This book focuses on the key technologies, challenges, and research directions of the Industrial Internet of Things (IIoT). It provides a basis for discussing open principles, methods, and research problems, and provides a systematic overview of the state-of-the-art research efforts, directions, and potential challenges associated with IIoT.
Industrial Internet of Things: Technologies and Research Directions covers how industry automation is projected to be the largest and fastest-growing segment of the market. It explores the collaborative development of high-performance telecommunications, military, industrial, and general-purpose embedded computing applications, and offers a systematic overview of the state-of-the-art research efforts and new potential directions.
Researchers, academicians, and professionals working in this inter-disciplinary area will be interested in this book.
Author(s): Anand Sharma, Sunil Kumar Jangir, Manish Kumar, Dilip Kumar Choubey, Tarun Shrivastava, S. Balamurugan
Series: Advances in IoT, Robotics, and Cyber Physical Systems for Industrial Transformation
Edition: 1
Publisher: CRC Press
Year: 2022
Language: English
Pages: 294
City: Boca Raton
Cover
Half Title
Series Page
Title Page
Copyright Page
Contents
Preface
About the Authors
Contributors
Chapter 1: Artificial Intelligence and Machine Learning for the Industrial Internet of Things (IIoT)
Chapter 2: Role of Internet of Things (IoT) in Electronic Waste Management
Chapter 3: Creating a Reliable IIoT Framework to Prioritize Workplace Safety in Industries Involving Hazardous Processes
Chapter 4: Parkinson Disease Prediction and Drug Personalization Using Machine Learning Techniques
Chapter 5: IoT and Deep Learning-Based Prophecy of COVID-19
Chapter 6: Machine Learning Applications and Challenges to Protect Privacy in the Internet of Things
Chapter 7: IoT-Enabled Heart Disease Prediction Using Machine Learning
Chapter 8: Internet of Everything, the Future of Globalization:
A Comprehensive Study
Chapter 9: A Review of Human–Robot Interaction for Automated Guided Vehicles Using Robot Operating Systems
Chapter 10: Analysis of Cascading Behavior in Social Networks and IoT
Chapter 11: Performance Evaluation of Machine Learning Classifiers for Memory Assessment Using EEG Signal
Chapter 12: Robotic Operating System and Human–Robot Interaction for Automated Guided Vehicles (AGVs): An Application of Internet of Things in Industries
Chapter 13: A Review on IoT Architectures, Protocols, Security,
and Applications
Chapter 14: Performance Analysis of Distributed Mobility Protocol
for Multi-Hop IoT Networks
Chapter 15: Comparative Analysis of Emotional State Classification
Using Different Machine Learning Techniques
Chapter 16: A Survey on Antennas for IIoT Application
Index
