Pre-Impact Firefighter Fall Detection Using Machine Learning on the Edge-Reference-Cited by-同舟云学术

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Pre-Impact Firefighter Fall Detection Using Machine Learning on the Edge

Published:2023-07-01 Issue:13 Volume:23 Page:14997-15009
ISSN:1530-437X
Container-title:IEEE Sensors Journal
language:
Short-container-title:IEEE Sensors J.

Author:

Chai Xiaoqing¹^ORCID,Lee Boon-Giin¹^ORCID,Pike Matthew¹^ORCID,Wu Renjie¹^ORCID,Chieng David¹^ORCID,Chung Wan-Young²^ORCID

Affiliation:

1. Nottingham Ningbo China Beacons of Excellence Research and Innovation Institute, Faculty of Science and Engineering, University of Nottingham Ningbo China, Ningbo, China

2. Department of Electronic Engineering, Pukyong National University, Busan, South Korea

Funder

Zhejiang Provincial Natural Science Foundation of China

Ningbo Science and Technology (S&T) Bureau through the Major S&T Program

National Research Foundation of Korea (NRF) grant funded by the Korean Government [Ministry of Science and ICT (MSIT)]

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

http://xplorestaging.ieee.org/ielx7/7361/10168680/10136391.pdf?arnumber=10136391

Reference69 articles.

1. A study of the influence of the sensor sampling frequency on the performance of wearable fall detectors;santoyo-ramón;Measurement,2022

2. Context aware inactivity recognition for visual fall detection;jansen;Proc Pervasive Health Conf Workshops,2007

3. Test Event Generation for a Fall-Detection IoT System

4. A Depth-Based Fall Detection System Using a Kinect® Sensor

5. Sparse Inertial Poser: Automatic 3D Human Pose Estimation from Sparse IMUs

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