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Erschienen in:
Comparison of Multi-channel Ranging Algorithms for Narrowband LPWA Network Localization Kapitel lesen Erstes Kapitel lesen

2020 | OriginalPaper | Buchkapitel

A Wearable IoT-Based Fall Detection System Using Triaxial Accelerometer and Barometric Pressure Sensor

verfasst von : Elahe Radmanesh, Mehdi Delrobaei, Oussama Habachi, Somayyeh Chamani, Yannis Pousset, Vahid Meghdadi

Erschienen in: Ubiquitous Networking

Verlag: Springer International Publishing

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Abstract

The aim of this research work is to develop a wearable and IoT-based fall detection system that can potentially be integrated within a smart home or a community health center to improve the quality of life of the elderly. This system would enable caregivers to remotely monitor the activities of their dependents and to immediately be notified of falls as adverse events. The proposed hardware architecture includes a processor, a triaxial accelerometer, a barometric pressure sensor, a Wi-Fi module, and battery packs. This unobtrusive architecture causes no interference with daily living while monitoring the falls. The output of the fall detection algorithm is a two-state flag, transmitted to a remote server in real-time.

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Vorheriges Kapitel IIoT-Based Prognostic Health Management Using a Markov Decision Process Approach
Nächstes Kapitel A Congestion Game Analysis for Route-Parking Selection with Dynamic Pricing Policies
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Metadaten
Titel
A Wearable IoT-Based Fall Detection System Using Triaxial Accelerometer and Barometric Pressure Sensor
verfasst von
Elahe Radmanesh
Mehdi Delrobaei
Oussama Habachi
Somayyeh Chamani
Yannis Pousset
Vahid Meghdadi
Copyright-Jahr
2020
Buch
Ubiquitous Networking

Print ISBN: 978-3-030-58007-0

Electronic ISBN: 978-3-030-58008-7

Copyright-Jahr: 2020

DOI
https://doi.org/10.1007/978-3-030-58008-7_13