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Titlebook: Intelligent Internet of Things; From Device to Fog a Farshad Firouzi,Krishnendu Chakrabarty,Sani Nassif Book 2020 Springer Nature Switzerla

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发表于 2025-3-21 18:25:56 | 显示全部楼层 |阅读模式
书目名称Intelligent Internet of Things
副标题From Device to Fog a
编辑Farshad Firouzi,Krishnendu Chakrabarty,Sani Nassif
视频video
概述Presents an efficient method to understand the most appropriate positioning of a business against its competitors by digitally transforming into an agile and profitable business based on AI-driven IoT
图书封面Titlebook: Intelligent Internet of Things; From Device to Fog a Farshad Firouzi,Krishnendu Chakrabarty,Sani Nassif Book 2020 Springer Nature Switzerla
描述.This holistic book is an invaluable reference for addressing various practical challenges in architecting and engineering Intelligent IoT and eHealth solutions for industry practitioners, academic and researchers, as well as for engineers involved in product development. The first part provides a comprehensive guide to fundamentals, applications, challenges, technical and economic benefits, and promises of the Internet of Things using examples of real-world applications. It also addresses all important aspects of designing and engineering cutting-edge IoT solutions using a cross-layer approach from device to fog, and cloud covering standards, protocols, design principles, reference architectures, as well as all the underlying technologies, pillars, and components such as embedded systems, network, cloud computing, data storage, data processing, big data analytics, machine learning, distributed ledger technologies, and security. In addition, it discusses the effects of Intelligent IoT, which are reflected in new business models and digital transformation. The second part provides an insightful guide to the design and deployment of IoT solutions for smart healthcare as one of the mo
出版日期Book 2020
关键词Internet of everything; Big data; AI-driven IoT; IoT cloud architecture and design; IoT in healthcare
版次1
doihttps://doi.org/10.1007/978-3-030-30367-9
isbn_softcover978-3-030-30369-3
isbn_ebook978-3-030-30367-9
copyrightSpringer Nature Switzerland AG 2020
The information of publication is updating

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发表于 2025-3-21 21:47:15 | 显示全部楼层
Machine Learning for IoTsics that many machine learning solutions must rely on to become amenable. Next, we provide several use cases of machine learning in IoT solutions. Finally, we will discuss the details of two main categories in machine learning, namely, supervised learning and unsupervised learning.
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Emerging Hardware Technologies for IoT Data Processing The first architecture is a memory subsystem based on the emerging nonvolatile memory technologies that enables energy-efficient neural network acceleration in memory arrays. The memory system is capable of performing ordinary data storage in the future IoT nodes, as well as significantly accelerat
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Healthcare IoTEmpowering this transformation will require the software and hardware communities to come together to achieve extensive technological advancements. This chapter addresses all these important aspects of novel IoT technologies for smart healthcare – wearable sensors, body area sensors, advanced pervas
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Smart Learning Using Big and Small Data for Mobile and IOT e-Healthe accumulated longitudinal records of such phonemes are also expected to capture patterns that can help distinguish individual physiological differences, e.g., being insulin-sensitive or insulin-resistant, which will make a difference in disease diagnosis and prognosis [8].
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