Dr Balakrishnan S

Scopus Publications

Performance evaluation of a 100 Gbps dual-polarized QPSK-based intersatellite optical wireless communication (IsOWC) system under link impairments
Annamalai Kaliappan, Raju Balakrishnan, Krishnaraj Natarajan, Venkatesalu Ramasamy Balaji, Subramanian Balakrishnan, Mohan Hema Kumar
Journal of Optical Communications, 2026
This paper presents the design and comprehensive performance evaluation of a 100 Gbps dual-polarized quadrature phase shift keying (DP-QPSK)-based intersatellite optical wireless communication (IsOWC) system intended for high-capacity space-borne links. System performance is analyzed under varying link distances, transmitter laser power levels, receiver aperture diameters, transmitter and receiver optical efficiencies, and additional channel losses using key quality metrics such as bit error rate (BER), error vector magnitude (EVM), and constellation diagram analysis. Simulation results reveal that link distance and receiver aperture diameter exert a dominant influence on transmission reliability. For example, with a 15 cm receiver aperture, the log(BER) degrades from −4.21 at 10,000 km to −0.77 at 30,000 km, while EVM increases from 22.88 % to 51.82 %. When the aperture diameter is reduced to 10 cm, performance deterioration becomes more severe, with log(BER) reaching −2.76 at 10,000 km and −0.34 at 30,000 km, and EVM exceeding 60 %. In addition, higher transmitter laser power effectively mitigates pointing error impairments; at 30 dBm with a pointing error of 1 µrad, log(BER) improves to −2.60 compared with −1.42 at 26 dBm, accompanied by a reduction in EVM from 45.70 % to 32.60 %. Constellation observations further validate signal distortion trends, highlighting aperture optimization and power scaling as practical strategies for sustaining robust link quality in next-generation terabit intersatellite optical networks.
DEEP LEARNING MODELS FOR CHOREOGRAPHY GENERATION
Afroj Alam, Sadhana Sargam, Jyoti Rani, Pavas Saini, Amol Bhilare, S. Balakrishnan
Shodhkosh Journal of Visual and Performing Arts, 2025
Due to the rapid development of deep learning, the new opportunities of computational production of human movement have been opened, especially in the field of dance choreography. The paper discusses deep learning choreography generators that combine movement information, music framework, and time in order to create expressive and sensible sequences of dances. Conventional choreography models tend to have a handmade regulation or professionalized composition where flexibility and creative variety is restricted. Conversely, deep learning methods that are data driven can directly learn complex spatio-temporal patterns using big datasets of motion and video. The suggested framework uses pose representations, video frames and rhythmic information based on music to simulate the inherent relationship between motion and sound. Recurrent neural networks as LSTM and GRU models are used to learn long-lasting temporal dependencies in dance sequences whereas transformer-based models are used to improve global context awareness and sequence coherence. Also, generative adversarial networks, diffusion-based networks are explored to achieve motion synthesis which provides smooth transitions, stylistic variability and a sense of realistic continuity in movement. A modular system architecture is structured in such a way that it can allow multimodal inputs, convolutional feature extraction and temporal sequence generation. The evaluation of the experimental results is carried out on standard choreography and motion datasets and performance is measured by quantitative evaluation measures including mean absolute error, Fréchet Inception Distance, and a smoothness index specific to the movement evaluation.
MANAGEMENT OF ONLINE ART EDUCATION PLATFORMS
Priyadarshani Singh, Himanshu Makhija, Chaitanya Joshi, S. Balakrishnan, Hitesh Singh, Prashant Anerao
Shodhkosh Journal of Visual and Performing Arts, 2025
Ecosystems of online art education have become rich online spaces, combining creative pedagogy and smart technology and data-driven management. The research explores a global governance and operational system that combines artificial intelligence and cloud services with ethical policies to provide more accessibility, quality, and sustainability in the learning of digital art. The study identifies the use of human-AI hybrids in enhancing the learner experience, teaching and learning, and organizational effectiveness by analyzing the stakeholder collaboration, learning outcomes, and risk management aspects. The model focuses on fair monetization, transparency of intellectual property management and culturally aware content curation such that creativity and accountability exist in a safe online space. Analysis of quantitative performance shows that there are great correlations between the engagement performance and completion rates, consistent increase in revenue growth and system reliability which confirms the suggested governance model. The paper ends with a strategic plan, based on which immersive technologies, predictive analytics, and blockchain-based accreditation might be integrated to promote the concept of sustainable and inclusive art education in the global context.
Advancing cardiac motion estimation with emerging AI techniques for enhanced echocardiographic image registration
M. Rajesh, S. Balakrishnan, R. Elankavi
Methodsx, 2025
Monitoring and diagnosis of cardiovascular diseases rely on cardiac motion estimation. The methods used for registering echocardiographic images have drawbacks such as low resolution, noise, and distortion of the anatomy. In order to enhance the prediction of cardiac motion, this research presents an AI-powered architecture that makes use of Vision Transformers, Diffusion Models, and Neural Radiance Fields (NeRF). Adversarial and self-supervised contrastive learning enhance picture quality and generalisability across adult and foetal echocardiography, while a graph neural network (GNN)-based anatomical constraint maintains heart shape. Better, more accurate, more efficient real-time motion tracking without relying on massive labelled datasets is possible with the proposed approach. Cardiac motion analysis in a wide range of patient populations is now therapeutically viable, thanks to this innovative approach that improves echocardiographic picture registration.•Utilizes Vision Transformers, Diffusion Models, and NeRF for high-quality cardiac motion prediction.•Adversarial and self-supervised contrastive learning improve echocardiographic registration across demographics.•A GNN-based anatomical constraint ensures accurate heart morphology during motion analysis.
A Blockchain-Based Authentication Handover Protocol for Autonomous Vehicle Networks
Tasmimgiri Va Tahqiq Dar Amaliyyat, 2025
Hypersoft Sets with Weight-Based SVM for Medical Uncertainty Modeling: A Case Study in Heart Disease Diagnosis
Journal of Fuzzy Extension and Applications, 2025
Enhancing 5G Networks Performance Using MIMO and MU-MIMO Technologies for High-Capacity Communication
P. Ashok, D. Sumathi, Krishnaraj Natarajan, S. Balakrishnan
Internet Technology Letters, 2025
In order to accommodate the exponential growth of data‐intensive apps and linked devices in the current era, the next generation of wireless networks must offer extraordinarily high speeds, great connection, and low latency. Two of the most significant advanced technologies fifth‐generation (5G) networks use to fulfill these goals are multiple‐input multiple‐objectives (MIMO) and multiuser MIMO (MU‐MIMO). The main emphasis of this work is on high‐capacity communication and how MIMO and MU‐MIMO technologies might enhance the performance of the 5G network. MU‐MIMO expanded allows several users to access the same time‐frequency resources free from interference, thereby optimizing spectrum consumption and boosting network capacity. These solutions meet the congested and dynamic conditions typical of modern urban and industrial settings by allowing flawless mobile broadband and ultrareliable low‐latency communications (URLLC). The present article investigates the foundations of MIMO and MU‐MIMO, how they are included into 5G new radio (NR) standards, and what part beamforming, spatial multiplexing, and channel estimation play in them. Among the subjects addressed are hardware complexity, pilot contamination, and channel state information (CSI) acquisition. Real‐time inference and task scheduling in E5G‐SPF are powered by machine learning for predictive analytics and reinforcement learning for dynamic resource allocation. These techniques enable adaptive decision‐making and efficient task management. 5G networks use MIMO and MU‐MIMO to manage the great rise in user demand and data traffic. Without these technologies, which this paper contends are necessary to open the path for future developments in the 6G network, the expected performance targets of 5G cannot be reached.
Big Data and Fuzzy Logic for Demand Forecasting in Supply Chain Management: A Data-Driven Approach
Journal of Fuzzy Extension and Applications, 2025
Monitoring COVID-19 environment: a real-time facial mask detection using YOLO models
P. Pandiyan, Rajasekaran Thangaraj, Balasubramanian V, Manavalasundaram V. K, Balakrishnan S
Research on Biomedical Engineering, 2025
Challenges and Future Directions
S. Balakrishnan, Kumar RM Sunil, S. Simonthomas
Engineering the Circular Economy Leveraging Fuzzy Logic for Implementation, 2025
The chapter examines the challenges and opportunities in integrating fuzzy logic with circular economy (CE) practices. The CE model increases relevance in addressing global environmental issues through sustainability, waste reduction, and efficient resource management. Yet there are many challenges, such as uncertainty in the flows of materials, complex demand forecasting, and integrating diversities of stakeholders. Previous researches have looked into the fuzzy logic application to handle uncertainty and imprecision in various systems but are underinvestigated for their application in the circular economy. This chapter fills this gap by investigating how fuzzy logic can enhance decision-making in CE processes, especially in areas like product life cycle management, resource recovery, and supply chain optimization. The research uses a combination of case studies and analytical methods to demonstrate how fuzzy systems can model uncertainty and provide adaptive solutions in dynamic CE environments. The findings show that fuzzy logic offers practical and scalable solutions for overcoming key barriers to CE implementation. The chapter emphasizes fuzzy algorithm refinement and the inclusion of future technologies such as AI and IoT in order to push forward in circular economy strategies for sustainable, efficient, and more resilient systems.
Dynamic Image-Based Screening for Effective Lidar Data Noise Elimination in Unsupervised Driving
Balakrishnan S, K Srinivas Rao, K. Mohana Prabha, Rajesh M
5th IEEE International Conference on Innovations in Power and Advanced Computing Technologies I Pact 2025, 2025
Designing Intelligent Traffic Routing Systems for Autonomous Vehicles using the Deep Learning based Optimization Algorithm
S. Balakrishnan, S. Simonthomas, B. Prasad, K. Srinivas Rao
Proceedings of 5th International Conference on Soft Computing for Security Applications Icscsa 2025, 2025
Machine Learning based Portable Executable Malware and DDoS Attacks Detection in IoT Networks
S. Balakrishnan, S. Leelavathy, Sunil Kumar RM, S. Simonthomas
Proceedings of the International Conference on Intelligent Computing and Control Systems Iciccs 2025, 2025
Blockchain-Integrated Federated Learning for IoT-Based Smart Applications
S. Balakrishnan, Syed Shahul Hameed, RM Sunil Kumar, S. Simonthomas
Applications of Federated Learning in Technological Advancements Use Cases and Applications, 2025
Optimizing Smart Grid Performance through Real-Time State Estimation and Forecasting using Deep Learning based LSTM Models
S. Balakrishnan, S. Simonthomas, S. Senthil Kumar, K. Srinivas Rao, M. Madhan Kannan
2025 IEEE 2nd International Conference on Green Industrial Electronics and Sustainable Technologies Giest 2025, 2025
USING AI TO PERSONALIZE CREATIVE LEARNING PATHS
Vivek Kumar, S. Balakrishnan, Gurpreet Kaur, Jaskirat Singh, Abhinav Srivastav, Pawan Wawage
Shodhkosh Journal of Visual and Performing Arts, 2025
AI-DRIVEN BLOCKCHAIN SOLUTIONS FOR ENHANCING DECISION-MAKING IN COMPLEX ENGINEERING PROJECTS
Inderpreet Kaur, Balaji N., Suresh A., Manoharan S. N., Balakrishnan S., Jagadesh T.
Engineering Review, 2025
INTEGRATING AI AND OR FOR REAL-TIME OPTIMIZATION IN DIGITAL TWIN ECOSYSTEMS AND METAVERSE ENGINEERING
Nithyashri J., Naveeth Babu C., Jayaraj Velusamy, Cowsigan S.P., Balakrishnan S., Anitha R.
Engineering Review, 2025
AI-Driven Edge Cloud Collaboration Framework With Autonomous Resource Allocation for Standardized 6G Healthcare Networks
S. Balakrishnan, M. Senbagavalli, M. Manikandan, D. Sumathi, Navyatha Ravi, Mohammad Shabaz
IEEE Communications Standards Magazine, 2025
Toward Standardized Energy-Aware Adaptive Routing Protocols for Ultra-Dense 6G Networks With Integrated Satellite-Terrestrial Architectures
S. Balakrishnan, Gunasekaran Thangavel, M. Manikandan, S. Vinodhkumar, M. Rajesh, Mohammad Shabaz
IEEE Communications Standards Magazine, 2025
Enhancing Smart Grid Performance with LSTM-Based Real-Time State Monitoring and Prediction
S. Simonthomas, S. Balakrishnan, K. Shantha Shalini, S. Alex, J. Jayasuthan, Bandaru Siva Ganesh
2025 IEEE 1st International Conference on Innovations in Engineering and Next Generation Technologies for Sustainability Icinvents 2025, 2025
Federated Learning and Digital Twin-Enabled Predictive Security Architectures With Standardized Policy Enforcement for Zero-Touch 6G Networks
A. Kaliappan, S. Balakrishnan, K. Kavipriya, S. Alagumuthukrishnan, Pramoda Patro, Mohammad Shabaz
IEEE Communications Standards Magazine, 2025
Automated Diagnosis of Cancer Disease with Human Tissues using Haralick Texture Features and Deep Learning Techniques
S. Balakrishnan, N.S. Simonthomas, J. Nithyashri, B. Suchitra, G. Umamaheswari, D. Pradeep
International Journal of Computational and Experimental Science and Engineering, 2024
Remote Sensing Data-Based Satellite Image Analysis in Water Quality Detection for Public Health Data Modelling
S. Balakrishnan, P Michael Preetam Raj, J. Somasekar, Kambala Vijaya Kumar, S. Amutha, A. Sangeetha
Remote Sensing in Earth Systems Sciences, 2024
Deep Learning Algorithm Design for Discovery and Dysfunction of Landmines
S. Leelavathy, S. Balakrishnan, M. Manikandan, J. Palanimeera, K. Mohana Prabha, R. Vidhya
International Journal of Computational and Experimental Science and Engineering, 2024
Predicting nitrous oxide contaminants in Cauvery basin using region-based convolutional neural network
Ravi Kumar Poluru, Shanmugam Sundararajan, Vinodhkumar S, S. Balakrishnan, Sathya V, Manikandan Rajagopal
Groundwater for Sustainable Development, 2024
An emergence of technological aids using machine learning algorithms to curtail the mounting manifestation of dyspraxia
S. Balakrishnan, K. Suresh Kumar, J. Janet, D. Vijendra Babu, Chandra Prakash Lora
Multimedia Tools and Applications, 2024
Monitoring of Drowsiness Using OpenCV and Python
Akash, Kishan, Shyam, Balakrishnan Subramanian
Aip Conference Proceedings, 2024
A Survey for Recognizing Sign Language for Deaf-Mute People Using Image-Based Hand Recognition
S. Balakrishnan, B. Naveen Kumar, S. Kiran Subramanian, R. Nithiskumar
Aip Conference Proceedings, 2024
Artificial Intelligence-Based Vociferation Chatbot for Emergency Health Assistant
S. Balakrishnan, P. Sri Jayanth, S. Parvathynathan, R. Sivashankar
Aip Conference Proceedings, 2024
Eye Tracking and Assistance Using Deep Learning for Paralyzed People with Cloud Integration for Data Processing
Bhavik Kumar, Imron Khan, Nishit, Balakrishnan Subramanian
Aip Conference Proceedings, 2024
A Survey on Protocol Based Control System to Enhance Internet Censorship
Balakrishnan Subramanian, Yogeshwaran, Kabilan, Mohamed Nousath Yusuf
Aip Conference Proceedings, 2024
A Survey on Artificial Intelligence Based Assisted Writing Device to Support Dyslexia Affected Children
Janet Jude, Balakrishnan Subramanian, Ananth, Majidha Fathima
Aip Conference Proceedings, 2024
A secured and energy-efficient system for patient e-healthcare monitoring using the Internet of Medical Things (IoMT)
Veera V Rama Rao M, Kiran Sree Pokkuluri, N. Raghava Rao, Sureshkumar S, Balakrishnan S, Shankar A
Data and Metadata, 2024
IOT based prediction of rainfall forecast in coastal regions using deep reinforcement model
J. Nithyashri, Ravi Kumar Poluru, S. Balakrishnan, M. Ashok Kumar, P. Prabu, S. Nandhini
Measurement Sensors, 2023
CLOUD load balancing for storing the internet of things using deep load balancer with enhanced security
K. Dhana Sree Devi, D. Sumathi, V Vignesh, Chunduru Anilkumar, Kirankumar Kataraki, S. Balakrishnan
Measurement Sensors, 2023
Retraction Note to: Automated query classification based web service similarity technique using machine learning (Journal of Ambient Intelligence and Humanized Computing, (2021), 12, 6, (6169-6180), 10.1007/s12652-020-02186-6)
B. Saravana Balaji, S. Balakrishnan, K. Venkatachalam, V. Jeyakrishnan
Journal of Ambient Intelligence and Humanized Computing, 2023
Retraction Note to: MCAMO: multi constraint aware multi-objective resource scheduling optimization technique for cloud infrastructure services (Journal of Ambient Intelligence and Humanized Computing, (2021), 12, 6, (5909-5916), 10.1007/s12652-020-02138-0)
S. Ramamoorthy, G. Ravikumar, B. Saravana Balaji, S. Balakrishnan, K. Venkatachalam
Journal of Ambient Intelligence and Humanized Computing, 2023
Retraction Note to: Optimized virtual network function provisioning technique for mobile edge cloud computing (Journal of Ambient Intelligence and Humanized Computing, (2021), 12, 6, (5807-5815), 10.1007/s12652-020-02122-8)
R. S. Ponmagal, S. Karthick, B. Dhiyanesh, S. Balakrishnan, K. Venkatachalam
Journal of Ambient Intelligence and Humanized Computing, 2023
A new method for human activity identification using convolutional neural networks
P.S. Prakash, S. Balakrishnan, K. Venkatachalam, Saravana Balaji Balasubramanian
International Journal of Cloud Computing, 2023
Deep Learning Techniques for Cybersecurity Applications
S Balakrishnan, G Aswin, Mohan Babu Chowdary, V. Arulkumar
Computational Intelligence for Cybersecurity Management and Applications, 2023
Online Complaint Management System using Image Recognition
S. Balakrishnan, J. Janet, Rohith T, Sakthivel R, Sanjaiy Kumar T N
Proceedings of the 8th International Conference on Communication and Electronics Systems Icces 2023, 2023
IoT for Health Monitoring System Based on Machine Learning Algorithm
S. Balakrishnan, K. Suresh Kumar, L. Ramanathan, S. K. Muthusundar
Wireless Personal Communications, 2022
Intelligent Document Finding using Optical Character Recognition and Tagging
A. Mohamed Abbas, M. Syed Shahul Hameed, S. Balakrishnan, K. S. Anandh
International Conference on Automation Computing and Renewable Systems Icacrs 2022 Proceedings, 2022
Opinion Mining for Breast Cancer Disease Using Apriori and K-Modes Clustering Algorithm
S. Balakrishnan, K. Suresh Kumar, M. Balasubramanian, Y. Rajkumar
Lecture Notes in Networks and Systems, 2022
A High Security Framework Through Human Brain Using Algo Mixture Model Deep Learning Algorithm
S. Balakrishnan, J. P. Ananth, L. Ramanathan, R. Sachinkanithkar, S. Rajkumar
Studies in Big Data, 2022
Sentiment Analysis on Book Reviews Using Machine Learning Techniques
V. R. Azhaguramyaa, J. Janet, G. R. Madhavan, S. Balakrishnan, K. Arunkumar
8th International Conference on Advanced Computing and Communication Systems Icaccs 2022, 2022
Impact of Early Termination of Lockdown and Maintaining Social Distancing: COVID-19
Syed Muzamil Basha, J. Janet, S. Balakrishnan, Sajeev Ram, Somula Ramasubbareddy, N. Ch. Sriman Narayana Iyengar
How Covid 19 is Accelerating the Digital Revolution Challenges and Opportunities, 2022
A cloud-based prototype for the monitoring and predicting of data in precision agriculture based on internet of everything
K. Suresh Kumar, S. Balakrishnan, J. Janet
Journal of Ambient Intelligence and Humanized Computing, 2021
Automated query classification based web service similarity technique using machine learning
B. Saravana Balaji, S. Balakrishnan, K. Venkatachalam, V. Jeyakrishnan
Journal of Ambient Intelligence and Humanized Computing, 2021
Optimized virtual network function provisioning technique for mobile edge cloud computing
R. S. Ponmagal, S. Karthick, B. Dhiyanesh, S. Balakrishnan, K. Venkatachalam
Journal of Ambient Intelligence and Humanized Computing, 2021
MCAMO: multi constraint aware multi-objective resource scheduling optimization technique for cloud infrastructure services
S. Ramamoorthy, G. Ravikumar, B. Saravana Balaji, S. Balakrishnan, K. Venkatachalam
Journal of Ambient Intelligence and Humanized Computing, 2021
An embarking user friendly palmprint biometric recognition system with topnotch security
S. Balakrishnan, Venkatesan K., M.Syed Shahul Hameed
Proceedings 5th International Conference on Intelligent Computing and Control Systems Iciccs 2021, 2021
Interaction of Spatial Computing in Augmented Reality
S. Balakrishnan, M.Syed Shahul Hameed, K Venkatesan, G Aswin
2021 7th International Conference on Advanced Computing and Communication Systems Icaccs 2021, 2021
Retraction Notice: An Exploration of Robotic Process Automation in all Spans of Corporate Considerations (2021 7th International Conference on Advanced Computing and Communication Systems (ICACCS) DOI: 10.1109/ICACCS51430.2021.9441996)
S. Balakrishnan, M.Syed Shahul Hameed, K Venkatesan, G Aswin
2021 7th International Conference on Advanced Computing and Communication Systems Icaccs 2021, 2021
An Exploration of Robotic Process Automation in all Spans of Corporate Considerations
S. Balakrishnan, M.Syed Shahul Hameed, K Venkatesan, G Aswin
2021 7th International Conference on Advanced Computing and Communication Systems Icaccs 2021, 2021
Preface
Ceur Workshop Proceedings, 2021
Reflections on COVID-19 in India: A survey
M. Balasubramanian, S. Balakrishnan
International Journal of Pharmaceutical Research, 2020
Performance evaluation of naive bayes classifier with and without filter based feature selection
D. Prabha, R. Subramanian, S. Balakrishnan, M. Karpagam
International Journal of Innovative Technology and Exploring Engineering, 2019
Heart disease prediction using machine learning algorithm
Praveen Kumar Reddy Maddikunta, T Sunil Kumar Reddy, S. Balakrishnan, Syed Muzamil Basha, Ravi Kumar Poluru
International Journal of Innovative Technology and Exploring Engineering, 2019
A novel and secured intrusion detection system for wireless sensor networks using identity based online/offline signature
Arpn Journal of Engineering and Applied Sciences, 2018
A novel and efficient mobile cloud service for searching encrypted data
Arpn Journal of Engineering and Applied Sciences, 2018
Machine learning based grape leaf disease detection
Journal of Advanced Research in Dynamical and Control Systems, 2018
Data movement optimization in a cloud environment using capacity optimization technique
Journal of Advanced Research in Dynamical and Control Systems, 2018
Extensibility of file set over encoded cloud data through empowered fine grained multi keyword search
S. Balakrishnan, J. Janet, S. Spandana
Advances in Intelligent Systems and Computing, 2017
Retraction:Coronary heart disease detection from variation of speech and voice
Suman Mishra, S. Balakrishnan, M. Babitha
Advances in Intelligent Systems and Computing, 2017
Fountain code based cloud storage mechanism for optimal file retrieval delay
J. Janet, S. Balakrishnan, Kesani Somasekhara
2016 International Conference on Information Communication and Embedded Systems Icices 2016, 2016
Improved data transfer scheduling and optimization as a service in cloud
J. Janet, S. Balakrishnan, E. Murali
2016 International Conference on Information Communication and Embedded Systems Icices 2016, 2016
Optimizing data movement within cloud environment using efficient compression techniques
J. Janet, S. Balakrishnan, E. Reddy Prasad
2016 International Conference on Information Communication and Embedded Systems Icices 2016, 2016
Information security in D-media (digital media)
Arpn Journal of Engineering and Applied Sciences, 2016
An agent based centralized router with dynamic connection management scheme using JADE
International Journal of Applied Engineering Research, 2016
Multiagent based open source for supply chain management using JADE
Rolls John, S. Balakrishnan
2014 International Conference on Information Communication and Embedded Systems Icices 2014, 2015
An agent based collaborative spam filtering assistance using JADE
International Journal of Applied Engineering Research, 2015
A multiagent based secured video authentication scheme using jade
International Journal of Applied Engineering Research, 2015
An effective two way classification of breast cancer images
International Journal of Applied Engineering Research, 2015
Amelioration of artificial intelligence using game techniques for an imperfect information board game geister
International Journal of Applied Engineering Research, 2014

Dr Balakrishnan S

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