Dr.P.Venkadesh

Scopus Publications

Blockchain for Content Authentication and Copyright Protection
S. V. Divya, P. Venkadesh, S. Saravanaprabhu, Jelin Taric G., S. Yazhini, M. Shify Antolin
Securing AI Generated Media with Blockchain Technologies, 2025
Digital media has provided new frontiers where the challenge to authentication and copyright is unparalleled. The emergence of new solutions for safeguarding intellectual property rights and ensuring authenticity in content becomes necessary. This chapter introduces blockchain integration as a means of authenticating AI-generated content with secure attribution against risks of unlawful duplication or misappropriation and how blockchain-based systems allow verifiable ownership of digital assets through smart contracts that automate licensing, royalty collection, and the tracking of use. This chapter goes deeply into the technical architecture of blockchain applications in digital media, illuminating its capacity to create trust and accountability in this fast-evolving creative ecosystem. Ethical, legal, and scalability considerations discuss the role that blockchain is playing in building a fairer and more transparent digital economy.
Teaching Methods for AI-Driven HR Practices
P. Venkadesh, R. Mathusoothana S. Kumar, L. Shalini, S.V. Divya, R. Sukesh
Emerging Technologies for Recruitment Strategy and Practice, 2025
Using Artificial Intelligence (AI) in Human Resources (HR) has completely changed HR work. Now, decisions about managing workers are smarter and based on data. AI uses tools like machine learning, predictive analysis, and natural language processing, and these are key for recruitment, keeping employees satisfied, managing talent, and organizational planning. So, how we teach HR professionals also needs to change. This chapter talks about new teaching methods focused on AI in HR. It highlights learning from different areas, hands-on learning, and thinking about ethics. It offers a detailed plan for what should go into teaching materials, the key skills needed, and includes practical tools, real-world examples, and ways to test understanding. The goal is to help teachers and students create and run programs that fit the changing HR field. By doing this, future HR leaders will be well-prepared for a workplace driven by data and digital technology.
Virtual Reality for Interview Simulations
P. Venkadesh, S. Ninisha Nels, S.V. Divya, K.V. Shiny, M. Sudhan
Emerging Technologies for Recruitment Strategy and Practice, 2025
Virtual Reality (VR) is transforming recruitment by offering immersive, interactive simulations that replicate real job scenarios. Unlike traditional interviews, VR enables recruiters to assess behavioral traits, decision-making, communication, and cultural fit with greater precision. Powered by Artificial Intelligence (AI) and Big Data, VR systems analyze verbal and non-verbal cues to predict job performance, reduce bias, and improve hiring outcomes. Industries such as emergency medicine, software engineering, and retail have successfully adopted VR, resulting in better employee retention and reduced training costs. Gamified and AI-driven environments enhance candidate engagement through avatar-based interactions, real-time feedback, and collaborative problem-solving. VR can simulate high-pressure scenarios to evaluate emotional intelligence, adaptability, and leadership—traits often overlooked in conventional interviews. This Chapter deals with how Virtual Reality helps for Interview simulations in conduction a smooth and efficient interview virtually.
Ethical and regulatory dimensions of integrating AI in nuclear medicine
P. Venkadesh, B. Selvapriya, S. V. Divya, C. Berin Jones, S. Keerthana
AI Insights on Nuclear Medicine, 2025
The integration of Artificial Intelligence (AI) into nuclear medicine holds the potential to revolutionize both diagnostic and therapeutic approaches. However, this transformative technology brings with it significant ethical and regulatory challenges that require careful attention. Ethical concerns such as patient privacy, data security, algorithmic bias, and the accountability of AI-driven decisions raise critical questions about trust and fairness in healthcare. Additionally, the lack of standardized regulatory framework creates additional hurdles for ensuring the safe and effective implementation of AI systems in clinical practice. By addressing these issues, the chapter aims to provide a roadmap for the responsible development and deployment of AI in nuclear medicine. It advocates for a collaborative approach among technologists, medical professionals, policymakers, and ethicists to ensure that AI enhances patient care while upholding the principles of fairness, accountability, and transparency.
Streamlining Photo Sorting: Augmenting iOS Application
S. H. Annie Silviya, T. S. Lakshmi Prabha, P. Venkadesh, S. Rahavi, J. Syed Thahir Hussain, B. L. Sai Vighnessh
Aip Conference Proceedings, 2025
Deep Learning Based - Brain Stroke Detection System on CT Images using CNN and Federated Learning (CNN-FL)
P. Venkadesh, S.V. Divya, L.S. Karunya, M. Dhanushya, M.Monica Hirin
2025 8th International Conference on Circuit Power and Computing Technologies Iccpct 2025, 2025
Brain Stroke is one of the leading causes of death and long-term disability worldwide, with early detection being crucial for successful intervention and treatment. The use of deep learning techniques in medical imaging, particularly Convolutional Neural Networks (CNNs), has greatly improved the efficiency and accuracy of stroke detection in CT scans. Additionally, Federated Learning (FL), a decentralized machine learning technique, has emerged as an effective solution for training models across distributed datasets while preserving privacy and security. This work explores the hybrid application of CNNs combined with FL to detect and localize strokes in CT images, aiming to improve model performance while addressing privacy concerns. The CNN model was used to classify CT images as either brain stroke or non-stroke, achieving high accuracy, precision, and recall. With FL, the model was trained across multiple medical institutions without sharing sensitive patient data, ensuring privacy and security while also making it more robust and adaptable by learning from diverse datasets worldwide. The results demonstrate that the combination of CNN and FL not only maintains high detection accuracy but also addresses privacy concerns associated with sensitive medical data. The system outperforms traditional centralized learning models in terms of data privacy, without compromising the accuracy or performance of brain stroke detection. In conclusion, CNNs, when paired with FL, offer a powerful solution for large-scale brain stroke detection, enabling real-time, privacy-preserving, and collaborative medical imaging applications. Future research should focus on further improving the efficiency of FL frameworks and exploring their application in other areas of medical imaging. The proposed Hybrid CNN with FL boosts stroke detection accuracy to $94 \%$, surpassing traditional CNNs (89%) by $5 \%$ and ML models ($84 \%$) by $10 \%$. This improvement not only enhances detection reliability but also strengthens data privacy and scalability.
GenNav - AI Enhanced Autonomous Vehicle Safety Using Generative Models
P. Venkadesh, S.V. Divya, K. Kasthuri, R.M. Madhushree, M. Aishwarya
Proceedings of the 2025 International Conference on Computational Innovations and Sustainable Technologies Iccist 2025, 2025
The GenNav is a novel approach that combines predictive modelling with generative models to enhance the safety of self-driving automobiles. GenNav applies modern machine learning methods to realistically recreate challenging driving situations, such as sudden obstacles and unpredictable pedestrian behaviour-issues that earlier systems often failed to manage. Many existing autonomous vehicle safety models rely on fixed algorithms and limited datasets, making it difficult for them to respond effectively to unusual or rapidly changing road conditions. This weakness increases the risk of safety failures and reduces public confidence in autonomous technology.A major limitation in current systems is their inability to simulate rare or unexpected events, which leads to poor decision-making in critical moments. GenNav addresses this problem by combining generative models with predictive simulations to create a more flexible and responsive navigation framework. By using continuous real-time sensor data, it builds dynamic driving scenarios that help vehicles operate more safely in complex environments [1]. This approach aims to reduce accidents and strengthen public trust in autonomous transportation [2].The system blends sensor inputs with crowdsourced information to improve decision-making and uses Explainable AI to provide clear reasoning for its actions. Through extensive real-world and virtual testing, GenNav demonstrates strong reliability and aligns with regulatory standards, supporting a safer and smarter autonomous ecosystem.
IoT-Based Water Usage Tracking and Automated Tax Computation (WUTATCS) System
T. Hemalatha, S.V. Divya, P. Venkadesh, D. Dharnesh, R. Jesvin, S. Naveenkumar
Proceedings of the 9th International Conference on Inventive Systems and Control Icisc 2025, 2025
The issue of water scarcity and inefficiency in water resources has become a big issue in the world threatening the environment, the social and economic stability of all nations across the world. Urbanization at a faster rate, increased population in the world, industries and the increasing effects of climate change have made it a necessity to come up with a smart and sustainable solution to this. The traditional systems that were used to distribute and meter water have been faced with many limitations which include slow billing by the respective authorities and providers, the readings are not accurate at times, the leakages are not tracked and the water users do not get realtime information about the water that they are using. All these play a very crucial role in waste and mismanagement of water. To solve this problem, this research paper introduces the IoTBased Water Usage Tracking and Automated Tax Computation System (WUTATCS), an innovative and technology-driven approach that offers comprehensive, real-time water usage monitoring and data-centric management. The uniqueness of the WUTATCS system lies in the integration of IoT-enabled smart water meters within homes, businesses, and industries. These water meters contain in-built flow and pressure sensors that collect data, and they transmit this information to cloudbased servers via secure communication channels.
Driver Somnolence and Lethargy Detection Model based on Eyes and Facial Movement using OpenCV Library (EyeF Model)
R. Murugadoss, P. Venkadesh, M Srivimal, S.V Kumaraguru, J Stanis Jeba, J Aurlian
2025 8th International Conference on Circuit Power and Computing Technologies Iccpct 2025, 2025
Fatigue and drowsiness are significant contributing factors to driver alertness, which tend to cause severe road accidents because reaction times are slower and judgment is impaired. It is important to detect these early to ensure safe driving. Monitoring eye movements has been found to be a good method of identifying drowsiness signs, with methods such as PERCLOS (Percentage of Eyelid Closure), EAR (Eye Aspect Ratio), and YOLO (You Only Look Once) being used to monitor in real-time. Yet, each of these approaches possesses its own difficulties, including compensation for lighting variation and separating typical behaviour from tiredness. Through the integration of the strengths of all three approaches, a hybrid model assists in eliminating these drawbacks and providing a more balanced and more precise method of identifying indicators of fatigue. Testing shows that this method delivers high precision in real-time, significantly reduces false alerts, and improves overall system reliability. With its strong potential for use in everyday transportation, this approach could make driver monitoring more effective and help prevent accidents caused by fatigue.
AI in Bioinformatics Unlocking the Secrets of Life
P. Venkadesh, S. V. Divya, V. Mathumitha, S. Ninisha Nels, J. Balaji, Aiswariya Ramesh
Role of Artificial Intelligence in Advancing Applied Life Sciences, 2025
Bioinformatics, where Artificial Intelligence (AI) meets biology, as transforming our understanding of life. By combining machine learning algorithm with tools like blast and cluster Omega, scientists are deciphering DNA and predicting protein structure. AI models such as CNN's and RNN's, help analyze DNA sequence, identify genetic variation and predict mutation effects. Alpha fold, developed by deep mind has made groundbreaking strides and protein folding, essential for drug discovery and under disease research. AI platforms like atom wise and benevolent AI accelerate drug discovery by analyzing massive datasets. AI even uses Natural Language Processing (NLP) to process scientific literature, uncovering insights and suggesting result direction. Looking ahead, AI ensures transparency, making advancement more trustworthy. Together, bioinformatics and AI are reshaping feels like personalized medicine and synthetic biology. With endless possibilities the next breakthrough in biology may be just algorithm away, our journey into frontier has only begun.
Multi Modal Deep Learning Framework for Malpractice Detection in Virtual Exams Using YOLOV5
G. Nithya, P. Venkadesh, S.V. Divya, D Philip Daniel, V Praveenkumar, V Suryakumar
2025 8th International Conference on Circuit Power and Computing Technologies Iccpct 2025, 2025
A Hybrid CNN-LSTM Multi-Modal for Early Detection and Recurrence Prediction of Ovarian Cancer and Model Transparency using SHAP and LIME
B. Jebaranjani, P. Venkadesh, S.V. Divya, M. Mahalakshmi, D. Shalini, P. Prasitha
2025 8th International Conference on Circuit Power and Computing Technologies Iccpct 2025, 2025
Social Media Aided E-Commerce Dynamic Pricing System using GPT-3.5 and XGB Regressor
M Abernakumari, P. Venkadesh, S.V. Divya, C. Irfan, A F Godwin, S Roshan Kumar
2025 8th International Conference on Circuit Power and Computing Technologies Iccpct 2025, 2025
A Hybrid Convolutional Neural Network Integrated with Federated Learning and Bayesian Optimization (HCNNFLB)Technique for Diabetes Prediction
S.V. Divya, P. Venkadesh, R Deva, S Aadhavan, Js Livish, K Subash Kumar
2025 8th International Conference on Circuit Power and Computing Technologies Iccpct 2025, 2025
TruthChain: A Decentralized News Verification System Using Blockchain and AI
V. Murugalakshmi, P. Venkadesh, S.V. Divya, T Gopinath, P Jesso, T Suresh Raja
2025 8th International Conference on Circuit Power and Computing Technologies Iccpct 2025, 2025
A Multimodal Neural Fusion Framework by Integrating T-CNN and L-DL for Drug Discovery
S. V. Divya, B. Selvapriya, P. Venkadesh, J. Balaji, Yazhini. S, Shify Antolin. M
2025 International Conference on Recent Advances in Electrical Electronics Ubiquitous Communication and Computational Intelligence Raeeucci 2025, 2025
Improving Sentimental Analysis Through Integration of BERT
G. Nithya, P. Venkadesh, S.V. Divya, Adithyamahraj K, Muthualiasranjithkumar S, Mukilan M
Proceedings of the 9th International Conference on Inventive Systems and Control Icisc 2025, 2025
QR-based Fernet Encryption and Decryption Framework for File Protection System (QR-FEDF)
S. Soundhar, P. Venkadesh, S.V. Divya, R. Gobiprakash, A. Paramasivan, P. Suryamarilan
2025 8th International Conference on Circuit Power and Computing Technologies Iccpct 2025, 2025
Vision Transformer-Based Context-Aware Image Captioning System with Transformer Decoder Integration
D.S. Jayakumari, P. Venkadesh, S.V. Divya, K. Santhoshkumar, S. Elakkian, R. Sarathi
2025 8th International Conference on Circuit Power and Computing Technologies Iccpct 2025, 2025
Virtual Mouse for Amputee using Computer Vision and CNN-SVM
S. Soundhar, P. Venkadesh, S.V. Divya, P. Prajeesh, T. SowndharBharathi, M. Elayaraja
2025 8th International Conference on Circuit Power and Computing Technologies Iccpct 2025, 2025
MedAi: An AI-Driven Approach to Personalized Healthcare
D.S. Jayakumari, P. Venkadesh, S.V. Divya, S Hanush Viswanath, B Karthikeyaan, K Arivumathi
2025 8th International Conference on Circuit Power and Computing Technologies Iccpct 2025, 2025
Intelligent IoT based Car Parking Assistance System using Sensors and Arduino by Integrating with MobileApp
S.V.Divya, B.Selvapriya, P.Venkadesh, J. Balaji, Kaviha.R.M, Saranyadevi.M
Proceedings of the 9th International Conference on Electronics Communication and Aerospace Technology Iceca 2025, 2025
An AI Hybrid Model for Road Accident Detection based on YOLO and CNN Algorithm
P. Venkadesh, S.V. Divya, P Jayaprathap, K Deepak Kumar, R Aravindh, N Jeevanandham
2025 8th International Conference on Circuit Power and Computing Technologies Iccpct 2025, 2025
Enhanced Phishing Detection using Machine Learning, NLP and Emerging Technologies
D. Jeevitha, P. Venkadesh, S.V. Divya, J. Lingeshwaran, S. Kavinkumar, S. Hariharan
2025 8th International Conference on Circuit Power and Computing Technologies Iccpct 2025, 2025
AI-Driven Emotion-Aware Learning with Cross-Modal Fusion
R. Murugadoss, P. Venkadesh, S.V. Divya, K. Sowmithra, K. Abinaya, C. Sathya
2025 8th International Conference on Circuit Power and Computing Technologies Iccpct 2025, 2025
A Hybrid CNN-ViT and GAN (HCVGAN) Model for Cocoa Leaf Disease Prediction
S.V. Divya, P. Venkadesh, D. Saravanaprabhu, S. Roshini, G. Vasunthraa, S Saihareesh
2025 8th International Conference on Circuit Power and Computing Technologies Iccpct 2025, 2025
Enhancing Algorithm Learning Through LLM-Based Leetcode Solution Visualization
F. Theophilus, P. Venkadesh, S.V. Divya, L. Sanjay, S. Chandru, S. Praveen
2025 8th International Conference on Circuit Power and Computing Technologies Iccpct 2025, 2025
Blockchain Technology for Authentic Product Identification in the Medical and Pharmaceutical Sector Using QR code and NFT (QR-NFT)
D. Jeevitha, P. Venkadesh, G. Jaya Bharathi, N. Subhashini, G. Gowsalya, S.V. Divya
2025 8th International Conference on Circuit Power and Computing Technologies Iccpct 2025, 2025
Intelligent Dynamic Code Analysis using Large Language Models
V Murugalakshmi, P. Venkadesh, S.V. Divya, K Ageilan, K Kishore, C S Alden
2025 8th International Conference on Circuit Power and Computing Technologies Iccpct 2025, 2025
YOLOv7-Based Intelligent System for Real-Time Object Detection and Assistive Navigation in Smart Accessibility Solutions using NLP Feedback (YOLO-AI)
B. Jebaranjani, P. Venkadesh, A Abhyshek Jose, A Sakthibala, K S Dhayanidhi, S Velumani
2025 8th International Conference on Circuit Power and Computing Technologies Iccpct 2025, 2025
Unlocking AI Creativity: A Multi-Agent Approach with CrewAI
P. Venkadesh, S. V. Divya, K. Subash Kumar
Journal of Trends in Computer Science and Smart Technology, 2024
Optimized Deep Neuro-Fuzzy Network with MapReduce Architecture for Acute Lymphoblastic Leukemia Classification and Severity Analysis
G. Mercy Bai, P. Venkadesh
International Journal of Image and Graphics, 2024
Predicting natural disasters with AI and machine learning
P Venkadesh, Divya S. V., P Marymariyal, S. Keerthana
Utilizing AI and Machine Learning for Natural Disaster Management, 2024
Utilizing AI and machine learning for natural disaster management: Overview of machine learning and its importance in disaster management
Divya S. V., Venkadesh P., Yazhini S., Shiny K. V.
Utilizing AI and Machine Learning for Natural Disaster Management, 2024
Precision Agriculture and Resource Optimization Using Artificial Intelligence Techniques
Revolutionizing Sustainable Food Production with Quantum Computing, 2024
Classifying and Predicting Covid-19 during pregnancy using RNN and ML Techniques
S.V. Divya, P. Venkadesh, K.V. Shiny, S.Ninisha Nels, A. Prasanth
Proceedings 2024 International Conference on Social and Sustainable Innovations in Technology and Engineering Sasi ITE 2024, 2024
SignChatAI-Generative AI for Deaf-and-Mute Community using Indian Sign Language(ISL)
P. Venkadesh, G Jelin Taric, P Mary Mariyal, S.V. Divya, S Danumithra, K. Anuranjani
International Conference on Computing and Intelligent Reality Technologies Proceedings of Iccirt 2024, 2024
A Multi-Layer Encryption and Anomaly Detection Framework for Securing SCTP Data Transmission
P. Venkadesh, S.V. Divya, Geetha Ponnaian, T.Saju Raj, S.Ninisha Nels, K.Subash Kumar
International Conference on Computing and Intelligent Reality Technologies Proceedings of Iccirt 2024, 2024
An Integrated XGBRF Framework for Early Identification of Parkinson's Disease
S.V. Divya, P. Venkadesh, R. Joan Pavithra, Amal M.R, Lakshayaa G, Logasundari A
2nd International Conference on Emerging Research in Computational Science Icercs 2024, 2024
Classification and methods of acute lymphoblastic leukemia detection using neural network
G. Mercy Bai, P. Venkadesh, S. V. Divya
Predicting Pregnancy Complications Through Artificial Intelligence and Machine Learning, 2023
RETRACTED ARTICLE: Homomorphic Naccache–Stern Tanimoto Key Matching Cryptosystem-Based Authentication for Secure 5G Cellular Networks Communication with Iot
M. P. Haripriya, P. Venkadesh
Arabian Journal for Science and Engineering, 2023
R2NET: Storage and Analysis of Attack Behavior Patterns
M. R. Amal, P. Venkadesh
Ksii Transactions on Internet and Information Systems, 2023
H-DOCTOR: Honeypot based firewall tuning for attack prevention
M.R. Amal, P. Venkadesh
Measurement Sensors, 2023
A Novel Technique to Prevent Cross-Sensor Issues in Fingerprint Matching
H. Mohamed Khan, P. Venkadesh
Arabian Journal for Science and Engineering, 2023
Taylor political monarch butterfly optimization driven deep learning model for acute lymphoblastic leukemia detection and severity classification using blood smear images
Gnana Prakasam Mercy Bai, Venkadesh Perumal
Concurrency and Computation Practice and Experience, 2023
Hybrid H-DOC: A bait for analyzing cyber attacker behavior
Amal M. R., Venkadesh P
International Journal of Electrical and Computer Engineering Systems, 2023
Spoofing free fingerprint image enhancement
H. Mohamed Khan, P. Venkadesh
International Journal of Information Technology Singapore, 2023
Comprehensive Analysis of Deep Learning Methods for COVID-19 Detection and Classification
Bindhu Prabha, S V Divya, P Venkadesh
2023 Annual International Conference on Emerging Research Areas International Conference on Intelligent Systems Aicera Icis 2023, 2023
Increment Learning for Acute Lymphoblastic Leukemia Classification
Mercy Bai G, Venkadesh P
International Journal of Engineering Trends and Technology, 2022
Fingerprint Denoising Using Iterative Rule-Based Filter
H. Mohamed Khan, P. Venkadesh
Arabian Journal for Science and Engineering, 2022
Feature Selection Based on IoT Aware QDA Node Authentication in 5G Networks
M. P. Haripriya, P. Venkadesh
Intelligent Automation and Soft Computing, 2022
TAYLOR-MONARCH BUTTERFLY OPTIMIZATION-BASED SUPPORT VECTOR MACHINE for ACUTE LYMPHOBLASTIC LEUKEMIA CLASSIFICATION with BLOOD SMEAR MICROSCOPIC IMAGES
G. MERCY BAI, P. VENKADESH
Journal of Mechanics in Medicine and Biology, 2021
Trust aware IoT enhanced B-tree node authentication for secured 5G wireless communication
M.P. Haripriya, P. Venkadesh
International Journal of Ultra Wideband Communications and Systems, 2021
Noise removal using various filters based on PSNR & MSE in fingerprint biometrics
International Journal of Advanced Science and Technology, 2019
Investigation study on secured data communication on 5G cellular networks
Haripriya M.P., Venkadesh P
Journal of Advanced Research in Dynamical and Control Systems, 2019
A combined data storage with encryption and keyword based data retrieval using SCDS-TM model in cloud
S.V. Divya, R.S. Shaji, P. Venkadesh
Malaysian Journal of Computer Science, 2019
An efficient data storage and forwarding mechanism using fragmentation-replication and DADR protocol for enhancing the security in cloud
S. V. Divya, R. S. Shaji, P. Venkadesh
Journal of Computational and Theoretical Nanoscience, 2018
A technique for transmitting secret message using secret matrix in SCTP
P. Venkadesh, Julia Punitha Malar Dhas, S.V. Divya
International Journal of Enterprise Network Management, 2016
Techniques to enhance security in SCTP for multi-homed networks
P. Venkadesh, Julia Punitha Malar Dhas, S. V. Divya
Global Conference on Communication Technologies Gcct 2015, 2015
A comprehensive data forwarding technique under cloud with dynamic notification
S.V. Divya, R.S. Shaji, P. Venkadesh
Research Journal of Applied Sciences Engineering and Technology, 2014
A multi-level security mechanism for secure data transmission in SCTP
P. Venkadesh, Julia Punitha Malar Dhas, S.V. Divya
Research Journal of Applied Sciences Engineering and Technology, 2014
Minimum cost virtually single storage private grid using OGA
European Journal of Scientific Research, 2012

Dr.P.Venkadesh

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