Advances in Intelligent Computing and Communication Technology

1. Auflage 2026
ISBN: 978-1-041-33408-8
Verlag: Taylor & Francis

Buch, Englisch, 290 Seiten, Format (B × H): 210 mm x 280 mm

Reihe: Conference Proceedings Series on Futuristic Intelligent and Smart Technologies

This book discusses innovative ideas and cutting-edge research in intelligent computing and communication technologies.

The book covers a broad spectrum of emerging areas, including Artificial Intelligence, Machine Learning, Data Science, Intelligent Systems, Communication Technologies, Computer Science and Engineering, Information Technology, and other interdisciplinary engineering domains. Each contribution reflects rigorous peer review and emphasizes both theoretical advancements and real-world applications. Designed as a valuable multidisciplinary reference, this book bridges the gap between academia and industry by offering practical insights, real-time problem-solving approaches, and future research directions.

It will be an essential resource for researchers, educators, practitioners, and postgraduate students seeking to stay abreast of recent developments and innovations in engineering and technology.

Zielgruppe

Academic and Undergraduate Core

Autoren/Hrsg.

Kumar, Sanjeev

Shukla, Prashant

Banerjee, Jyoti Sekhar

Bhattacharyya, Siddhartha

Sarigiannidis, Panagiotis

Platos, Jan

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Neuronale Netzwerke
• Mathematik | Informatik EDV | Informatik Technische Informatik Quantencomputer, DNA-Computing
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Spracherkennung, Sprachverarbeitung
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen
• Mathematik | Informatik EDV | Informatik Informatik Mensch-Maschine-Interaktion Ambient Intelligence, RFID, Internet der Dinge

Inhaltsverzeichnis

1. VTRWC-Net: An Intelligent Pharmaceutical and Biomedical Residual Waste Management Framework - Integrating Vision Transformer with Recommendation System 2. Innovations, Interdisciplinary Challenges and Future Directions in Harnessing AI for Criminal Justice System 3. Satellite-Based Anomaly Detection for Agricultural Monitoring Using Autoencoder 4. Support Vector Machine-Based Land Cover Classification Using Fused Hyperspectral and LiDAR Data  5. Anomaly Detection in Cloud Storage: A Systematic Survey of Models, Datasets, and Metrics for DDoS Precursor and Insider Threat Identification 6. Smart Computational Framework for Hand Gesture Recognition Using MediaPipe in Therapeutic and Training Applications 7. Adaptive edge offloading framework for efficient congestion management in mMTC systems 8. Harmonizing Human and Machine: A Verification Loop for Enterprise Safety Systems 9. Value-Weighted Graph Embeddings: A Hybrid Framework for High-Precision Ethereum Phishing Detection 10. Attention-Enhanced ResNet for Fire, Smoke, and Normal Image Multi-Class Classification 11. An Explainable Voting Ensemble Framework for Robust Diabetes Prediction Using SHAP and LIME-Based Interpretability 12. Designing Scalable and Resilient Software Architectures for Juice Production in the Age of Industry 4.0 13. Artificial Intelligence Trends for Automatically Identifying Hate Speech on Social Media Networks 14. Machine Learning-Based Prediction of Typhoid Incidence Using Clinical and Environmental Characteristics 15. Explainable AI in Diabetic Retinopathy Diagnosis: CNN-Based Detection with Gradient-Weighted Class Activation Mapping 16. A Novel Framework for LGB Model-Based Approach for Malware Detection By Analyzing the Ember Dataset 17. Multi–Omics Integration in Leukemia Detection Using Multimodal Deep Learning Architectures 18. Unsupervised Deep Learning for Granular Strategic Insight: The Autoencoder Approach 19. Yolov8 Detection of Deviant Behavior in the Crowded Campus 20. AI-Powered Regression Approaches for Early Prediction of Blood Glucose and Blood Pressure 21. Explainable Prognostic Modelling for Glioma Using Interpretable Machine Learning Techniques 22. Automating Precision Agriculture with Deep Learning and Image Analysis 23. Hybrid Feature Selection Using Nature-Inspired Algorithms for Accurate Lower Back Pain Diagnosis 24. Comparative Study of Chatbots for College Campus Applications: Evaluating Knowledge Base Quality and Platform Performance 25. Multi-Class Anomaly Detection in Network Traffic Using Supervised Learning 26. Machine Learning-Driven Personalization in E-commerce: Enhancing Recommendation Systems for Optimal User Engagement 27. Predictive Analysis of Cardiovascular Disease — A Future Direction 28. Comparative Analysis And Implementation Of Malware Detection In Android Using Machine Learning 29. Student Grade Prediction Using Moth-Flame Optimization and Machine Learning 30. Exploring Instance Segmentation and Defect Detection Across Varied Textured Surfaces: A Comprehensive Study 31. Gan-Driven Data Augmentation For Enhanced Diabetic Retinopathy Classification Using Deep Learning Frameworks 32. Use of AIoT Approaches in Precision Agriculture 33. Minimising Outage Probability in MIMO-UWOC Systems using Alternating Metaheuristic Power Allocation 34. Intelligent Stroke Risk Assessment System 35. Evaluating the Influence of Intelligent Personalization on Consumer Buying Patterns in Digital Commerce 36. A Stacked Learning Approach to Intrusion Detection for Robust Network Protection 37. A Scalable RPA-Enabled Incremental Learning Framework for Course-Specific Student Performance Prediction 38. Transformer-Multi Model-Guided Generative Adversarial Network For Face Occlusion Removal 39. Comparative Study of Diffusion Models and GANs for Synthetic Retinal Image Generation 40. Role of Healthcare 5.0 in Society 5.0 41. Adaptive edge offloading framework for efficient congestion management in mMTC systems 42. Impact of online credible review and customer purchase intention: A case study of Cambodia 43. Improved Spam Identification using a Hybrid Neural-Fuzzy-Wrapper Architecture with Statistical Superiority and Programmatic Noise Alleviation 44. UniBlend: A Hybrid Machine Learning Ensemble for Accurate and Robust Breast Cancer Diagnosis 45. GreenEdge: Leveraging Edge-Enabled Big Data Pipelines and Cloud Orchestration for Real-Time Environmental MonitoringDeep Learning: Sustainable Model Design through

Über Autor(innen)

Dr. Sanjeev Kumar received his Master’s degree in Software Engineering from MNNIT Allahabad in 2015 and earned his Ph.D. from the same institute in 2020. With nearly 12 years of professional experience, he is currently serving as an Associate Professor in the Department of Computer Science at United University, Prayagraj. He has published around 15 research articles in reputed Scopus-indexed international journals, more than 10 book chapters, and 12 papers in conference proceedings. He has supervised four Ph.D. scholars who are currently pursuing their research, and he has guided 30 MCA major project theses. He serves as a reviewer for several reputed international journals. Dr. Kumar’s primary research interests include Artificial Intelligence, Machine Learning, and Deep Learning. His academic work focuses on developing intelligent, data-driven computational models with real-world applications in smart systems, automation, and predictive analytics. He is committed to fostering innovation, promoting quality research, and nurturing the next generation of professionals in the field of computer science.

Dr. Prashant Shukla is an Associate Professor and Head of the Department in the Department of Computer Science and Engineering at United University, Prayagraj, India. He received his M.Tech. and Ph.D. degrees from the prestigious Indian Institute of Information Technology (IIIT) Allahabad. He is also an active member of the IEEE. Dr. Shukla has been extensively involved in teaching, research, and departmental leadership for several years. His research interests span across Deep Learning, Machine Learning, Natural Language Processing, Artificial Intelligence, and emerging computational technologies. He has contributed to academic growth by guiding students, participating in collaborative research, and promoting modern pedagogical practices. As the Head of the Department, he has played a key role in strengthening academic quality, introducing technology-driven learning practices, and fostering a research-oriented environment within the department. Dr. Shukla continues to work toward advancing knowledge, innovation, and excellence in the field of computer science.

Dr. Jyoti Sekhar Banerjee is currently serving as the Associate Professor & Head of the Department in the Computer Science and Engineering (AI & ML) Department at the Bengal Institute of Technology, Kolkata, India. He is also the Professor-in-Charge, R & D and Consultancy Cell & Nodal Officer of the IPR Cell of BIT. Since 2024, he also works as a Remote Researcher in the Internet of THings & AppliCAtions Lab (ITHACA) at the Department of Electrical and Computer Engineering, University of Western Macedonia, Greece. Dr. Banerjee is also working as the Adjunct Research Faculty under the Lincoln Global Postdoctoral Researcher (LGPR) Programme at Lincoln University College, Malaysia. He is the former Remote Research Fellow of the Cognitive Computing and Brain Informatics Research Group (CCBI) at Nottingham Trent University (NTU), UK. Dr. Banerjee did his Post-Doctoral Fellowship at Nottingham Trent University, UK, in the Department of Computer Science. He also completed the Post Graduate Diploma in IPR & TBM from MAKAUT, WB. He has teaching and research experience spanning 21 years and completed one IEI funded project. He is the present Secretary-cum-Treasurer of the ISTE WB Section and Secretary of the IETE, Kolkata Centre. He is the Immediate Past Secretary of the Computer Society of India, Kolkata Chapter. Dr. Banerjee is also elected as the Vice Chairman Cum Chairman Elect in Computer Society of India, Kolkata Chapter for the year 2025-2027.

Dr. Siddhartha Bhattacharyya [FIET(UK), FIEI, FIETE, LFOSI, FSCRS, SMIEEE, SMACM, SMAAIA, SMIETI, LMCSI, LMISTE] is currently serving as a Senior Researcher in the Faculty of Electrical Engineering and Computer Science of VSB Technical University of Ostrava, Czech Republic. He also serves as the Scientific Advisor of Algebra University College, Zagreb, Croatia. Before this, he served as the Principal of Rajnagar Mahavidyalaya, Rajnagar, Birbhum. He served as a Professor in the Department of Computer Science and Engineering of Christ University, Bangalore. He was the Principal of RCC Institute of Information Technology, Kolkata, India. He has also served as a Senior Research Scientist in the Faculty of Electrical Engineering and Computer Science of VSB Technical University of Ostrava, Czech Republic. He is the recipient of several coveted awards, including the Distinguished HoD Award and Distinguished Professor Award conferred by the Computer Society of India, Mumbai Chapter, India, in 2017, the Honorary Doctorate Award (D. Litt.) from The University of South America, and the South East Asian Regional Computing Confederation (SEARCC) International Digital Award ICT Educator of the Year in 2017. He was an ACM Distinguished Speaker for 2018–2020. He was inducted into the People of ACM Hall of Fame by ACM, USA, in 2020. He was the IEEE Computer Society Distinguished Visitor for 2021–2023. He is a full foreign member of the Russian Academy of Natural Sciences (RANS) and the Russian Academy of Engineering (REA). He is a full fellow of The Royal Society for the Arts, Manufacturers and Commerce (RSA), London, UK. He is a co-author of 7 books and the co-editor of 114 books and has more than 400 research publications in international journals and conference proceedings to his credit.

Dr. Panagiotis Sarigiannidis is the Director of the ITHACA lab, co-founder of the 1st spin-off of the University of Western Macedonia: MetaMind Innovations P.C., and Full Professor in the Department of Electrical and Computer Engineering in the University of Western Macedonia, Kozani, Greece. He received the B.Sc. and Ph.D. degrees in computer science from the Aristotle University of Thessaloniki, Thessaloniki, Greece, in 2001 and 2007, respectively. He has published over 360 papers in international journals, conferences and book chapters. He received six best paper awards and the IEEE SMC TCHS Research and Innovation Award 2023. He has been involved in several national, European and international projects, coordinating and technically leading numerous national and European projects including H2020, Horizon Europe, Erasmus+ and operational programs. His research interests include telecommunication networks, internet of things and network security. He is an IEEE member and participates in the Editorial Boards of various journals.

Dr. Jan Platoš is a professor at the Department of Computer Science and the Dean of the Faculty of Electrical Engineering and Computer Science, VSB-TUO, Czech Republic. He has co-authored more than 240 scientific articles published in proceedings and journals. His primary fields of interest are machine learning, artificial intelligence, industrial data processing, text processing, data compression, bioinspired algorithms, information retrieval, data mining, data structures, and data prediction.