Channel State Information (CSI) analysis for predictive maintenance using Convolutional Neural Network (CNN)

Dataset manual:

This dataset contains CSI amplitude values for rotating motors in an office environment. Details of the experiments may be found in the corresponding paper published in the DATA'19 workshop, SenSys (https://doi.org/10.1145/3359427.3361917). 

Folder structure:
The folders for servo motor and stepper motor contains separate folders for network reconnection conditions (w_recc: with reconnections, wo_recc: without recconnections) and load conditions (w_load: with load and wo_load: without load). The data is stores as Matlab files with .mat extentions. 

File structure:
In each file name, the digits after the '_' at the end of the file name correspond to the speed of the motor. In case of stepper motor these numbers could be directly interpreted as rpm. Ex: table_inj_with_load_5_0.mat corresponds to stationary motor (0 rpm) and table_inj_with_load_5_250.mat corresponds to motor rotating with 250 rpm speed. In the case of servo motor these numbers should be mapped with the following table in order to get the speeds.

0: 0 rpm
50: 14.45 rpm
100: 8.02 rpm
150: 5.38 rpm
200: 4.05 rpm
250: 3.26 rpm
300: 2.67 rpm
Ex: table_inj_with_load_50.mat corresponds to motor running with 14.45 rpm.

Each file has 3 columns, each corresponding to CSI value, labels (speed/last digits in the file name) and the data sample number (not in sequence as a result of packer loss) respectively. CSI values are typically a matrix of size 3000*180 (3000 CSI samples for 3sec data @1kHz sampling rate and 180 channels for 6 antenna pairs @ 30 subcarrier data per antenna).