Transforming Industries

Capturing the Potential of IIoT and ML in the Era of Industry 5.0

Ashima Kalra, Sita Rani, Ravinder Kumar, Ahmed A. Elngar

• Publisher: CRC Press
• Year: 2025
• eBook ISBN: 9781040431580
• Topic: Design
• Subtopic: Industrial Engineering

The rapid convergence of the industrial internet of things (IIoT) and machine learning (ML) is propelling us into a new era known as Industry 5.0. This era is defined by unparalleled levels of automation, customization, and sustainability. Despite these advancements, there is a noticeable absence of comprehensive resources that offer a complete understanding of these transformative technologies and their practical applications across various industrial sectors. Transforing Industries: Capturing the Potential of IIoT and ML in the Era of Industry 5.0 aims to fill the void by providing a timely and relevant guide that explores the theoretical foundations of the technologies while also presenting real-world case studies and best practices.

This comprehensive text discusses the profound impact of the IIoT and ML on various sectors, including manufacturing, supply chain management, and energy production. It provides a thorough examination of the opportunities and obstacles associated with these cutting-edge technologies. Through real-world case studies and success stories, readers gain insight into how industry leaders have successfully leveraged IIoT and ML solutions to optimize operational efficiency, foster innovation, and achieve unparalleled excellence. Practical strategies and detailed guidelines are also offered to facilitate the seamless integration of these technologies into existing workflows, empowering businesses to navigate the complexities of digital transformation with confidence. The focus of this publication also extends to future trends and potential disruptors in the era of Industry 5.0, equipping readers with the knowledge needed to anticipate and adapt to emerging challenges. Furthermore, the exploration of how IIoT and ML can streamline resource allocation, minimize waste, and promote sustainable practices underscores the alignment of technological advancements with corporate, environmental, and social responsibilities.

By equipping industry leaders, professionals, and entrepreneurs with actionable insights, this book will empower businesses to stay ahead of the curve, foster innovation, optimize resource utilization, and ultimately gain a competitive advantage in the ever-evolving manufacturing landscape.

Table of contents

• Cover
• Half Title
• Series
• Title
• Copyright
• Contents
• About the Editors
• List of Contributors
• Chapter 1 Unlocking Industry 5.0: The Role of IIoT and Machine Learning
• Chapter 2 Fundamentals of the Industrial Internet of Things (IIoT)
• Chapter 3 A Conceptual Study on the Industrial Revolution (IR) from 1.0 to 5.0
• Chapter 4 Potential Technologies and Applications of Industry 5.0
• Chapter 5 Streamlining Operations: The AI-Era Production Management
• Chapter 6 The Impact of Technological Advancement on Society and the Workforce
• Chapter 7 Optimizing Manufacturing Performance Using Contemporary Technologies
• Chapter 8 Transforming Industry 4.0: The Synergy of IIoT and Machine Learning for Enhanced Production Efficiency
• Chapter 9 Predictive Maintenance and Asset Management with IIoT and ML
• Chapter 10 Ensuring Security and Privacy in Internet of Things Deployments for Industry, Training, and Residential Environments: A Comprehensive Investigation
• Chapter 11 Statistical Analysis of Industrial Activities Using Machine Learning Techniques
• Chapter 12 HRM 5.0: Transforming Human Capital Management in the Era of Industry 5.0
• Chapter 13 Autonomous Robotics and Intelligent Automation in Industry 5.0
• Chapter 14 An Autonomous Mobile Robot Simulation Using Navigation (NAV2) and Simultaneous Localization and Mapping (SLAM) in ROS2
• Chapter 15 Integrating IIoT and Machine Learning for Enhanced Smart City Development and Urban Infrastructure
• Chapter 16 IIoT and ML in Smart Cities and Urban Infrastructure
• Chapter 17 Securing the Future of Industry: A Detailed Analysis of IIoT Cybersecurity Challenges and Solutions
• Chapter 18 Cybersecurity and Data Privacy Considerations for IIoT
• Chapter 19 Integrating Industry 5.0 Principles with Machine Learning and Internet of Things for Biotech Advancements
• Chapter 20 Implementation of Artificial Neural Networks and Machine Learning Algorithms Using Feature Selection to Predict User Capacity in LTE Network: An Extensive Overview
• Chapter 21 Enhancing Quality Control in Industry 4.0 by Leveraging Deep Learning and Machine Vision for Defect Detection and Process Optimization
• Chapter 22 Exploring the Intersection of Machine Learning and Wireless Communications in the Internet of Things
• Chapter 23 Leveraging Blockchain and Industrial Internet of Things (IIoT) Integration to Enhance Cybersecurity and Data Security in Industrial Environments
• Chapter 24 An Investigative Study of Recent Advancements in Augmented Reality for Industrial Internet of Things (IIoT) Applications
• Chapter 25 RFID Integrated with Human Interface System for Autonomous Shopping Tram with Integrated Bill Generator
• Chapter 26 Vocalizing Retail Innovation: A Qualitative Investigation into the Adoption of IoT-Enabled Voice Assistants in Indian Retail
• Chapter 27 The Autonomous Fermenter: Redefining Microbial Production with Intelligent Automation
• Chapter 28 Environmental Gas Monitoring Using Energy-Efficient LoRa-Based IoT Setup Products
• Index