Toward fast and accurate emergency cases detection in BSNs-Reference-Cited by-同舟云学术

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Toward fast and accurate emergency cases detection in BSNs

Published:2020-02 Issue:1 Volume:10 Page:47-60
ISSN:2043-6386
Container-title:IET Wireless Sensor Systems
language:en
Short-container-title:IET wirel. sens. syst.

Author:

Boudargham Nadine¹,El Sibai Rayane²^ORCID,Bou Abdo Jacques³,Demerjian Jacques⁴,Guyeux Christophe⁵,Makhoul Abdallah⁵

Affiliation:

1. Faculty of EngineeringNotre Dame UniversityDeir El KamarLebanon

2. Faculty of EngineeringAl Maaref UniversityBeirutLebanon

3. Faculty of Natural and Applied SciencesNotre Dame UniversityDeir El KamarLebanon

4. LaRRIS, Faculty of SciencesLebanese UniversityFanarLebanon

5. Computer Science Department - DISCFemto-ST Institute, UMR CNRS 6174, Université de Bourgogne Franche-ComtéBesançonFrance

Publisher

Institution of Engineering and Technology (IET)

Subject

Industrial and Manufacturing Engineering

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/iet-wss.2019.0134

Reference72 articles.

1. Investigating low level protocols for Wireless Body Sensor Networks

2. Efficient cluster-based routing algorithm for body sensor networks

3. Anomaly Detection in Medical Wireless Sensor Networks

4. Sensor Anomaly Detection in Wireless Sensor Networks for Healthcare

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1. MEDCO: an efficient protocol for data compression in wireless body sensor network;Journal of Ambient Intelligence and Humanized Computing;2024-09-14

2. AS-LR Emergency Detection Scheme for Biomedical Applications;2023 International Conference on Microelectronics (ICM);2023-12-17

3. XorshiftH128+: A hybrid random number generator for lightweight IoT;2023 IEEE International Conference on Artificial Intelligence, Blockchain, and Internet of Things (AIBThings);2023-09-16

4. Detection of Adversarial Attacks against the Hybrid Convolutional Long Short-Term Memory Deep Learning Technique for Healthcare Monitoring Applications;Applied Sciences;2023-06-03

5. Isolation Forest Based Anomaly Detection Approach for Wireless Body Area Networks;Hybrid Intelligent Systems;2023

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