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.
© 2019 The Author(s)
You do not have subscription access to this journal. Citation lists with outbound citation links are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.
Contact your librarian or system administrator
Login to access OSA Member Subscription