Edge-based Fall Detection
Edge-Based Fall Detection is a fall detection framework that performs real-time data processing and analysis on local edge devices rather than centralized servers, thereby reducing latency, preserving privacy, and enabling immediate response in human activity monitoring systems.
18
Publications
1.3K
Citations
74
Authors
35
Institutions
Publications per year
2017–2026
15
Parents
18
FAST: A fog computing assisted distributed analytics system to monitor fall for stroke mitigation
Yu Cao, Songqing Chen, Peng Hou et al. · 2015 · 193 citations
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35
Taipei Medical University
Taipei, Taiwan
2 h-index
3 publications
123 citations

National Taipei University
Taipei, Taiwan
2 h-index
9 publications
333 citations

Huazhong University of Science and Technology
Wuhan, China
1 h-index
3 publications
102 citations

National Yang Ming Chiao Tung University
Hsinchu, Taiwan
1 h-index
2 publications
34 citations

Silesian University of Technology
Gliwice, Poland
1 h-index
2 publications
264 citations

University of North Texas
Denton, United States
1 h-index
3 publications
51 citations

Mohammed V University
Rabat, Morocco
1 h-index
5 publications
120 citations
University of Oklahoma
Norman, United States
1 h-index
3 publications
936 citations
1–8 of 35
3 publications · 126 citations
3
h-index
1 publications · 24 citations
1
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1 publications · 17 citations
1
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1 publications · 312 citations
1
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JETCAS · 1 publications · 98 citations
1
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1–5