
Data Analytics and Artificial Intelligence for Predictive Maintenance in Industry 4.0
- English
- ePUB (mobile friendly)
- Available on iOS & Android
Data Analytics and Artificial Intelligence for Predictive Maintenance in Industry 4.0
About this book
Data Analytics and Artificial Intelligence for Predictive Maintenance in Industry 4.0 unites data science, machine learning, IIOT, and AI to enable predictive and prescriptive maintenance across manufacturing, energy, transportation, agriculture, and healthcare. With contributions from leading academics and practitioners, the book bridges foundational principles with cutting-edge industrial case studies ranging from digital twins and anomaly detection to federated learning and secure healthcare analytics. Key Features Explains fundamental concepts of data analytics, AI, and machine learning for predictive maintenance. Integrates IIoT, digital twins, federated learning, and blockchain into industrial maintenance strategies. Demonstrates real-world applications across manufacturing, energy, healthcare, and agriculture sectors. Analyzes optimization techniques, anomaly detection, condition monitoring, and RUL prediction models. Addresses security and ethical issues, including hardware protection and homomorphic encryption for healthcare. Maps future trends and emerging technologies driving predictive maintenance research.
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Information
Table of contents
- Welcome
- Table of Contents
- Title
- BENTHAM SCIENCE PUBLISHERS LTD.
- FOREWORD
- PREFACE
- List of Contributors
- Understanding the Basics of Data Analytics and AI for Predictive Maintenance in Industry 4.0
- AI-Enabled Industrial Intelligence: From Data Engineering to Predictive Modeling
- Big Data Analytics for Predictive Maintenance in Industry 4.0.
- Hardware Security Enhancement with Generative Artificial Intelligence
- Fundamentals of Predictive Maintenance Using Machine Learning, Deep Learning, and IoT in Industry 4.0
- Predictive Maintenance for Enhanced Resilience in Natural Disasters
- Advancing Agriculture 4.0 through Federated Learning Techniques: Collaborative Analysis of Distributed Agricultural Data
- From Data to Insights: A Bibliometric Exploration of AI Innovations in the Fourth Industrial Revolution
- Application of IoT-Based EEG Sensors in Industry 4.0
- Optimization Techniques for Predictive Maintenance in Industry 4.0
- Enhancing Predictive Maintenance through Optimization in the Era of Industry 4.0
- Future Trends in Secure Healthcare Predictive Analysis: Homomorphic Encryption Perspectives
- Future Trends and Emerging Technologies in Predictive Maintenance Research