| 书目名称 | Learning Techniques for the Internet of Things | | 编辑 | Praveen Kumar Donta,Abhishek Hazra,Lauri Lovén | | 视频video | | | 概述 | Introduces a pictorial representation of IoT.Briefly discuss advanced learning techniques for IoT.Presents the collaboration IoT-Edge-Cloud architecture for new applications | | 图书封面 |  | | 描述 | .The book is structured into .thirteen. chapters; each comes with its own dedicated contributions and future research directions. Chapter 1 introduces IoT and the use of Edge computing, particularly cloud computing, and mobile edge computing. This chapter also mentions the use of edge computing in various real-time applications such as healthcare, manufacturing, agriculture, and transportation. Chapter 2 motivates mathematical modeling for federated learning systems with respect to IoT and its applications. Further Chapter 3 extends the discussion of federated learning for IoT, which has emerged as a privacy-preserving distributed machine learning approach. Chapter 4 provides various machine learning techniques in Industrial IoT to deliver rapid and accurate data analysis, essential for enhancing production quality, sustainability, and safety. Chapter discusses the potential role of data-driven technologies, such as Artificial Intelligence, Machine Learning, and Deep Learning, focuses on their integration with IoT communication technologies. Chapter 6 presents the requirements and challenges to realize IoT deployments in smart cities, including sensing infrastructure, Artificial In | | 出版日期 | Book 2024 | | 关键词 | Internet of Things; IoT Applications; Learning techniques; AI for Healthcare; AI for IoT; AI for Industry | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-031-50514-0 | | isbn_softcover | 978-3-031-50516-4 | | isbn_ebook | 978-3-031-50514-0 | | copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl |
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发表于 2025-3-21 18:24:02
