Internet of Things in the Era of Machine Learning
Curated Literature Overview
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Beschreibung
This book presents the result of an innovative challenge, to create a systematic literature overview driven by machine-generated content. This machine-generated volume, with chapter introductions by the human expert, of summaries of the existing studies furthers our understanding of the Internet of Things in the Era of Machine Learning. This book illuminates the opportunities that machine learning (ML) offers to IoT and provides a glimpse of the state-of-the-art in this area. The book is organized into ten chapters with each chapter gathering recent publications that tackle how ML has served a specific constituent of the IoT platform. The main objective of the book is to shed light on ML-driven research for the design and development of IoT technologies.
Questions and related keywords were prepared for the machine to query, discover, collate, and structure by Artificial Intelligence (AI) clustering. The AI-based approach seemed especially suitable to provide an innovative perspective as the topics are indeed both complex, interdisciplinary and multidisciplinary. Springer Nature has published much on these topics in its journals over the years, so the challenge was for the machine to identify the most relevant content and present it in a structured way that the reader would find useful. The automatically generated literature summaries in this book are intended as a springboard to further discoverability. They are particularly useful to readers with limited time, looking to learn more about the subject quickly and especially if they are new to the topics. Springer Nature seeks to support anyone who needs a fast and effective start in their content discovery journey, from the undergraduate student exploring interdisciplinary content to Master- or PhD-thesis developing research questions, to the practitioner seeking support materials, this book can serve as an inspiration, to name a few examples.
It is important to us as a publisher to make advances in technology easily accessible to our authors and find new ways of AI-based author services that allow human-machine interaction to generate readable, usable, collated, research content.
This book presents the result of an innovative challenge, to create a systematic literature overview driven by machine-generated content. This machine-generated volume, with chapter introductions by the human expert, of summaries of the existing studies furthers our understanding of the Internet of Things in the Era of Machine Learning. This book illuminates the opportunities that machine learning (ML) offers to IoT and provides a glimpse of the state-of-the-art in this area. The book is organized into ten chapters with each chapter gathering recent publications that tackle how ML has served a specific constituent of the IoT platform. The main objective of the book is to shed light on ML-driven research for the design and development of IoT technologies.
Questions and related keywords were prepared for the machine to query, discover, collate, and structure by Artificial Intelligence (AI) clustering. The AI-based approach seemed especially suitable to provide an innovative perspective as the topics are indeed both complex, interdisciplinary and multidisciplinary. Springer Nature has published much on these topics in its journals over the years, so the challenge was for the machine to identify the most relevant content and present it in a structured way that the reader would find useful. The automatically generated literature summaries in this book are intended as a springboard to further discoverability. They are particularly useful to readers with limited time, looking to learn more about the subject quickly and especially if they are new to the topics. Springer Nature seeks to support anyone who needs a fast and effective start in their content discovery journey, from the undergraduate student exploring interdisciplinary content to Master- or PhD-thesis developing research questions, to the practitioner seeking support materials, this book can serve as an inspiration, to name a few examples.
It is important to us as a publisher to make advances in technology easily accessible to our authors and find new ways of AI-based author services that allow human-machine interaction to generate readable, usable, collated, research content.
A Curated Literature Overview of Internet of Things in the Era of Machine Learning An experimental text into machine generated and curated content A starting guide to Internet of Things
Autor*in
Mounib Khanafer
Themen in »Internet of Things in the Era of Machine Learning«
IoT Networking Technologies Machine Learning Architectures IoT Applications Recommender Systems for IoT Securing IoT using Machine Learning Machine Learning and IoT Clouds Data Analysis in IoT IoT Embedded Systems