ABSTRACT

This book comprehensively discusses the role of cloud computing in artificial intelligence‑based data‑driven systems and hybrid cloud computing for large data‑driven applications. It further explores new approaches, paradigms, and frameworks to meet societal challenges by providing solutions for critical insights into data. The text provides Internet of Things‑based frameworks and advanced computing techniques to deal with online/virtual systems.

This book:

• Covers the aspects of security, authentication, and prediction for data‑driven systems in heterogeneous environments.

• Provides data‑driven frameworks in combination with the Internet of Things, artificial intelligence, and computing to provide critical insights and decision‑making for real‑time problems.

• Showcases deep learning‑based computer vision algorithms for enhanced pattern detection in different domains based on data‑centric approaches.

• Examines the role of the Internet of Things and machine learning algorithms for data‑driven systems.

• Highlights the applications of data‑driven systems and cloud computing in enhancing network performance.

This book is primarily written for senior undergraduates, graduate students, and academic researchers in diverse fields including electrical engineering, electronics and communications engineering, and computer science engineering.

chapter Chapter 1|15 pages

Artificial intelligence and IoT

Challenges and future directions for data-driven system

chapter Chapter 2|19 pages

Cloud computing in AI-based data-driven systems

Opportunities and challenges

chapter Chapter 10|37 pages

Connected healthcare—the impact of Internet of Things on medical services

Merits, limitations, future insights, case studies, and open research questions

chapter Chapter 13|19 pages

Crowd-sourced-based emergency response on the Internet of Vehicles (IOV)

Harnessing strengths and limitations