Advanced Sensing Techniques for Intelligent Human Activity Recognition Using Machine Learning-Reference-Cited by-同舟云学术

Advanced Sensing Techniques for Intelligent Human Activity Recognition Using Machine Learning

Published:2023-09-22 Issue:19 Volume:12 Page:3990
ISSN:2079-9292
Container-title:Electronics
language:en
Short-container-title:Electronics

Author:

Shah Syed Aziz¹^ORCID,Abbasi Qammer Hussain²^ORCID,Ahmad Jawad³^ORCID,Imran Muhammad Ali²^ORCID

Affiliation:

1. Research Centre for Intelligent Healthcare, Coventry University, Coventry CV1 5FB, UK

2. James Watt School of Engineering, University of Glagsow, Glasgow G12 8QQ, UK

3. School of Computing, Engineering and the Built Environment, Edinburgh Napier University, Edinburgh EH10 5DT, UK

Abstract

State-of-the-art network architectures ensure fast and dependable real-time communication with abundant data and minimal delays [...]

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Hardware and Architecture,Signal Processing,Control and Systems Engineering

Link

https://www.mdpi.com/2079-9292/12/19/3990/pdf

Reference23 articles.

1. Data portability for activities of daily living and fall detection in different environments using radar micro-Doppler;Shah;Neural Comput. Appl.,2022

2. Shah, S.I., Shah, S.Y., and Shah, S.A. (2019, January 21–22). Intrusion detection through leaky wave cable in conjunction with channel state information. Proceedings of the IEEE 2019 UK/China Emerging Technologies (UCET), Glasgow, UK.

3. Development of an Intelligent Real-Time Multiperson Respiratory Illnesses Sensing System Using SDR Technology;Rehman;IEEE Sens. J.,2022

4. Saeed, U., Shah, S.A., Khan, M.Z., Alotaibi, A.A., Althobaiti, T., Ramzan, N., and Abbasi, Q.H. (2022). Intelligent reflecting surface-based non-LOS human activity recognition for next-generation 6G-enabled healthcare system. Sensors, 22.

5. AI-driven lightweight real-time SDR sensing system for anomalous respiration identification using ensemble learning;Saeed;CCF Trans. Pervasive Comput. Interact.,2022

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