Information Systems Engineering and Management

This book showcases an endeavor to delve into the fusion of artificial intelligence (AI) and the Internet of Things (IoT) within the healthcare domain.

The healthcare sector is currently experiencing a shift fueled by technological advancements and a heightened focus on providing tailored, efficient and impactful care to individuals. AI and IoT have emerged as facilitators of this evolution presenting opportunities to elevate patient results streamline operations and enhance decision-making within healthcare environments.

This publication unites an array of viewpoints from experts in healthcare, technology and research domains. Through an array of enlightening chapters readers will embark on a journey exploring the applications, hurdles and consequences of merging AI with IoT in healthcare contexts. From analytics and remote monitoring to treatment suggestions and operational enhancements the potentials offered by AI and IoT is both captivating and revolutionary.

As editors overseeing this volume’s creation we take pride in presenting an assemblage of contributions that mirror the research findings, innovations and optimal practices in healthcare technology.

Our aim is to encourage readers to engage in thinking, creativity and teamwork when considering the impact of integrating AI with IoT on enhancing patient care and healthcare services.

This book simplifies complex AI and ML concepts, making them accessible to security analysts, IT professionals, researchers, and decision-makers. Cyber threats have become increasingly sophisticated in the ever-evolving digital landscape, making traditional security measures insufficient to combat modern attacks. Artificial intelligence (AI) and machine learning (ML) have emerged as transformative tools in cybersecurity, enabling organizations to detect, prevent, and respond to threats with greater efficiency. This book is a comprehensive guide, bridging the gap between cybersecurity and AI/ML by offering clear, practical insights into their role in threat intelligence. Readers will gain a solid foundation in key AI and ML principles, including supervised and unsupervised learning, deep learning, and natural language processing (NLP) while exploring real-world applications such as intrusion detection, malware analysis, and fraud prevention. Through hands-on insights, case studies, and implementation strategies, it provides actionable knowledge for integrating AI-driven threat intelligence into security operations. Additionally, it examines emerging trends, ethical considerations, and the evolving role of AI in cybersecurity. Unlike overly technical manuals, this book balances theoretical concepts with practical applications, breaking down complex algorithms into actionable insights. Whether a seasoned professional or a beginner, readers will find this book an essential roadmap to navigating the future of cybersecurity in an AI-driven world. This book empowers its audience to stay ahead of cyber adversaries and embrace the next generation of intelligent threat detection.

This book explores the current state and future trajectories of digital transformation for sustainability in the VUCA era, offering far-reaching insights for researchers, practitioners and policymakers. It serves as a robust academic supplement for advanced programs in information systems, business, management, and supply chain. It also guides readers through the market research process—from formulating questions to data collection and analysis—employing diverse methods such as case studies, qualitative, quantitative, and systematic literature reviews, with method-specific rationales to enhance practical understanding.