Applied Data Science and Smart Systems

1. Auflage 2026
ISBN: 978-1-041-46309-2
Verlag: Taylor & Francis Ltd

Buch, Englisch, 486 Seiten, Format (B × H): 210 mm x 280 mm

Reihe: Taylor and Francis Proceedings in Computer Science and Engineering

This volume presents the peer-reviewed proceedings of the International Conference on Applied Data Science and Smart Systems (ADSSS-2025), bringing together pioneering research that reflects the rapid advancements in data science, artificial intelligence, and intelligent computing.

The book showcases innovative contributions from researchers, academicians, and industry experts who address contemporary challenges through data-driven methodologies, smart computing, automation, and emerging digital technologies. Covering applications in healthcare, smart cities, manufacturing, finance, education, and other critical sectors, the chapters bridge the gap between theoretical foundations and practical implementations. Emphasising interdisciplinary collaboration, the proceedings explore novel algorithms, intelligent architectures, edge intelligence, deep learning, smart sensing, secure data communication, and applied mathematics. By presenting cutting-edge research alongside real-world applications, this volume captures the evolving landscape of intelligent systems and serves as a valuable record of the ideas, innovations, and collaborative efforts that are shaping the future of applied data science and smart technologies. It highlights significant advances in machine learning, deep learning, artificial intelligence, edge intelligence, smart sensing, software engineering, computer graphics, multimedia, secure data communication, and intelligent automation.

This book is an essential reference for researchers, academicians, postgraduate students, industry professionals, technology practitioners, and policymakers working in applied data science, artificial intelligence, smart systems, and allied disciplines. It will also benefit innovators and interdisciplinary research communities seeking current developments, practical insights, and future research directions in intelligent computing.

Zielgruppe

Academic, General, and Undergraduate Core

Autoren/Hrsg.

Singh, Jaiteg

Kaushal, Rajesh Kumar

Sehra, Sukhjit Singh

Fachgebiete

• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Datenbankdesign & Datenbanktheorie
• Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Algorithmen & Datenstrukturen
• Mathematik | Informatik EDV | Informatik Informatik Mensch-Maschine-Interaktion Informationsarchitektur
• Mathematik | Informatik EDV | Informatik Technische Informatik Quantencomputer, DNA-Computing
• Naturwissenschaften Physik Physik Allgemein Theoretische Physik, Mathematische Physik, Computerphysik
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Wissensbasierte Systeme, Expertensysteme
• Naturwissenschaften Physik Quantenphysik
• Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Software Engineering
• Technische Wissenschaften Technik Allgemein Mess- und Automatisierungstechnik

Inhaltsverzeichnis

AI-Powered Personalized Health Monitoring and Remedial System using Machine Learning. AI Based Model to Enable Personalized Learning Environment. Migrating Indian Railways System to AWS: A Comprehensive Analysis. Unified Machine Learning Approach for Enhanced Detection of Cerebral Hemorrhagic Events. A Study of Heterogeneous Servers with Priority Queues. Transfer learning-based Object Detection using Convolutional Neural Networks. Segmentation Techniques in Smart Agriculture for Maize Leaf Disease detection. A Calibrated Ensemble Classifier for Skin Cancer Detection using Transfer Learning and Heuristic Tabu Search Feature Selection. Dynamic Emotion-Driven Speech Synthesis: Bridging Realism and Expressiveness. Studying the Influence of AI-Powered Customer Service on Entrepreneurial Performance and Effectiveness. Measuring Student Engagement in the Higher Education Online Program. Mudra Loan and its Effectiveness: Assessing Transformation Needs. The Digital Ledger of Trust: Blockchain for Authentic Vaccine Supply Chains. Fault Tolerant IoT enabled Solar Streetlight Illumination Efficiency System. Analyzing Queuing Model Numerically: Reverse Balking and Holding Impatient Customers in Transient Conditions. A Federated Learning and GAN-Based Framework for Addressing Data Imbalance and Privacy Challenges in Medical Imaging. Speakofy: A Bidirectional Sign Language Interpreter. Advancing Business Analytics Through Deep Learning Driven Predictive Frameworks for Enhanced Sales Productivity Forecasting. A Systematic Review of Various Attack Types and Detection Techniques on Ethereum Blockchain Layers. A novel and innovative artificial intelligence framework for bird call preparation, classification, and transformation using hybrid CNN–BiLSTM architecture with mean opinion score evaluation. XMAFusion: Cross-Modal Attention Fusion for Enhanced Multimodal Sentiment Understanding. Signature Fraud Detection using combined CNN and SIFT. Image Dehazing with ResUNet++ and Multi-Metric Evaluation in Semi-Supervised Setting. A Machine Learning Based Approach for Detection of Alzheimer's Disease Using Analysis of Hippocampus Region from MRI Scan. Machine Learning Based Drug Recommendation Systems. Quantum-Enhanced Blockchain Frameworks for Next-Generation Financial Systems and Human Capital Optimization. Synergizing Quantum Computing and Blockchain for Secure Talent Management and Predictive Financial Intelligence. Anemia Disease Classification Based on Machine Learning Models and Data Augmentation. A Mixed Attention Mechanism Model Based on Resnet50 for Tomato Leaf Disease Recognition. Reinforcement Learning-Driven Digital Twins: Adaptive Simulation and Control for Next-Generation Smart Manufacturing. Enhanced Financial Forecasting through Regime-Aware Multi-Scale Neural Networks with Dual-Task Learning. Fake News Detection in Low-Resource Indian Languages: A Survey of Multilingual and Multimodal Approaches. AI-Based Multilingual Scam Detection: A Comparative Study of Sentence Transformer Models. Evolutionary Trajectories in Large Language Models: From Transformers to Reasoning-Augmented Systems. Ensemble Machine Learning Based Intrusion Detection Framework for Cyber Physical Systems. A Practical Framework for Robust SMS Spam Detection Using a Hybrid Feature Ensemble Model. Smart Floors that Predict and Power: Piezo-Footfall Harvesting Energy with Piezotiles and LSTM. Decentralized Quantum-Blockchain Ecosystems for Trustworthy Financial Governance and Intelligent Human Resource Management. Metaverse-Driven HR and Finance with Blockchain, AI, and Quantum Computing. Real-Time Quantum Key Distribution Protocol for Secure Blockchain Communication in Critical Infrastructure. Edge-AI and Quantum-Blockchain for Smart HR and Sustainable Finance. Quantum-Safe Blockchain Architecture Using Multivariate Signature Schemes: Design, Implementation, and Benchmarking. Quantum Entanglement-Driven Consensus: A Novel Paradigm for Ultra-Fast and Secure Blockchain Protocols. A Post-Quantum Blockchain Framework Using Lattice-Based Cryptography for Securing Decentralized Financial Systems. The Moderating Role of AI Chatbot Integration in Green Food E-Commerce: How Price Fairness and Emotional Value Influence Customer Satisfaction. Evolving Paradigms in Spectrum Sensing: From Conventional to Intelligent Cognitive Radio Networks. Efficient Task Offloading in Mobile Edge Computing: Optimization Strategies and Emerging Frameworks. Hybrid Deep Learning Framework for Enhanced DDoS Detection in SDN-IoT Environments Using NMRA-Optimized Neural Networks. AI-Based YouTube Video Summarization & Short Video Generator. Predictive Analysis of Stock Market Using Long Short-Term Memory Networks: A Comparative Study. Exploring the Evolution of Software Fault Prediction Using Soft Computing Techniques. Lifestyle-Centric Reproductive Health Prediction Using Ensemble Machine Learning.

Über Autor(innen)

Jaiteg Singh is an accomplished academician with 22 years of experience in research, development, and teaching in computer science and engineering. He possesses expertise in diverse fields like Neuromarketing, Navigation Systems, Software Engineering, Business Intelligence, and Data Mining. He has supervised eighteen Ph.D. thesis and eighteen M.Tech thesis. He has generated significant consultancy revenue, organized international conferences, and published extensively in renowned journals indexed in reputed databases like Scopus and Web of Science. He has authored/edited six books, secured four US copyrights, and filed over 50 patents. He is serving as a reviewer for numerous journals from reputed publishers.

Rajesh Kumar Kaushal is a highly accomplished and dedicated researcher and educator, boasting a robust background in Computer Science and Engineering, and accumulating 20 years of extensive experience in academia since 2004. Holding a Ph.D. in Computer Science and Engineering from Chitkara University, Punjab, India. He currently serves as a professor in the Department of Computer Applications, Chitkara University and actively contributes to research endeavours. Dr. Kaushal's prolific research output is evident through his involvement in more than 100 patent filings, one of them being published in the World Intellectual Property Organization (WIPO) and 40 being granted. Additionally, he has taken on the role of Project Manager in a DST-funded project titled "Smart and Portable Intensive Care Unit," supported by the Millennium Alliance (FICCI, USAID, UKAID, Facebook, World Bank, and TDB DST). Furthermore, he served as a Co-Principal Investigator in another DST-funded project named "Remote Vital Information and Surveillance System for Elderly and Disabled Persons," under the Technology Intervention of Disabled and Elderly (TIDE) scheme of the Ministry of Science & Technology, Government of India. Presently he is working on another DST funded project named “Smart Ergonomic Portable Commode Chair” under the DST TIDE scheme.

Sukhjit Singh Sehra is currently working as an Assistant Professor at Wilfrid Laurier University, Waterloo, Canada. A proactive academician with extensive experience teaching undergraduate and graduate courses in Machine Learning, Artificial Intelligence, Natural Language Processing, Spatial Data Science, and Big Data. He possesses strong analytical skills and provides expertise in large-scale spatial and unstructured textual datasets. He has supervised 19 master’s theses and published over 80 peer-reviewed articles in journals and conferences. He possesses 18+ years of experience in research, academia, and industry. He worked at prestigious organizations in India and Canada like Guru Nanak Dev Engineering College, Ludhiana, Punjab, India, and Canada Centre for Mapping and Earth Observation, Natural Resources Canada. He is actively involved in the usability and application of technology to solve social problems. He is the Co-Founder and Director at Sabudh Foundation, India, a data science organization for social initiatives (http://sabudh.org) to develop an incubation center of Artificial Intelligence and Machine Learning for the youth of India.