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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.
Use Case: Consumer Products
This is the corresponding project for Use Case chapter "Consumer Products" of the O'Reilly book "AI at the Edge" (https://learning.oreilly.com/library/view/ai-at-the/9781098120191/)
About this project
Bicycle monitor
Note: The corresponding end-to-end tutorial for this Edge Impulse project is included in Chapter 13 (Use Case: Consumer Products) of the O'Reilly book "AI at the Edge" by Daniel Situnayake and Jenny Plunkett.
Image by
Michael Gaida
Device/sensor information
- Nordic Thingy:53
- Mobile phone
- Accelerometer data (62.5 Hz)
Machine learning classes
- Idle
- Nominal
- Sudden stop
Block information
- DSP: Spectral analysis
- ML: Classification
- ML: Anomaly detection
Run this model
On any device
Dataset summary
Data collected
8m 49sSensors
accX, accY, accZ @ 62.5HzLabels
idle, nominal, sudden stopProject info
| Project ID | 115653 |
| Project version | 3 |
| License | BSD 3-Clause Clear |
| No. of views | 3,202 |
| No. of clones | 17 |
