BRAINWAVE: EEG Based Brain and Voice Controlled Hybrid Smart Multi-Plug

The purpose of this study is to develop a hybrid Brain-Computer Interface (BCI) system for home automation (smart multiplug), which can be controlled through both mind (brain) and voice (vocals). BCIs have emerged as a viable prospect in the fields of medicine (e.g., neuronal rehabilitation), education, mind reading, and distant communication over the last decade. However, because of the challenges of the uncomfortable head equipment, reduced classification accuracy, high expense, and complex operation, BCI is still difficult to utilize in daily life. In this work, the Fast Fourier transform (FFT) and the Convolution Neural Network (CNN) are the algorithms that were used for feature extraction and classification respectively. Four home appliances will be controlled by the BCI system in our work. Besides that, we propose to make a Smart Multi-plug that can be controlled by both brain and voice from anywhere in the world, with links to Google Assistant, Alexa, and a Virtual Private Server(VPS) through WEMOS D1 Mini board and Sinric Pro API. With this WEMOS D1 Mini project, four home appliances will be controlled with Google Assistant, Alexa, and manual switches.