This volume showcases upcoming trends and applications that are set to redefine our technological landscape. Chapters comprise referenced reviews focused on the recent research that introduces new methods and techniques for using AI in Industry 4.0, and the integration of Internet of Things (IoT) to drive new industrial processes. The contributors have discussed challenges in industry 4.0 along with the applications and the way it is shaping different industries.
New AI Techniques for Industry 4.0: Learn about technologies such as blockchains and applications of machine learning, deep learning, and image processing.
Whether you're a tech enthusiast, researcher, or industry professional, this book offers a glimpse into the innovative world of Industry 4.0 and its intersection with AI, IoT, big data, and cloud computing.
Key themes:
AI in Communication Media: Uncover the latest research, with insights into the challenges and adoption of AI in remote processes.New AI Techniques for Industry 4.0: Learn about technologies such as blockchains and applications of machine learning, deep learning, and image processing.
IoT and AI for Smart Systems: Understand IoT with a special focus on enhancing smart systems, in different industries, including agriculture and transaction processing
Explorable AI: Gain a quick understanding of Explainable AI (XAI) and its role in improving the predictability and transparency of IoT applications.Whether you're a tech enthusiast, researcher, or industry professional, this book offers a glimpse into the innovative world of Industry 4.0 and its intersection with AI, IoT, big data, and cloud computing.
Table of Contents
- Contents
- Foreword
- Preface
- List of Contributors
- And Challenges in Iot, and Blockchain Technologies for Industry 4.0
- Saniya Zahoor, Ravesa Akhter, Varad Vishwarupe, Mangesh Bedekar, Milind Pande
- Vijay P. Bhatkar, Prachi M. Joshi, Vishal Pawar, Neha Mandora and Priyanka
- Kuklani
2. Integrated Blockchain-Iot Applications
2.1. Smart Iot-Healthcare
2.2. Smart Home
2.3. Smart Education
2.4. Drug Traceability
2.5. Power Grid
2.6. Smart Transportation System
2.7. Commercial World
2.8. Supply Chain
2.9. Automotive Industry
2.10. E-Government
3. Challenges in the Adoption of Blockchain in IoT Environments
- For Industry 4.0.
3.2. Storage Capacity and Scalability
3.3. Security
3.4. Smart Contracts
3.5. Legal Issues
3.6. Co-Integration With IoT Platform
3.7. Virtual Ecosystem
3.8. Structurally Adaptable
3.9. Dynamic Expandability
3.10. Standardization
- Conclusion
- References
- Priya Shelke and Riddhi Mirajkar
1.1. Core Value Drivers
1.2. The Nine Pillars of Industry 4.0
2. Blockchain
2.1. Features of Blockchain
2.2. Evolution of Blockchain
2.2.1. Blockchain 1.0
2.2.2. Blockchain 2.0
2.2.3. Blockchain 3.0
2.3. Consensus Mechanism in Blockchain Technology
3. Role of Blockchain in Industry 4.0
3.1. Healthcare
3.1.1. Issues in the Adaption of Blockchain in Healthcare
3.1.2. Current Application of Blockchain in Healthcare
3.2. Agriculture
3.2.1. Crop Insurance
3.2.2. Smart Agriculture
3.2.3. Food Supply Chain
3.3. Manufacturing
3.3.1. Commercial Impact of Blockchain
3.3.2. Automating Across Boundaries while Enabling Trust
3.3.3. Blockchain’S Case Studies in Manufacturing
3.3.4. Best Practices for Blockchain Solutions
3.4. Government
3.4.1. Building Trust in Government
3.4.2. Benefits of Solving the Problems Unique to Government With Blockchain
3.5. Education
3.5.1. Benefits for Students
3.5.2. Benefits for Institutions
3.5.3. Benefits for Employers
3.5.4. Using Blockchain for University Curricula
3.5.5. Blockchain’S Role in Lowering Education Costs
- Conclusion
- Acknowledgments
- References
- Pratap Pandurang Halkarnikar and Hriday Pandurang Khandagale
2. Components of Industry 4.0
2.1. Internet of Things (Iot)
2.2. Autonomous Robots
2.3. Big Data
2.4. Simulation
2.4.1. Benefits of Simulation Software
2.5. Cloud Computing
3. Benefits of Industry 4.0
4. Implementing Industry 4.0: Challenges, Issues, and Solutions
5. Case Study: Leather Manufacturing Unit
5.1. Iot-Based Area Measuring Machine
- Conclusion
- References
- Brain Tumor Using Explainable Artificial Intelligence (Xai): A
- Systematic Review of the State-Of-The-Art
- Prasad Raghunath Mutkule, Nilesh P. Sable, Parikshit N. Mahalle and Gitanjali R.
- Shinde
1.1. Explainable Ai
1.2. Some Key Concepts Related to Xai
1.3. Significance of Explainable Artificial Intelligence
1.4. Lime (Locally Interpretable Model Agnostic Explanations)
Author
- Parikshit N. Mahalle
- Gitanjali R. Shinde
- Prachi M. Joshi
