Iot And Machine Learning For Smart Applications
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Machine Learning and IoT for Intelligent Systems and Smart Applications
The fusion of AI and IoT 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 IoT 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 IoT 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 IoT applications. Discusses supervised and unsupervised machine learning for IoT data and devices. Presents an overview of the different algorithms related to Machine learning and IoT. Covers practical case studies on industrial and smart home automation. Includes implementation of AI from case studies in personal and industrial IoT. This book aims at Researchers and Graduate students in Computer Engineering, Networking Communications, Information Science Engineering, and Electrical Engineering.
IoT and Machine Learning for Smart Applications
This book provides an illustration of the various methods and structures that are utilized in machine learning to make use of data that is generated by IoT devices. Numerous industries utilize machine learning, specifically machine learning-as-a-service (MLaaS), to realize IoT to its full potential. On the application of machine learning to smart IoT applications, it becomes easier to observe, methodically analyze, and process a large amount of data to be used in various fields. Features: Explains the current methods and algorithms used in machine learning and IoT knowledge discovery for smart applications Covers machine- learning approaches that address the difficulties posed by IoT- generated data for smart applications Describes how various methods are used to extract higher- level information from IoT- generated data Presents the latest technologies and research findings on IoT for smart applications Focuses on how machine learning algorithms are used in various real- world smart applications and engineering problems It is a ready reference for researchers and practitioners in the field of information technology who are interested in the IoT and Machine Learning fields.
IoT and Machine Learning for Smart Applications
"This book provides an illustration of the various methods and structures that are utilized in machine learning to make use of data that is generated by IoT devices. Numerous industries utilize machine learning, specifically Machine learning-as-a-Service (MLaaS) to realize IoT to its full potential. On the application of machine learning to smart IoT applications, it becomes easier to observe, methodically analyze, and process a large amount of data to be put to use in various fields. Explains the current methods and algorithms used in machine learning and IoT knowledge discovery for smart applications Covers machine-learning approaches that address the difficulties posed by IoT-generated data for smart applications Describes how various methods are used to extract higher-level information from IoT-generated data Presents the latest technologies and research findings on IoT for smart Applications Focuses on how Machine Learning algorithms are used in various real-world smart applications and engineering problems It is a ready reference for researchers and practitioners in the field of information technology who are interested in the IoT and Machine Learning fields"-- Provided by publisher.