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This is a public Edge Impulse project, use the navigation bar to see all data and models in this project; or clone to retrain or deploy to any edge device.
This is a public Edge Impulse project, use the navigation bar to see all data and models in this project; or clone to retrain or deploy to any edge device.
Fall Detection w Arduino Nano 33 BLE
A project of TinyTensor - A Tiny Machine Learning Bootcamp
About this project
Fall Detection with Arduino Nano 33 BLE
Welcome to the Fall Detection with Arduino Nano 33 BLE project!
Overview
In this project, we upload data from the accelerometer, gyroscope, and magnetometer to build a model that detects falling states. Currently, the model identifies three states:
- FALL
- IDLE
Principle
The core logic is based on the principle that a sudden change in sensor values indicates a fall.
Features
- Real-time data processing from multiple sensors
- Accurate fall detection using machine learning models
- Easy deployment and integration with other systems
Requirement for uploading data
Sensors:
- Accelerometer
- Gyroscope
- Magnetometer
Sample Length: 5000ms (5s)
Frequency: 62.5Hz
Label: Named along with states in Overview
Train/Test Rate: 5/1
Developers
- Nam Khánh
A project of TinyTensor - A Tiny Machine Learning Bootcamp
Run this model
On any device
Dataset summary
Data collected
2m 30sSensors
accX, accY, accZ, gyrX, gyrY, gyrZ, magX, magY, magZ @ 62.5HzLabels
FALL, IDLEProject info
| Project ID | 492876 |
| License | Apache 2.0 |
| No. of views | 434 |
| No. of clones | 6 |
