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Titlebook: Internet of Things; Cases and Studies Fausto Pedro García Márquez,Benjamin Lev Book 2021 Springer Nature Switzerland AG 2021 IoT.Smart indu

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發(fā)表于 2025-3-27 00:27:54 | 只看該作者
32#
發(fā)表于 2025-3-27 01:32:00 | 只看該作者
The Combination of AI, Blockchain, and the Internet of Things for Patient Relationship Management,tter service to patients. However, shared data may be subject to theft or misuse due to the security issues on various devices. Moreover, transparency among stakeholders, confidentiality, and micropayments need to be addressed. The objective of this work is to use federated learning over blockchain
33#
發(fā)表于 2025-3-27 05:43:04 | 只看該作者
Bibliometric Characteristics of Highly Cited Papers on Internet of Things Assessed with Essential Sievements have been published. This study aims to provide a bibliometric review for highly cited papers in the field of IoT using the Essential Science Indicators, a widely used database to evaluate scientific outputs. Through the retrieval process, 388 papers were identified as highly cited papers.
34#
發(fā)表于 2025-3-27 12:41:40 | 只看該作者
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發(fā)表于 2025-3-27 16:59:17 | 只看該作者
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發(fā)表于 2025-3-27 21:40:50 | 只看該作者
IoT Applications in Healthcare,ces the existing IoT products in the healthcare market; reviews the studies on developing, using, and improving IoT healthcare applications; and presents and discusses the recent trend and focus of IoT healthcare applications. First, the chapter describes a general picture of IoT healthcare applicat
37#
發(fā)表于 2025-3-28 01:36:50 | 只看該作者
An Interactive Visiting System Using BLE Devices,nding grounds (smart places). The system features a mobile application that allows the user to access information from several smart places in a single application and an indoor location and tracking system that infers the user location during the smart place visit. The system calculates the trackin
38#
發(fā)表于 2025-3-28 05:50:04 | 只看該作者
Systematic Market and Asset Liquidity Risk Processes for Machine Learning: Robust Modeling AlgorithFurthermore, this research focuses on the theoretical aspects of asset liquidity risk and presents two critically robust machine learning processes to measuring the market liquidity risk for trading securities as well as for asset management objectives. To that end, this chapter extends research lit
39#
發(fā)表于 2025-3-28 09:29:56 | 只看該作者
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發(fā)表于 2025-3-28 10:45:03 | 只看該作者
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