Sampath Kumar S

@sece.ac.in

Assistant Professor (Sl. Gr) and Department of Computer Science and Engineering
Sri Eshwar College of Engineering

Sampath Kumar S


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https://researchid.co/thegeeksam

RESEARCH INTERESTS

Blockchain, Drone, Deep Learning, Data Science
17

Scopus Publications

112

Scholar Citations

4

Scholar h-index

2

Scholar i10-index

Scopus Publications

  • An Efficient Fusion with Infrared and Visible Images for Deep Learning Based Adversarial Attack Detection
    P. Murugeswari, P. K. A. Chitra, M. Ramkumar, S. Sampath Kumar
    Circuits Systems and Signal Processing, 2026
  • Grey wolf optimizer with softmax-regressed and tanimoto reweight for AI-ML-based wireless sensor network routing
    Satheesh Kumar D, Satheesh Kumar N, Divya R, Sampath Kumar S
    Peer to Peer Networking and Applications, 2025
  • Aeroponics techniques for improved farming using artificial and deep learning techniques
    C. Amuthadevi, E. Afreen Banu, S. Sampath Kumar, S. Karthick, A. Kistan, M. Sudhakar
    Utilizing Aeroponics Techniques for Improved Farming, 2025
    This chapter will delve into the integration of aeroponics into artificial intelligence and deep learning techniques for agricultural productivity and its sustainability. This is a no-soil farming method where plants grow in a nutrient-rich mist. Therein lies a couple of major advantages: water efficiency and an accelerated pace of plant growth. The reasoning behind the inclusion of AI and deep learning techniques lies in the computer vision and predictive analytics ability—how best it can help determine if this has the potential to optimally run aeroponic systems. Monitoring the health of a plant and the environmental state in real time, using AI-driven sensors and deep learning for analytics, is capable of identifying data patterns in predicting growth and optimizing practices for the delivery of nutrients. Some specific successful cases and novel innovations are exemplified next, showing how new breakthroughs can solve the existing challenges of agriculture, improve yield quality, and ultimately reduce resource consumption.
  • Experimental investigation and comparative analysis of an efficient machine learning algorithm for distribution system reconfiguration
    Kavitha S., Dileep M. R., Sampath Kumar S., Mohammad Shahid, P. Hemachandu, S. Kaliappan
    Metaheuristic and Machine Learning Optimization Strategies for Complex Systems, 2024
    This study studies the implementation of machine learning (ML) algorithms to improve power distribution in an industrial context, concentrating on the essential issue of anticipating energy consumption. Various ML models, including Support Vector Machine (SVM), Artificial Neural Network (ANN), Decision Trees (DT), and Random Forests (RF), were extensively examined and compared for their usefulness in anticipating demand patterns within a sector encompassing machining, forging, CNC, and packaging stations. The models revealed various strengths, with SVM leading with an accuracy of 95.6%, closely followed by ANN at 94.33%, while DT and RF displayed accuracies of 87.6% and 85.6%, respectively. The research additionally gives a thorough comparison of actual vs expected demand levels over hourly intervals, illustrating the models' responsiveness to dynamic energy use patterns throughout the day.
  • A Novel Approach for Detecting Advanced Persistent Threats
    M. Sujith Sairam, M. Shaval Khan, R. Vigneshwaran, S. Yaswanth Kumar, M. Deva Priya
    10th International Conference on Advanced Computing and Communication Systems Icaccs 2024, 2024
    The proposed comprehensive approach to evaluating threats in cloud security is complemented by an innovative solution designed to enhance data loss detection accuracy while prioritizing data privacy and resource efficiency. In the context of cloud security, the multifaceted analysis considers vulnerability information, attack likelihood, and the impact of detected threats, while also addressing the specific security needs of clients. This personalized approach allows cloud security administrators to make precise decisions in selecting mitigation measures tailored to protect outsourced computing assets from targeted attacks. This departure from traditional asset-based systems is paralleled in the data loss detection solution, which introduces a Homomorphic Linear Authenticator (HLA) to improve detection accuracy. By leveraging correlations among lost data, the HLA architecture ensures secure and truthful auditing by virtual machines, minimizing communication and storage overheads, making it suitable for resource-constrained wireless devices. The data-block-based mechanism in this system allows a flexible trade-off between detection accuracy and computational complexity. Crucially, the proposed system guarantees that auditing information cannot compromise the content of the data, thereby safeguarding data privacy. Together, these integrated approaches offer a holistic solution for robust and secure data loss detection, applicable in diverse contexts, including low-cost cloud sensors and wireless devices with limited resources.
  • Unmanned Aerial Systems in Search and Rescue: A Comprehensive Review and Future Directions
    Kowshika M, Ooviya M, Pavithradevi B, Rashika K V, Sampath Kumar S
    Proceedings 2024 5th International Conference on Mobile Computing and Sustainable Informatics Icmcsi 2024, 2024
    Search and Rescue (SAR) operations are critical endeavors in disaster management and public safety, often involving high-risk situations where human lives are at stake. Traditionally, these operations have heavily relied on human resources and ground-based technologies, which can be time consuming, resource-intensive, and constrained by various limitations. In recent years, the integration of drone technology into SAR operations has revolutionized the field, offering a powerful tool to enhance the efficiency, effectiveness, and safety of rescue missions. This study provides an in-depth exploration of the role of drones in human search and rescue operations. It examines the various facets of this technology, including hardware, software, and operational considerations, and highlights the manifold benefits it brings to SAR missions. The most important obligation during a natural disaster is to locate and rescue any trapped individuals as soon as conceivable. Unmanned aerial vehicles (UAVs) have seen a surge in usage recently due to their excellent durability, adaptability, cheap cost, and simplicity of implementation. This article includes a fresh thermal imaging dataset that was obtained by drones. The study discovers the best observers to prune and fine-tune the survivor detection network based on the sensitivity of the convolutional layer due to the restricted computational power and memory of the microprocessor.
  • Investigation of early symptoms of tomato leaf disorder by using analysing image and deep learning models
    Surendra Reddy Vinta, Ashok Kumar Koshariya, Sampath Kumar S, Aditya, Annantharao Gottimukkala
    Eai Endorsed Transactions on Internet of Things, 2024
    Despite rapid population growth, agriculture feeds everyone. To feed the people, agriculture must detect plant illnesses early. Predicting crop diseases early is unfortunate. The publication educates farmers about cutting-edge plant leaf disease-reduction strategies. Since tomato is a readily accessible vegetable, machine learning and image processing with an accurate algorithm are used to identify tomato leaf illnesses. This study examines disordered tomato leaf samples. Based on early signs, farmers may quickly identify tomato leaf problem samples. Histogram Equalization improves tomato leaf samples after re sizing them to 256 × 256 pixels. K-means clustering divides data space into Voronoi cells. Contour tracing extracts leaf sample boundaries. Discrete Wavelet Transform, Principal Component Analysis, and Grey Level Co-occurrence Matrix retrieve leaf sample information.
  • Deep Reinforcement Learning for Autonomous Drone Navigation in Cluttered Environments
    Gautam Solaimalai, Kode Jaya Prakash, Sampath Kumar S, A Bhagyalakshmi, P Siddharthan, K. R Senthil Kumar
    Proceedings 3rd International Conference on Advances in Computing Communication and Applied Informatics Accai 2024, 2024
    This exploration paper investigates the operation of deep underpinning literacy(DRL) for enabling independent drone navigation in cluttered surroundings. Navigating drones in cluttered spaces poses significant challenges due to the presence of obstacles and dynamic environmental conditions. Traditional navigation approaches frequently struggle to acclimatize to these complications. In this study, we propose a new frame using DRL ways to enable drones to autonomously navigate through cluttered surroundings while avoiding obstacles. The frame employs a deep neural network to learn a policy that guides the drone’s conduct grounded on environmental compliances. Through expansive simulations and real-world trials, we demonstrate the efficacity of the proposed approach in achieving robust and adaptive drone navigation in cluttered surroundings. The findings of this exploration have significant counteraccusations for colorful operations, including hunt and deliverance operations, surveillance, and package delivery, where independent drone navigation in cluttered spaces is pivotal.
  • Intelligent Resource Management in Computing using Genetic Algorithms
    Md Hussain Ansari, Balusamy Nachiappan, Sampath Kumar S, Ardly Melba Reena B, Shankar Nagarajan, Jonnadula Narasimharao
    Proceedings of 2024 International Conference on Science Technology Engineering and Management Icstem 2024, 2024
    The purpose of this exploration composition is to probe the use of inheritable algorithms(GAs) for intelligent resource operation in cloud computing settings. The optimization of resource allocation and operation is becoming an increasingly delicate task as cloud computing continues to expand in both complexity and size. The operation of inheritable algorithms, which are deduced from natural selection and the generalities of genetics, gives a promising strategy for addressing this difficulty. inheritable algorithms are suitable to efficiently search and use the result space to gain near-optimal resource allocation ways. This is fulfilled by iteratively evolving a population of seeker results. In this exploration, we probe how inheritable algorithms(GAs) can be employed to perform tasks in cloud surroundings, similar to the placement of virtual machines, the scheduling of workloads, and the provisioning of coffers. This paper investigates the efficacity and scalability of GA-grounded resource operation strategies in cloud computing systems, with the thing of enhancing performance, resource application, and energy effectiveness. This is fulfilled by conducting a conflation of literature and case studies. One of the ultimate pretensions of this exploration is to donate to the development of resource operation results that are both intelligent and adaptive, and that can meet the ever-changing conditions of cloud computing surroundings.
  • Natural Language Processing in Virtual Assistants Current Approaches and Challenges
    Gautam Solaimalai, J. Maria Shanthi, Sampath Kumar S, Priyanka Khabiya, K. Geetha, Gokul Talele
    Proceedings of 2024 International Conference on Science Technology Engineering and Management Icstem 2024, 2024
    The proliferation of virtual sidekicks in colorful disciplines has prodded a swell of interest in advancing Natural Language Processing(NLP) ways to enhance their effectiveness. This paper provides a comprehensive review of the current approaches and challenges encountered in integrating NLP into virtual sidekicks. It begins by outlining the foundational generalities of NLP and its vital part in enabling mortal- suchlike relations with virtual sidekicks. latterly, it delves into a discussion of the different methodologies employed in NLP for understanding and generating mortal language, ranging from rule-grounded systems to deep literacy models. likewise, the paper highlights the crucial challenges such as nebulosity resolution, environment understanding, and handling different verbal variations that stymie the flawless functioning of virtual sidekicks. By synthesizing perceptivity from recent exploration trials, this paper offers precious perspectives on the state-of-the-art NLP ways and directions for unborn exploration to overcome the challenges and propel the development of further intelligent and intuitive virtual sidekicks.
  • A Survey of Resource Management in IoT Data Centre: Techniques and Open Issues
    V Sathya Priya, Harshit Sharma, Neeraj Kumar Singh, Nilesh Dubey, Sampath Kumar S, Prabhishek Singh
    Proceedings 2022 2nd International Conference on Innovative Sustainable Computational Technologies Cisct 2022, 2023
  • SIGN BOT Extending an Ability to Communicate by Creating an Indian Sign Language
    S. Sampath Kumar, Kumar V. Ajay, Nataraj S. Arun, B. Devasarathy, B. Hariharan
    Advances in Science and Technology, 2023
  • Marking and Traceback Algorithm for IP Traceback with Bitwise Operator
    S. Sampath Kumar, M. Prithiv, S. Ravi Kumar, K. Senthil Kumar, K. Vishnu
    Advances in Science and Technology, 2023
  • A Deep Learning-based Innovative Approach for Enhancing the Precision of Tool Wear Prediction
    D. Vinod, Karimulla Syed, Sampath Kumar S, B. Sankara Babu, Shatrudhan Pandey, Raja Velur Loganathan
    Proceedings of the 8th International Conference on Communication and Electronics Systems Icces 2023, 2023
  • Predicting Indian GDP with Machine Learning: A Comparison of Regression Models
    Nikhil Srinivasan, Krishna M, Naveen V, Kishore S M, Sampath Kumar, Subha R
    2023 9th International Conference on Advanced Computing and Communication Systems Icaccs 2023, 2023
  • An Automated Crop and Plant Disease Identification Scheme Using Cognitive Fuzzy C-Means Algorithm
    S. Sampathkumar, R. Rajeswari
    IETE Journal of Research, 2022
  • Tool condition monitoring by quality during the micro milling process by using IoT and AI
    V. naveen Kumar, Gurpreet Singh, S. Rudresha, S Sampath Kumar
    6th International Conference on Electronics Communication and Aerospace Technology Iceca 2022 Proceedings, 2022

RECENT SCHOLAR PUBLICATIONS

  • An Efficient Fusion with Infrared and Visible Images for Deep Learning Based Adversarial Attack Detection
    P Murugeswari, PKA Chitra, M Ramkumar, SS Kumar
    Circuits, Systems, and Signal Processing 45 (2), 1460-1485 , 2026
    2026
  • A nature-inspired dual phased fuzzy hybrid algorithm for adaptive self-healing and dynamic energy-aware resource management in cloud computing
    MARTA Michaelraj Kingston Roberts, Sampath Kumar Shanmugam
    Journal of Cloud Computing 14 (62), 1-23 , 2025
    2025
    Citations: 2
  • Grey wolf optimizer with softmax-regressed and tanimoto reweight for AI-ML-based wireless sensor network routing
    DS Kumar, NS Kumar, R Divya, SS Kumar
    Peer-to-Peer Networking and Applications 18 (3) , 2025
    2025
    Citations: 2
  • Aeroponics techniques for improved farming using artificial and deep learning techniques
    C Amuthadevi, EA Banu, SS Kumar, S Karthick, A Kistan, M Sudhakar
    Utilizing Aeroponics Techniques for Improved Farming, 81-118 , 2025
    2025
    Citations: 6
  • Deep reinforcement learning for autonomous drone navigation in cluttered environments
    G Solaimalai, KJ Prakash, A Bhagyalakshmi, P Siddharthan, KRS Kumar
    2024 International Conference on Advances in Computing, Communication and … , 2024
    2024
    Citations: 9
  • Natural Language Processing in Virtual Assistants Current Approaches and Challenges
    G Solaimalai, JM Shanthi, KS Sampath, P Khabiya, K Geetha, G Talele
    2024 International Conference on Science Technology Engineering and … , 2024
    2024
    Citations: 3
  • Investigation of early symptoms of tomato leaf disorder by using analysing image and deep learning models
    SR Vinta, AK Koshariya, SK S, A Gottimukkala
    EAI Endorsed Transactions on Internet of Things 10 , 2024
    2024
    Citations: 4
  • Experimental Investigation and Comparative Analysis of an Efficient Machine Learning Algorithm for Distribution System Reconfiguration
    S Kavitha, MR Dileep, S Sampath Kumar
    Metaheuristic and Machine Learning Optimization Strategies for Complex … , 2024
    2024
  • A deep learning-based innovative approach for enhancing the precision of tool wear prediction
    D Vinod, K Syed, BS Babu, S Pandey, RV Loganathan
    2023 8th International Conference on Communication and Electronics Systems … , 2023
    2023
    Citations: 2
  • Marking and Traceback Algorithm for IP Traceback with Bitwise Operator
    SS Kumar, M Prithiv, SR Kumar, KS Kumar, K Vishnu
    Advances in Science and Technology 124, 873-880 , 2023
    2023
  • SIGN BOT Extending an Ability to Communicate by Creating an Indian Sign Language
    SS Kumar, KV Ajay, NS Arun, B Devasarathy, B Hariharan
    Advances in Science and Technology 124, 20-27 , 2023
    2023
  • Predicting Indian GDP with machine learning: a comparison of regression models
    N Srinivasan, M Krishna, V Naveen, SM Kishore, S Kumar, R Subha
    2023 9th International Conference on Advanced Computing and Communication … , 2023
    2023
    Citations: 16
  • Tool condition monitoring by quality during the micro milling process by using IoT and AI
    V naveen Kumar, G Singh, S Rudresha, SS Kumar
    2022 6th International Conference on Electronics, Communication and … , 2023
    2023
    Citations: 3
  • A Survey of Resource Management in IoT Data Centre: Techniques and Open Issues
    VS Priya, H Sharma, NK Singh, N Dubey, S Kumar S, P Singh
    2022 2nd International Conference on Innovative Sustainable Computational … , 2022
    2022
    Citations: 3
  • An automated crop and plant disease identification scheme using cognitive fuzzy C-means algorithm
    S Sampathkumar, R Rajeswari
    IETE Journal of Research 68 (5), 3786-3797 , 2022
    2022
    Citations: 58
  • Internet of Things and blockchain based Digital Twin management system
    JS H Summia Parveen, Dr. Sindhu C, S Saradha, S Sampath Kumar, B. Saravanan
    IN Patent .202,241,026,077 , 2022
    2022
  • SIGN BOT Extending an Ability to Communicate by Creating an Indian Sign Language
    HB Sampath Kumar S, Ajay Kumar V, Arun Nataraj S, Devasarathy B
    International Research Conference on IOT, Cloud and Data Science , 2022
    2022
  • Marking and Traceback Algorithm for Ip Traceback with Bitwise Operator
    KV S SAMPATH KUMAR, M PRITHIV, S RAVI KUMAR, K SENTHIL KUMAR
    International Research Conference on IOT, Cloud and Data Science , 2022
    2022
  • Design of Real Time Control of Launch Vehicles using Wireless Sensor Network
    DBJ Dr. Archana Kumar, Dr. Amarendra Alluri, Dr. S. Gomathi, M. R. Faridha ...
    IN Patent 202,211,004,031 , 2022
    2022
  • Deep Learning Approaches for Autonomous UAV Control and Mapping in Cluttered Outdoor Environments
    B MACIEL-PEARSON
    Durham University , 2020
    2020

MOST CITED SCHOLAR PUBLICATIONS

  • An automated crop and plant disease identification scheme using cognitive fuzzy C-means algorithm
    S Sampathkumar, R Rajeswari
    IETE Journal of Research 68 (5), 3786-3797 , 2022
    2022
    Citations: 58
  • Predicting Indian GDP with machine learning: a comparison of regression models
    N Srinivasan, M Krishna, V Naveen, SM Kishore, S Kumar, R Subha
    2023 9th International Conference on Advanced Computing and Communication … , 2023
    2023
    Citations: 16
  • Deep reinforcement learning for autonomous drone navigation in cluttered environments
    G Solaimalai, KJ Prakash, A Bhagyalakshmi, P Siddharthan, KRS Kumar
    2024 International Conference on Advances in Computing, Communication and … , 2024
    2024
    Citations: 9
  • Aeroponics techniques for improved farming using artificial and deep learning techniques
    C Amuthadevi, EA Banu, SS Kumar, S Karthick, A Kistan, M Sudhakar
    Utilizing Aeroponics Techniques for Improved Farming, 81-118 , 2025
    2025
    Citations: 6
  • Investigation of early symptoms of tomato leaf disorder by using analysing image and deep learning models
    SR Vinta, AK Koshariya, SK S, A Gottimukkala
    EAI Endorsed Transactions on Internet of Things 10 , 2024
    2024
    Citations: 4
  • Natural Language Processing in Virtual Assistants Current Approaches and Challenges
    G Solaimalai, JM Shanthi, KS Sampath, P Khabiya, K Geetha, G Talele
    2024 International Conference on Science Technology Engineering and … , 2024
    2024
    Citations: 3
  • Tool condition monitoring by quality during the micro milling process by using IoT and AI
    V naveen Kumar, G Singh, S Rudresha, SS Kumar
    2022 6th International Conference on Electronics, Communication and … , 2023
    2023
    Citations: 3
  • A Survey of Resource Management in IoT Data Centre: Techniques and Open Issues
    VS Priya, H Sharma, NK Singh, N Dubey, S Kumar S, P Singh
    2022 2nd International Conference on Innovative Sustainable Computational … , 2022
    2022
    Citations: 3
  • Heuristic Optimization Using Gene Navigation with the Gravitational Search Algorithm
    RR Sampath Kumar S
    Journal of Electrical Engineering 19 (2) , 2019
    2019
    Citations: 3
  • A nature-inspired dual phased fuzzy hybrid algorithm for adaptive self-healing and dynamic energy-aware resource management in cloud computing
    MARTA Michaelraj Kingston Roberts, Sampath Kumar Shanmugam
    Journal of Cloud Computing 14 (62), 1-23 , 2025
    2025
    Citations: 2
  • Grey wolf optimizer with softmax-regressed and tanimoto reweight for AI-ML-based wireless sensor network routing
    DS Kumar, NS Kumar, R Divya, SS Kumar
    Peer-to-Peer Networking and Applications 18 (3) , 2025
    2025
    Citations: 2
  • A deep learning-based innovative approach for enhancing the precision of tool wear prediction
    D Vinod, K Syed, BS Babu, S Pandey, RV Loganathan
    2023 8th International Conference on Communication and Electronics Systems … , 2023
    2023
    Citations: 2
  • A young female with catastrophic antiphospholipid syndrome
    VS Pari, M Lakshmi, S Kumar, P Sathyamurthy, MK Sudhakar, ...
    Int J Case Rep Images 5 (7), 513-518 , 2014
    2014
    Citations: 1
  • An Efficient Fusion with Infrared and Visible Images for Deep Learning Based Adversarial Attack Detection
    P Murugeswari, PKA Chitra, M Ramkumar, SS Kumar
    Circuits, Systems, and Signal Processing 45 (2), 1460-1485 , 2026
    2026
  • Experimental Investigation and Comparative Analysis of an Efficient Machine Learning Algorithm for Distribution System Reconfiguration
    S Kavitha, MR Dileep, S Sampath Kumar
    Metaheuristic and Machine Learning Optimization Strategies for Complex … , 2024
    2024
  • Marking and Traceback Algorithm for IP Traceback with Bitwise Operator
    SS Kumar, M Prithiv, SR Kumar, KS Kumar, K Vishnu
    Advances in Science and Technology 124, 873-880 , 2023
    2023
  • SIGN BOT Extending an Ability to Communicate by Creating an Indian Sign Language
    SS Kumar, KV Ajay, NS Arun, B Devasarathy, B Hariharan
    Advances in Science and Technology 124, 20-27 , 2023
    2023
  • Internet of Things and blockchain based Digital Twin management system
    JS H Summia Parveen, Dr. Sindhu C, S Saradha, S Sampath Kumar, B. Saravanan
    IN Patent .202,241,026,077 , 2022
    2022
  • SIGN BOT Extending an Ability to Communicate by Creating an Indian Sign Language
    HB Sampath Kumar S, Ajay Kumar V, Arun Nataraj S, Devasarathy B
    International Research Conference on IOT, Cloud and Data Science , 2022
    2022
  • Marking and Traceback Algorithm for Ip Traceback with Bitwise Operator
    KV S SAMPATH KUMAR, M PRITHIV, S RAVI KUMAR, K SENTHIL KUMAR
    International Research Conference on IOT, Cloud and Data Science , 2022
    2022