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Titlebook: Activity Recognition and Prediction for Smart IoT Environments; Michele Ianni,Antonella Guzzo,Zhelong Wang Book 2024 The Editor(s) (if app

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發(fā)表于 2025-3-21 18:02:21 | 只看該作者 |倒序瀏覽 |閱讀模式
期刊全稱Activity Recognition and Prediction for Smart IoT Environments
影響因子2023Michele Ianni,Antonella Guzzo,Zhelong Wang
視頻videohttp://file.papertrans.cn/168/167122/167122.mp4
發(fā)行地址Provides a comprehensive review of the field of activity recognition.Covers an array of topics and applications illustrating the use of activity recognition in IoT related scenarios.Explains how to ex
學(xué)科分類Internet of Things
圖書封面Titlebook: Activity Recognition and Prediction for Smart IoT Environments;  Michele Ianni,Antonella Guzzo,Zhelong Wang Book 2024 The Editor(s) (if app
影響因子.This book provides the latest developments in activity recognition and prediction, with particular focus on the Internet of Things. The book covers advanced research and state of the art of activity prediction and its practical application in different IoT related contexts, ranging from industrial to scientific, from business to daily living, from education to government and so on. New algorithms, architectures, and methodologies are proposed, as well as solutions to existing challenges with a focus on security, privacy, and safety. The book is relevant to researchers, academics, professionals and students.?.
Pindex Book 2024
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A Sitting Posture Monitoring System in Wheelchair Users,s of the optimal number of sensors to obtain a high percentage of success has been carried out, using Random Forest. The results show that the approach used is suitable for posture recognition, with accuracy over 90%, and that a number of nine sensors are enough to distinguish between different post
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Multi-User Activity Monitoring Based on Contactless Sensing,ferent activities. We evaluate the performance of our method on a publicly available dataset and compare it to other approaches, such as those based on computer vision and wearable sensors. Our results show that off-the-shelf Wi-Fi devices can be effectively used as a contactless sensing method for
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Grundkurs WirtschaftsmathematikR. We also compare the performance of recently proposed methods on popular benchmark datasets. We review 22 benchmark datasets for human action recognition. Some potential research directions are discussed to conclude this survey.
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