Cloud Computing and AI-Driven Data Analytics

Erscheinungsjahr 2026
ISBN: 978-3-032-33629-3
Verlag: Springer

Buch, Englisch, 313 Seiten, Format (B × H): 155 mm x 235 mm

Reihe: Signals and Communication Technology

This book provides an overview of developments in cloud computing and AI-driven data analytics, highlighting how these technologies are transforming the way data is managed, processed, and utilized across diverse application domains. It explores emerging approaches, challenges, and opportunities in building intelligent, scalable, and secure digital systems. 

Bringing together contributions from researchers and practitioners, the book covers both foundational concepts and advanced applications, offering insights into modern data-driven technologies and their role in addressing real-world problems. Topics discussed include cloud-based services, machine learning, cybersecurity, privacy, distributed computing, and intelligent decision-support systems. The book also examines the integration of cloud and AI technologies with other emerging paradigms to address evolving technological and societal needs. It serves as a valuable resource for students, researchers, and professionals interested in the evolving intersection of cloud computing, artificial intelligence, and data analytics. 

Zielgruppe

Research

Autoren/Hrsg.

Jameel, Roshan

Idrees, Sheikh Mohammad

Khan, Akif Quddus

Sikri, Alisha

Fachgebiete

• Mathematik | Informatik EDV | Informatik Daten / Datenbanken
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
• Technische Wissenschaften Elektronik | Nachrichtentechnik Nachrichten- und Kommunikationstechnik

Inhaltsverzeichnis

Introduction.- Introduction to Cloud Computing and AI-Driven Analytics.- Data Management in the Cloud: Architectures and Frameworks.- Machine Learning in the Cloud Ecosystem.- Big Data Analytics in Cloud Environments.- Edge and Fog Computing: Extending the Cloud for Intelligent Analytics.- AI-Powered Cloud Automation and Orchestration.- Deep Learning at Scale: Cloud Infrastructure for Neural Networks.- Data Security, Privacy, and Trust in AI-Driven Clouds.- Explainable and Ethical AI in Cloud Data Systems.- AI-Driven Cloud Monitoring and Predictive Maintenance.- Cloud and AI Integration in Healthcare Analytics.- Healthcare Applications of Cloud and AI Analytics.- Intelligent Cloud Solutions for Smart Cities and IoT.- AI and Cloud Synergy in Financial and Business Intelligence.- Sustainability and Green AI in Cloud Computing.- Future Directions: Quantum Cloud, Federated AI, and Beyond.- Conclusion.

Über Autor(innen)

Roshan Jameel is a researcher and academic specializing in the intersection of emerging technologies and sustainability, with expertise in blockchain, machine learning, and healthcare applications. Her work focuses on integrating advanced computational techniques to develop practical, data-driven solutions that address real-world challenges while advancing interdisciplinary knowledge. Roshan is passionate about fostering research-oriented learning and mentorship, guiding students and early-career researchers in applying innovative technologies ethically and effectively. Her interdisciplinary approach bridges technology, sustainability, and social impact, reflecting her commitment to driving meaningful change through research and innovation. 

Sheikh Mohammad Idrees is a researcher, educator, and technologist with a deep interest in how decentralized systems and data-driven intelligence can shape the future of technology. He holds a Ph.D. in computer science and has worked across academia and industry, exploring ways to make blockchain systems more scalable, interoperable, and trustworthy. His work often brings together blockchain and machine learning to build smarter and more reliable digital ecosystems. As a certified enterprise blockchain architect, Idrees enjoys bridging theory and practice—mentoring students, collaborating with international teams, and helping ideas grow into real-world innovations. He currently works as a researcher and lecturer at NTNU in Gjøvik, Norway, where he continues to inspire curiosity and collaboration in emerging technologies. 

Akif Quddus Khan is an academician and researcher currently affiliated with Oslo Metropolitan University (OsloMet), Faculty of Technology, Art and Design, Department of Computer Science, within the Technology and Innovation in Organization and Society (TIOS) research group. Previously, he served as a doctoral researcher at the Norwegian University of Science and Technology (NTNU), Gjøvik, where he completed his Ph.D. focusing on cost modeling and optimization in cloud infrastructures.
Akif’s research spans cloud economics, FinOps strategies, storage optimization, resource allocation, and scalable data processing. He has actively contributed to academic and professional communities through conference presentations, research collaborations, and invited talks on cloud cost management and sustainable computing practices. His current research continues to explore intelligent workload management and cost-efficient architectures for cloud-native environments, bridging academic research with real-world FinOps and industry needs.

Alisha Sikri is a faculty member at the Vivekananda Institute of Engineering and Technology, Technical Campus, with over ten years of teaching and research experience in machine learning and artificial intelligence (AI). Her research focuses on developing intelligent computational models that enhance automation, prediction, and data-driven decision-making across interdisciplinary domains such as healthcare analytics, natural language processing, and smart systems. Alisha has published several papers in reputed national and international journals and holds multiple patents, reflecting her commitment to transforming theoretical concepts into practical innovations. Her work integrates AI techniques with emerging technologies to address complex real-world challenges. As a passionate educator and mentor, she emphasizes research-oriented learning and hands-on experimentation, nurturing the next generation of AI professionals.