 In this study, we developed an online home appliance control system using a steady-state visual evoked potential, SSVEP, based BCI with visual stimulation presented in an augmented reality, AR, environment and electrooculogram, EOG, based iTracker. The system was evaluated for individuals aged over 65, who were able to turn on the AR-based home automation system using an eye-blink-based switch and select devices to control with three different methods depending on their preference. The system achieved high usability scores and now performed other BCI systems for the elderly. This article was authored by Sianghan Park, Jisooha, Jimin Park and others.