I’m looking to train a model based on a geophone seismic sensor.
It’s a similar model to an accelerometer but it’s analog.
So i can connect it to the Nano but how should i do it?
How do I sample that data to create a detection model for certain vibrations?
I have data that looks like that from Raspberry Pi that was recorded as raw data.
0.0772400498390198 -0.0334217622876167 0.0159807838499546 0.0177145823836327 0.0773506164550781 -0.0327318646013737 0.0163810141384602 0.0180633589625359 0.0770958736538887 -0.0316078439354897 0.0168671533465385 0.018361896276474 0.0767902359366417 -0.029647970572114 0.0177943296730518 0.0189994983375072 0.0763635784387589 -0.0288539547473192 0.0179303847253323 0.0190845690667629 0.0770840123295784 -0.0290875006467104 0.0170500855892897 0.0185087844729424 0.0778733566403389 -0.0295919422060251 0.0161766037344933 0.0183468628674746
How can I load it into the ML? or it can work only directly from the edge unit?
Also on one hand it’s like an accelerometer but I want to extract 1D FFT data from it like Audio data.
How can i convert the time series data to a frequency series using an FFT, then build a training model with the small FFT segments as 1D inputs.