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About Real Time Fall Detection in Fog Computing Scenario
This document discusses using fog computing for real-time fall detection. It proposes using a one-class support vector machine (SVM) model with features extracted from smartphone accelerometer data to detect falls. The model is implemented using fog computing to send immediate notifications to caregivers, even without an internet connection. In initial tests, the method achieved 100% sensitivity and 98.77% specificity for fall detection on real data, while greatly reducing the amount of data transferred compared to direct cloud computing.
Detailed Information
| Author: | ['maachanas1530'] |
|---|---|
| Publication Year: | 2021 |
| Pages: | 10 |
| Language: | English |
| Format: | |
| Price: | FREE |
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