Walk4Me application



The current sensor capacity works at 100hz, so I used HTTP methods (TCP) in real-time.


Stream: If the server was not on record mood, the app would be steady on Ready mode, and it will move to stream mode automatically once the server sets on the recording mood.

Data collection

Server side: (1) Web application: PHP, JS, & Python. (2) dataset: csv and josn. (3) Computations: AWS EC2

Client: (1) ios app: swift. (2) Sensors: accelerometers and gyroscopes, and from the pedometer, magnetometer, and barometer.

Data processing

Pre-processing data: (1) Feature extraction (2) Raw data. (3) Classification, and dimensionality reduction
ML: (1) CML. (2) DL.

Results: Force Index FI/W