, GK Dasebenezer, ES Chinnathurai
    Ingenierie des Systemes d'Information 28 (5), 1317 , 2023
    2023
    Citations: 2
  • Cloud-Driven Face Recognition: The Future of Smart Surveillance
    CE Singh, R Harsh
    2025 6th International Conference on Intelligent Communication Technologies … , 2025
    2025
    Citations: 1
  • Workplace Stress Detection and Mental Health Prediction Using Machine Learning
    S Matheswaran, MS Kalpana, U Allimuthu, CE Singh
    2025 11th International Conference on Communication and Signal Processing … , 2025
    2025
    Citations: 1
  • Bacteria Foraging Optimized Self Secure Routing in Vehicular Ad Hoc Network
    CE Singh, BR Reddy
    International Journal of Data Science and Artificial Intelligence 3 (03), 91-96 , 2025
    2025
    Citations: 1
  • Hybrid Visual Verification
    SN Bushra, AS Ismail, P Sasigresa, E Singh
    2024 14th International Conference on Cloud Computing, Data Science … , 2024
    2024
    Citations: 1
  • Design and Evaluation of a Trace-Driven Cache Simulator Supporting Set-Associative and V-Way Cache Architectures
    S Matheswaran, PVD Vamsi, MD Chowdary, U Allimuthu, CE Singh
    2026 8th International Conference on Intelligent Sustainable Systems (ICISS … , 2026
    2026
  • Leakage current mitigation and efficiency enhancement in transformerless 3-level NPC PV inverters
    ESCT Revathi Dhanapalan, Sivasankari Balan, Jayapriya Mangalaraj
    Bulletin of Electrical Engineering and Informatics 15 (2), 1548 - 1557 , 2026
    2026
  • Real-Time Object Recognition and Distance Sensing using Machine Learning-Enabled Smart Assistive System to Empower Visually Challenged People
    S Matheswaran, U Allimuthu, CE Singh
    2025 International Conference on Signal Processing, Computation, Electronics … , 2025
    2025
  • A Deep Learning Framework for Radar Signal Analysis with Spatio-Temporal Fusion
    LU Maheshwari, S Meyyappan, M Suguna, CE Singh, G Vallathan, ...
    2025 4th International Conference on Innovative Mechanisms for Industry … , 2025
    2025
  • Deep Learning Assisted Blockchain for Secure Routing in Wireless Sensor
    B Pydi, AS Ahmed, CE Singh, RR Kumar, SS Susilabai, JAA Alzubi
    Mobile Radio Communications and 5G Networks: Proceedings of Fifth MRCN 2024, 383 , 2025
    2025
  • Enhancing Safety in Railway Stations Using Unsupervised Machine Learning
    CE Singh, U Allimuthu, S Matheswaran, P Chaitanya
    International Conference on Data Science and Applications, 217-228 , 2025
    2025