Principle Component Analysis and Random Forest Based All-Fiber Activity Monitoring

An activity monitoring algorithm based on principle component analysis and random forest is proposed, identifying three kinds of activities obtained from Mach-Zehnder interferometer with accuracy of 99.5% within one second, namely, normal, nobody and movement.