Deep Learning for Internet of Things Infrastructure

This book explores the design and investigation of deep learning-based data analytics of IoT infrastructures, addressing emerging trends and challenges in various application domains. It provides fundamental theory, models, and methodologies for interpreting, aggregating, processing, and analyzing data for intelligent DL-enabled IoT.

Format: Hardback
Length: 248 pages
Publication date: 30 September 2021
Publisher: Taylor & Francis Ltd

This comprehensive book delves into the realm of deep learning (DL) and its application in the field of data analytics for Internet of Things (IoT) infrastructures. It serves as a valuable resource for researchers, practitioners, and professionals seeking to explore the latest trends and advancements in this rapidly evolving domain.

The book promotes and facilitates the exchange of research knowledge and findings across diverse disciplines, focusing on the design and investigation of DL-based data analytics for IoT infrastructures. It addresses emerging trends and issues in IoT systems and services across various application domains, providing a comprehensive understanding of the challenges and opportunities associated with implementing deep learning on IoT networking models and services.

In its exploration, the book delves into the fundamental theory, models, and methodologies employed in interpreting, aggregating, processing, and analyzing data for intelligent DL-enabled IoT. It sheds light on the latest advancements in deep learning algorithms, neural networks, and machine learning techniques, enabling readers to gain a deep understanding of the underlying principles and practical applications of these technologies.

Furthermore, the book explores new functions and technologies that are emerging to provide adaptive services and intelligent applications for different end users. It discusses the role of DL in enabling real-time monitoring, predictive maintenance, and autonomous decision-making in IoT ecosystems, highlighting the potential benefits and limitations of these applications.

The authors of this book are highly respected experts in their respective fields. Uttam Ghosh holds an Assistant Professor position in the Department of Electrical Engineering and Computer Science at Vanderbilt University, Nashville, Tennessee, USA. Mamoun Alazab serves as an Associate Professor in the College of Engineering, IT, and Environment at Charles Darwin University, Australia. Ali Kashif Bashir is a Visiting Assistant Professor in the Department of Computer Science at the University of California, Davis, USA.

Their collective expertise and experience make this book an invaluable resource for anyone interested in advancing their knowledge and understanding of deep learning and its application in IoT infrastructures. Whether you are a researcher, practitioner, or industry professional, this book will provide you with the insights and tools necessary to thrive in this rapidly evolving field.

Weight: 550g
Dimension: 158 x 363 x 21 (mm)
ISBN-13: 9780367457334