jpteixeira / Fiap_MBA_DSA Public

Target: Raspberry Pi RP2040 (Cortex-M0+ 133MHz) Clone this project

Welcome to Edge Impulse, the largest community of edge AI developers!
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.

Fiap_MBA_DSA

Manutenção prescritiva de máquina com tinyML

Accelerometer

EdgeML tinyML Pi Pico W

About this project

This public Edge Impulse project does not have a README yet. Clone this project to add new data or retrain this project, or to deploy this project to a device.

Data (40 samples)

View all

falha.6hjf1m0t

ID: 2772584966

Label: falha

Sample length: 10s

OK.6hjff0ik

ID: 2772584979

Label: OK

Sample length: 10s

falha.6hjf14dm

ID: 2772584965

Label: falha

Sample length: 10s

OK.6hjf92rm

ID: 2772584971

Label: OK

Sample length: 10s

OK.6hjfbcs0

ID: 2772584974

Label: OK

Sample length: 10s

OK.6hjfeec6

ID: 2772584978

Label: OK

Sample length: 10s

falha.6hjevhns

ID: 2772584963

Label: falha

Sample length: 10s

OK.6hjf8guu

ID: 2772584970

Label: OK

Sample length: 10s

Model accuracy (Unoptimized (float32))

Validation set

99.6%

Test set

99.8%

On-device performance (Raspberry Pi RP2040 (Cortex-M0+ 133MHz), Quantized (int8))

Latency

11 ms.

Peak RAM usage

1.6K

Flash usage

17.9K

Run this model

On any device

Clone project

Dataset summary

Data collected

6m 40s

Sensors

accX, accY, accZ @ 937Hz

Labels

falha, OK

Project info

Project ID	961956
License	3-Clause BSD
No. of views	3
No. of clones	0