Reimagining Tomorrow

AI and Sustainable Imperative
1. Auflage 2026
ISBN: 978-1-041-26850-5
Verlag: Taylor & Francis Ltd

Buch, Englisch, 252 Seiten, Format (B × H): 210 mm x 280 mm

Reihe: Taylor and Francis Proceedings in Computer Science and Engineering

Reimagining Tomorrow: AI and Sustainable Imperative presents a curated collection of high-quality research contributions that explore the transformative role of Artificial Intelligence across diverse sectors in addressing pressing sustainability challenges.

The book highlights how advanced AI techniques—ranging from machine learning and deep learning to intelligent optimization—are being leveraged to enhance efficiency, reduce environmental impact, and support data-driven decision-making. The volume emphasises the growing importance of integrating technological innovation with sustainability goals to create resilient and future-ready systems. The primary focus of this book is on human-centred Artificial Intelligence, with particular attention to its ethical, societal, and governance dimensions. It examines critical issues such as transparency, fairness, accountability, and privacy, while also showcasing AI-driven solutions for sustainable development in key domains, including healthcare, education, smart infrastructure, and Industry 5.0. The contributions further address interdisciplinary approaches, combining AI with emerging paradigms such as edge computing, IoT, and green technologies to enable scalable and responsible innovation.

The book provides valuable insights for researchers, academicians, industry practitioners, policymakers, and students by offering a comprehensive perspective on both theoretical advancements and practical implementations of AI for sustainability and serves as a reference for understanding current trends, identifying research gaps, and exploring future directions in the design of intelligent, ethical, and sustainable systems.

Zielgruppe

General, Postgraduate, and Professional Reference

Autoren/Hrsg.

Prakash, Gyan

Kaur, Amandeep

Fachgebiete

• Geowissenschaften Umweltwissenschaften Nachhaltigkeit
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen
• Wirtschaftswissenschaften Wirtschaftssektoren & Branchen Gesundheitswirtschaft
• Naturwissenschaften Agrarwissenschaften Agrarwissenschaften Nachhaltige Landwirtschaft
• Wirtschaftswissenschaften Volkswirtschaftslehre Internationale Wirtschaft Entwicklungsökonomie & Emerging Markets
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken

Inhaltsverzeichnis

Section 1: Advanced Artificial Intelligence, Machine Learning Models and Intelligent System Development. Machine Learning and Geospatial Analysis for Advanced Water Quality Forecasting and Land Use Impact Assessment. Automated Detection of Autism Spectrum Disorder in Children Via Standardized Assessment-Based Deep Learning Models and Classification Model. Empowering Credit Decisions with CatBoost: From SHAP Driven Insights to Actionable Business Rules in Loan Default Prediction. Design and Implementation of Multi-Sensor IoT Based Real-Time Mental Wellness Monitoring Using Machine Learning. Smart Fruit Quality Monitoring Using Image Processing with Deep Neural Networks. Current Developments and the Challenges in the State of AI and Machine Learning Based Landslide Susceptibility Prediction Models: An Overview. A Review of Rock Slope Stability Assessment Techniques: Analytical, Numerical and Machine Learning. Design and Development of a Voice-Controlled Personal Safety Application 9. AI Powered Medical Reporting and Clinical Dashboard 10. Named Entity Recognition for Kannada Language Using XLM-RoBERTa and IndicBERT. Deep Learning Framework for Early Detection and Region-Wise Identification of Oral Cancer in Histopathology. Multi-Agent Framework for Pediatric Pneumonia Diagnosis Integrating Vision and Language Models. A Secure Multimodel Biometric Framework for Authentication Using Finger Vein and Palm Print Fusion via Deep Learning and Feature-Level Integration. A Hierarchical 3D Convolutional Neural Network (H-3D-CNN) with FreeSurfer-Based Brain Preprocessing for AD Classification. AI-Based Smart Feedback and Complaint Management System with Sentiment Prioritization. An End-to-End Deep Learning Approach to Intelligent Steganography for Data Hiding. Efficient Feature-Based Framework for Real-Time Static Sign Language Recognition Using Classical Machine Learning. Classifying Kidney Disease from CT Scan Images Using Deep Learning: An All-Inclusive Multi-Model Ensemble Method Section 2: Applied Artificial Intelligence, Socio-Technical Systems, Healthcare Innovations and Policy Perspectives. The Intelligent Health Paradigm: Modernizing India’s Medical Regime with AI. Neurophysiological Modulation Through Indian Classical Ragas: An Integrative Study on Therapeutic Effects. AI-Based Learning Analytics for Redesigning HR Reskilling toward Decent Work (SDG 8). Human-Centric Industry 5.0 Frameworks for Sustainable Gig Work Ecosystems. Qualitative Analysis of Gaps in Indian Agri-Food Supply Chains and Their Impact on Sustainability and Industry 4.0/5.0 Goals. Artificial Intelligence in Maritime Healthcare: Diagnostic Support, Predictive Analytics, and Teleconsultation. From Application Domains to Governance Implications: A Socio-Technical Framework for AI in Marginalised and Rural Contexts. AI-Based Monitoring of Anxiety and Depression in Professional Football: Mediating Mechanisms and Governance Tensions. Enhancing Transparency and Security Through Blockchain Innovation. Natto-Derived MK-7 in Postmenopausal Bone Health: Clinical Perspectives and the Role of Artificial Intelligence

Über Autor(innen)

Gyan Prakash, PhD, is a Professor of Operations and Technology Management and Dean Planning and Development and former Head, Department of Management Studies at the ABV-Indian Institute of Information Technology and Management, Gwalior, India. Prof. Prakash was visiting Associate Professor at the Asian Institute of Technology Bangkok and visiting researcher at the Institute for Manufacturing, University of Cambridge. His research interests include the fields of supply chain management, information systems, operations and service management, including public management. He has published his research work in many prestigious journals.

Amandeep Kaur, PhD, is an Assistant Professor in the Department of Management Studies at ABV-Indian Institute of Information Technology and Management (ABV-IIITM), Gwalior, India. Prior to joining ABV-IIITM, she served as Assistant Professor at Dr. B. R. Ambedkar National Institute of Technology, Jalandhar, and the National Institute of Technology, Hamirpur. Her research interests lie at the intersection of Artificial Intelligence and Machine Learning in Healthcare, Operations Management, Quality of Service Management, Business Analytics, and Business Intelligence. She has contributed to various high-impact journals, with her work reflecting a blend of technical innovation and practical application. Dr. Kaur continues to engage in interdisciplinary research and collaborative projects that aim to enhance data-driven decision-making across domains.