Industrial Internet of Things: An Introduction explores the convergence of IoT and machine learning technologies in transforming industries and advancing economic growth. This comprehensive guide examines foundational principles, innovative applications, and real-world case studies that showcase the power of IoT-enabled intelligent systems in enhancing efficiency, sustainability, and adaptability.
The book is structured into five parts. The first part introduces industrial IoT concepts, including algorithms, deep learning prediction models, and smart production techniques. The second section addresses machine learning and collaborative technologies, focusing on artificial neural networks, and AI's role in healthcare and industrial IoT. Subsequent chapters explore real-world applications, such as IoT adoption in healthcare during COVID-19 and intelligent transportation systems. The final sections address advanced IIoT progressions and the role of IoT in energy production using byproducts.
Key Features:
— Foundational concepts and algorithms for industrial IoT.
— Integration of machine learning in IoT systems.
— Case studies on healthcare, transportation, and sustainability.
— Insights into energy production using IoT.
