SATHEESH NARAYANASAMI

@set.jainuniversity.ac.in

Professor and Department of Computer Science and Engineering
Jain (Deemed to be University)

SATHEESH NARAYANASAMI

RESEARCH, TEACHING, or OTHER INTERESTS

Artificial Intelligence, Computer Networks and Communications, Computer Engineering
20

Scopus Publications

677

Scholar Citations

13

Scholar h-index

13

Scholar i10-index

Scopus Publications

  • FEDERATED INTELLIGENCE IN OPHTHALMOLOGY: PRIVACY-PRESERVING COLLABORATION FOR MULTICENTER AMBLYOPIA MODEL DEVELOPMENT
    Journal of Theoretical and Applied Information Technology, 2026
  • SECURING THE FUTURE OF WSNS: A HYBRID FEDERATED AND DEEP LEARNING APPROACH TO FAULT DETECTION AND THREAT MITIGATION
    DR. R. SARAVANAKUMAR, DR. B. NARMADA, DR. KEERTHI KETHINENI, VENKATA BALA ANNAPURNA P, DR. RAKSHITHA KIRAN P, SHAIK JILANI BASHA, DR. N. SATHEESH
    Journal of Theoretical and Applied Information Technology, 2026
    Intelligent computing is getting more and more close to the concept along with Wireless Sensor Networks (WSNs) operated for fault detection and system reliability assurance. However, more traditional centrally located deep learning (DL) models still have limitations in terms of scalability, suffer from high communication overhead and may have privacy issues. To overcome these problems, this work proposes a Hybrid Federated Deep Learning (HFDL) model, which merges federated learning (FL) and distributed DL models to enable secure, energy-efficient, and reliable fault detection in large-scale WSNs. This approach was evaluated through a simulated setup consisting of 500 sensors nodes along with various fault conditions (data loss, node failure, communication errors). At the edge nodes, the model comprises CNN and LSTM-based local models, and the global model is updated through a federated virtual aggregation of local updates, thereby no raw data sharing is involved. They were compared with common machine learning baselines such as Support Vector Machine (SVM), k -Nearest Neighbors (kNN), standalone DL only, and FL only. The results indicate that HFDL is going to have an average fault detection rate of 96.8, a reduction in latency by 22, and energy consumption of 18 less than the existing methods. Such outcomes are evidence that the model under consideration elevates not only the computational efficiency level but also the data privacy standards and can be implemented in the next-generation intelligent sensor instances
  • Advanced AI-driven emergency response systems for enhanced vehicle and human safety
    N. Satheesh, N. Gopisankar, S. Kumarganesh, S. Anthoniraj, S. Saravanakumar, K. Martin Sagayam, Binay Kumar Pandey, Digvijay Pandey
    Iran Journal of Computer Science, 2025
  • ADDRESSING THE CHALLENGES OF REAL-TIME OBJECT RECOGNITION AND NAVIGATION IN AUTONOMOUS SYSTEMS: A HYBRID SENSOR FUSION APPROACH
    Journal of Theoretical and Applied Information Technology, 2025
  • Achieving Provably Effective Quantum Algorithms for Extensive Machine Learning Models
    N. Satheesh, Rashmi Dixit, S. Venkataramana, S. Anthoniraj, Bala Gurivi Reddy Vemi Reddy, Jitendra Singh
    Proceedings 2024 International Conference on Computational Intelligence for Security Communication and Sustainable Development Ciscsd 2024, 2024
    Massive machine learning models are cutting edge artificial intelligence technologies, but they have significant computational costs, power requirements, and tuning time constraints. We demonstrate in this work that verifiable well-organized solutions for nonspecific (stochastic) ramp succession procedures may be possible with fault-tolerant quantum computing. We demonstrate that comparable procedures are effective for (stochastic) ramp succession, the main machine learning procedure, based on previous efficient quantum algorithms for dissipative differential equations. We yardstick pictures of large machine learning models with between 7 million and 103 million restrictions in real-world scenarios. It has been observed that in the scarce keeping fit setting, a substantial enrichment can occur during the initial learning phase following model pruning. This finding provides impetus for a sparse parameter download and re-upload strategy. It is evident from our work that most large-scale, state-of-the-art machine-learning problems may benefit from the use of fault-tolerant quantum algorithms.
  • An Automated live Streaming and Uploading Video Recording Assistance System Using Real-Time Based Object Detection, Tracking, Audio Recognition Techniques
    N. Satheesh, Vasukidevi. G, N. Raghava Rao, S. Anthoniraj, Ramakrishna Vadrevu, K.G.S. Venkatesan
    Proceedings 2024 International Conference on Computational Intelligence for Security Communication and Sustainable Development Ciscsd 2024, 2024
    The Automatic Video Recording Assistant System is a software solution that helps users to record video content with ease. It is designed to make the video recording process simpler and more efficient. The system is built with advanced features that enable users to set up recording schedules, select recording devices, and customize their settings.
  • PREDICTION OF AUTO-DETECTION FOR TRACKING OF SUB-NANO SCALE PARTICLE IN 2D AND 3D USING SVM-BASED DEEP LEARNING
    Journal of Theoretical and Applied Information Technology, 2023
  • Brain Tumor Prediction using Adaptive Connected Component based GLCM and SVM Method
    A. Srinivasa Reddy, R. Raja, N. Satheesh, R. Muruganantham
    International Journal on Recent and Innovation Trends in Computing and Communication, 2023
    A crucial stage in the diagnosis of brain disorders using magnetic resonance images is feature extraction. The feature extraction procedure is used to reduce the amount of the picture data by removing the necessary information from the segmented image. The segmentation strategy and features that are extracted have an impact on the classification algorithm's dependability. With the aid of a Support Vector Machine, texture features are retrieved in this study using a Grey Level Co-occurrence Matrix, while form features are extracted using connected areas. Images of benign tumours, malignant tumours, and a normal brain all exhibit distinctive features. The classification of MR images can benefit from this change in feature values. A SVM classifier will receive the features that were thusly obtained for training and testing and further able to classify the abnormalities in brain images.
  • Effective Scheduling of Multi-Load Automated Guided Vehicle in Spinning Mill: A Case Study
    Parkavi Krishnamoorthy, N. Satheesh, D. Sudha, Sudhakar Sengan, Meshal Alharbi, Denis A. Pustokhin, Irina V. Pustokhina, Roy Setiawan
    IEEE Access, 2023
    In the Flexible Manufacturing System (FMS), where material processing is carried out in the form of tasks from one department to another, the use of Automated Guided Vehicles (AGVs) is significant. The application of multiple-load AGVs can be understood to boost FMS throughput by multiple orders of magnitude. For the transportation of materials and items inside a warehouse or manufacturing plant, an AGV, a mobile robot, offers extraordinary industrial capabilities. The technique of allocating AGVs to tasks while taking into account the cost and time of operations is known as AGV scheduling. Most research has exclusively addressed single-objective optimization, whereas multi-objective scheduling of AGVs is a complex combinatorial process without a single solution, in contrast to single-objective scheduling. This paper presents the integrated Local Search Probability-based Memetic Water Cycle (LSPM-WC) algorithm using a spinning mill as a case study. The scheduling model’s goal is to maximize machine efficiency. The scheduling of the statistical tests demonstrated the applicability of the proposed model in lowering the makespan and fitness values. The mean AGV operating efficiency was higher than the other estimated models, and the LSPM-WC surpassed the different algorithms to produce the best result.
  • Biological Feature Selection and Classification Techniques for Intrusion Detection on BAT
    Satheesh Narayanasami, Sudhakar Sengan, Saira Khurram, Farrukh Arslan, Suresh Kumar Murugaiyan, Regin Rajan, Vijayakumar Peroumal, Anil Kumar Dubey, Sujatha Srinivasan, Dilip Kumar Sharma
    Wireless Personal Communications, 2022
  • An Enhanced Trust-Based Kalman Filter Route Optimization Technique for Wireless Sensor Networks
    Satheesh Narayanasami, Rajasekhar Butta, Rajeshkumar Govindaraj, Surendra Singh Choudhary, Dilip Kumar Sharma, Anjana Poonia, Sudhakar Sengan, Pankaj Dadheech, Neeraj Kumar Shukla, Rajesh Verma
    Wireless Personal Communications, 2022
  • Design of Automotive Accident-Avoidance System at Speed Limit Zone Using GPS
    P. M. Balasubramaniam, N. Satheesh, Rajib Guhathakurta, Shaik Khaleel Ahamed, Dilip Kumar Sharma, Rajasekar Rangasamy, Sudhakar Sengan
    Lecture Notes in Networks and Systems, 2022
  • IDS detection based on optimization based on WI-CS and GNN algorithm in SCADA network
    S. Shitharth, N. Satheesh, B. Praveen Kumar, K. Sangeetha
    Lecture Notes in Networks and Systems, 2021
  • Flow-based anomaly intrusion detection using machine learning model with software defined networking for OpenFlow network
    N. Satheesh, M.V. Rathnamma, G. Rajeshkumar, P. Vidya Sagar, Pankaj Dadheech, S.R. Dogiwal, Priya Velayutham, Sudhakar Sengan
    Microprocessors and Microsystems, 2020
  • Certain improvements to location aided packet marking and DDoS attacks in internet
    Journal of Engineering Science and Technology, 2020
  • Improvements in cluster-based routing to protect malicious node attacks on taodv routing protocol using MANET
    Applied Mathematics and Information Sciences, 2019
  • Optimizing joins in a map-reduce for data storage and retrieval performance analysis of query processing in HDFS for big data
    and Dr.Sudhakar S
    International Journal of Advanced Trends in Computer Science and Engineering, 2019
  • Secured wireless sensor network framework to support guaranteed successful data transmission
    R. J. Kavitha, N. Satheesh
    Applied Mathematics and Information Sciences, 2019
  • Evaluation performance of worm-hole attack using proposed AODV in MANET
    International Journal of Applied Engineering Research, 2016
  • Trust based ad hoc on demand distance vector routing protocol against wormhole attack
    Journal of Theoretical and Applied Information Technology, 2014

RECENT SCHOLAR PUBLICATIONS

  • FEDERATED INTELLIGENCE IN OPHTHALMOLOGY: PRIVACY-PRESERVING COLLABORATION FOR MULTICENTER AMBLYOPIA MODEL DEVELOPMENT
    J LAKSHMI C, DRN SATHEESH, DRM KUMARASAN
    Journal of Theoretical and Applied Information Technology 104 (7), 189-203 , 2026
    2026
  • SECURING THE FUTURE OF WSNS: A HYBRID FEDERATED AND DEEP LEARNING APPROACH TO FAULT DETECTION AND THREAT MITIGATION
    DRR SARAVANAKUMAR, DRB NARMADA, DRK KETHINENI, ...
    Journal of Theoretical and Applied Information Technology 103 (6), 453-465 , 2026
    2026
  • Boards’ Involvement in Strategic Human Resource Decisions–Towards an Integrative Model and Progress
    VSV Ch, KV Sridhar, NMV Rao, N Satheesh, KA Sravanthi
    Journal of Marketing & Social Research 2, 259-266 , 2025
    2025
  • ADDRESSING THE CHALLENGES OF REAL-TIME OBJECT RECOGNITION AND NAVIGATION IN AUTONOMOUS SYSTEMS: A HYBRID SENSOR FUSION APPROACH
    MV KISHORE, MSRVP REDDY, MCH DIVYA, MMM REDDY, ...
    Journal of Theoretical and Applied Information Technology 103 (9), 3969 - 3983 , 2025
    2025
    Citations: 1
  • Advanced AI-driven emergency response systems for enhanced vehicle and human safety
    N Satheesh, N Gopisankar, S Kumarganesh, S Anthoniraj, ...
    Iran Journal of Computer Science , 2025
    2025
    Citations: 26
  • AN AI-ENHANCED VEHICLE SAFETY SYSTEM WITH EMERGENCY WINDSHIELD CLEANING AND 360-DEGREE MONITORING
    DN Satheesh, MN Gopisankar, MM Latha, MS Narayanasami, ...
    IN Patent 202441047642 A , 2024
    2024
  • Achieving Provably Effective Quantum Algorithms for Extensive Machine Learning Models
    N Satheesh, R Dixit, S Venkataramana, S Anthoniraj, BGRV Reddy, ...
    2024 International Conference on Computational Intelligence for Security … , 2024
    2024
  • An Automated live Streaming and Uploading Video Recording Assistance System Using Real-Time Based Object Detection, Tracking, Audio Recognition Techniques
    N Satheesh, NR Rao, S Anthoniraj, R Vadrevu, KGS Venkatesan
    2024 International Conference on Computational Intelligence for Security … , 2024
    2024
  • A Lightweight IoT Evaluation Model for Threat Flow Prediction with SDN and IoT Integration
    R Raja, AS Reddy, R Muruganantham, N Satheesh
    International Journal of INTELLIGENT SYSTEMS AND APPLICATIONS IN ENGINEERING … , 2024
    2024
  • Navigation Detection Device with Intelligent Object Recognizer
    DN Satheesh, DS Boggavarapu, DK Kaur, D Ramanjeet
    IN Patent 415451-001 , 2024
    2024
  • A Survey on Micro-ElectroMechanical Systems for WSN Hole Using Optimized Sensor Treatment
    S N, S s, A S, TKS Pandraju, A R
    1st -International Conference on Recent Innovations in Computing, Science … , 2023
    2023
  • An Autonomous Multi-Modal System Based on Recognized Driving Behaviour for the Neural Internet of Transportation
    N Satheesh, S Saravanakumar, MA HARIKA, DK Saravanan, S Anthoniraj
    1st -International Conference on Recent Innovations in Computing, Science … , 2023
    2023
  • An ML Ensemble Method on Fake News Detection in Social Media
    MGC SEKHAR, S Saravanakumar, S Anthoniraj, N Satheesh
    1st -International Conference on Recent Innovations in Computing, Science … , 2023
    2023
  • Big Data From the Standpoint of a Machine Learning Approach
    MG NAGAMANI, ASV RAJ, S Anthoniraj, MN RAJASHEKAR, N Satheesh
    1st -International Conference on Recent Innovations in Computing, Science … , 2023
    2023
  • BIG DATA FATAL ROLE IN BUSINESS PROCESS OPTIMIZATION USING DIFFERENT ML APPROACHES.
    A S, S N, R N, S S
    1st -International Conference on Recent Innovations in Computing, Science … , 2023
    2023
  • Brain Tumor Prediction using Adaptive Connected Component based GLCM and SVM Method
    AS Reddy, R Raja, N Satheesh, R Muruganantham
    International Journal on Recent and Innovation Trends in Computing and … , 2023
    2023
    Citations: 45
  • Prediction of auto-detection for tracking of sub-nano scale particle in 2D and 3D using SVM-based deep learning
    PS Ramesh, I Sudha, N Satheesh, GG Rajulu, SA Kalaiselvan
    Journal of Theoretical and Applied Information Technology 101 (5), 1961-1971 , 2023
    2023
    Citations: 50
  • Effective scheduling of multi-load automated guided vehicle in spinning mill: A case study
    P Krishnamoorthy, N Satheesh, D Sudha, S Sengan, M Alharbi, ...
    Ieee Access 11, 9389-9402 , 2023
    2023
    Citations: 87
  • Data Communication and Computer Networks
    DBLK Dr P Santosh Kumar Patra, Mr. P. Alexander, Dr N Satheesh
    2022
  • An enhanced trust-based Kalman filter route optimization technique for wireless sensor networks
    S Narayanasami, R Butta, R Govindaraj, SS Choudhary, DK Sharma, ...
    Wireless Personal Communications 127 (2), 1311-1329 , 2022
    2022
    Citations: 28

MOST CITED SCHOLAR PUBLICATIONS

  • Flow-based anomaly intrusion detection using machine learning model with software defined networking for OpenFlow network
    N Satheesh, MV Rathnamma, G Rajeshkumar, PV Sagar, P Dadheech, ...
    Microprocessors and Microsystems 79, 103285 , 2020
    2020.0
    Citations: 102
  • Effective scheduling of multi-load automated guided vehicle in spinning mill: A case study
    P Krishnamoorthy, N Satheesh, D Sudha, S Sengan, M Alharbi, ...
    Ieee Access 11, 9389-9402 , 2023
    2023.0
    Citations: 87
  • IDS detection based on optimization based on WI-CS and GNN algorithm in SCADA network
    S Shitharth, N Satheesh, BP Kumar, K Sangeetha
    Architectural wireless networks solutions and security issues, 247-265 , 2021
    2021.0
    Citations: 55
  • Biological Feature Selection and Classification Techniques for Intrusion Detection on BAT
    S Narayanasami, S Sengan, S Khurram, F Arslan, SK Murugaiyan, ...
    Wireless Personal Communication , 2021
    2021.0
    Citations: 54
  • Routing with Cooperative Nodes using Improved Learning Approaches
    RR N. Satheesh, J. Britto Dennis, C. Ragavendra
    Intelligence Automation & Soft Computing 35 (3), 2857-2874 , 2022
    2022.0
    Citations: 53
  • Highway Adaptation-Based Car Safety Application Based on GPS and GMS Technologies.
    N Satheesh, R Raja, B Rajalingam, R Santhoshkumar, PS Kumar Patra
    Turkish Online Journal of Qualitative Inquiry 12 (4) , 2021
    2021.0
    Citations: 53
  • Prediction of auto-detection for tracking of sub-nano scale particle in 2D and 3D using SVM-based deep learning
    PS Ramesh, I Sudha, N Satheesh, GG Rajulu, SA Kalaiselvan
    Journal of Theoretical and Applied Information Technology 101 (5), 1961-1971 , 2023
    2023.0
    Citations: 50
  • Design of Automotive Accident-Avoidance System at Speed Limit Zone Using GPS
    PM Balasubramaniam, N Satheesh, R Guhathakurta, SK Ahamed, ...
    Innovations in Computer Science and Engineering 385, 271–279 , 2022
    2022.0
    Citations: 49
  • Brain Tumor Prediction using Adaptive Connected Component based GLCM and SVM Method
    AS Reddy, R Raja, N Satheesh, R Muruganantham
    International Journal on Recent and Innovation Trends in Computing and … , 2023
    2023.0
    Citations: 45
  • An enhanced trust-based Kalman filter route optimization technique for wireless sensor networks
    S Narayanasami, R Butta, R Govindaraj, SS Choudhary, DK Sharma, ...
    Wireless Personal Communications 127 (2), 1311-1329 , 2022
    2022.0
    Citations: 28
  • Advanced AI-driven emergency response systems for enhanced vehicle and human safety
    N Satheesh, N Gopisankar, S Kumarganesh, S Anthoniraj, ...
    Iran Journal of Computer Science , 2025
    2025.0
    Citations: 26
  • Certain improvements to location aided packet marking and ddos attacks in internet
    N Satheesh, D Sudha, D Suganthi, S Sudhakar, S Dhanaraj, VP Sriram, ...
    Journal of Engineering Science and Technology 15 (1), 94-107 , 2020
    2020.0
    Citations: 18
  • Optimizing Joins in a Map-Reduce for Data Storage and Retrieval Performance Analysis of Query Processing in HDFS for Big Data
    DS Sudhakar1, DN Satheesh, DS Balu, AS Reddy, DG Murugan
    International Journal of Advanced Trends in Computer Science and Engineering … , 2019
    2019.0
    Citations: 18
  • Blockchain - Facilitated IoT Built Cleverer Home with Unrestricted Validation Arrangement
    N Satheesh, GRK Rao, S Chowdhury, KB Prakash, S Sengan
    International Journal of Advanced Trends in Computer Science and Engineering … , 2020
    2020.0
    Citations: 9
  • Trust based ad hoc on demand distance vector routing protocol against wormhole attack
    N Satheesh, K Prasadh
    Journal of Theoretical and Applied Information Technology 70 (3) , 2014
    2014.0
    Citations: 7
  • & Sengan, S.(2020). Flow-based anomaly intrusion detection using machine learning model with software defined networking for OpenFlow network
    N Satheesh, MV Rathnamma, G Rajeshkumar, PV Sagar, P Dadheech, ...
    Microprocessors and Microsystems 79, 103285 , 0
    Citations: 5
  • Analysis and Parameterized Evaluation of Impact of Wormhole Attack Using AODV Protocol in MANET
    N Satheesh, DK Prasadh
    International Journal of Advanced Research in Computer Science and Software … , 2013
    2013.0
    Citations: 4
  • Improvements in Cluster-Based Routing to Protect Malicious Node Attacks on TAODV Routing Protocol using MANET
    N Satheesh, K Prasadh
    International Journal of Applied Mathematics & Information Sciences 13 (6 … , 2019
    2019.0
    Citations: 3
  • Testing for IoT Devices and Software's and Effects of New Features on Security and Privacy by using Test Simulation.”
    N Satheesh, P Udayakumar, S Sengan
    International Journal of Advanced Science and Technology 29 (3), 8715-8726 , 2019
    2019.0
    Citations: 3
  • A Linear Path Combined MAC Based Routing for Improving the Energy Efficiency in Underwater Acoustic Network
    SA Kalaiselvan, P Udayakumar, R Muruganantham, N Satheesh, ...
    International Journal of Innovative Technology and Exploring Engineering 9 … , 2020
    2020.0
    Citations: 2