The fusion of AI and Io T enables the systems to be predictive, prescriptive, and autonomous, and this convergence has evolved the nature of emerging applications from being assisted to augmented, and ultimately to autonomous intelligence. This book discusses algorithmic applications in the field of machine learning and Io T with pertinent applications. It further discusses challenges and future directions in the machine learning area and develops understanding of its role in technology, in terms of Io T security issues. Pertinent applications described include speech recognition, medical diagnosis, optimizations, predictions, and security aspects.
Features:
- Focuses on algorithmic and practical parts of the artificial intelligence approaches in Io T applications.
- Discusses supervised and unsupervised machine learning for Io T data and devices.
- Presents an overview of the different algorithms related to Machine learning and Io T.
- Covers practical case studies on industrial and smart home automation.
- Includes implementation of AI from case studies in personal and industrial Io T.
This book aims at Researchers and Graduate students in Computer Engineering, Networking Communications, Information Science Engineering, and Electrical Engineering.
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