Machine Learning Approach for Cloud Data Analytics in IoT

Preface

Sustainable computing paradigms like cloud and fog are capable of handling issues related to performance, storage and processing, maintenance, security, efficiency, integration, cost, energy and latency in an expeditious manner. According to statistics, billions of connected IoT devices will be producing enormous amounts of real-time data in the coming days. In order to expedite decision-making involved in the complex computation and processing of collected data, these devices are connected to the cloud or fog environment. Since machine learning as a service provides the best support in business intelligence, organizations have been making significant investments in the creation of the first artificial intelligence services. The abundant research occurring all around the world has resulted in a wide range of advancements being reported on computing platforms. This book elucidates some of the best practices and their respective outcomes in cloud and fog computing environments. The practices, technologies and innovations of business intelligence employed to make expeditious decisions are encouraged as a part of this area of research.

This book focuses on various research issues related to big data storage and analysis, large-scale data processing, knowledge discovery and knowledge management, computational intelligence, data security and privacy, data representation and visualization and data analytics. The featured technology presented herein optimizes various industry ...