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BRAINWAVE: EEG Based Brain and Voice Controlled Hybrid Smart Multi-Plug | IEEE Conference Publication | IEEE Xplore

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


Abstract:

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 (b...Show More

Abstract:

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.
Date of Conference: 01-02 December 2022
Date Added to IEEE Xplore: 02 January 2023
ISBN Information:
Conference Location: Colombo, Sri Lanka
References is not available for this document.

I. Introduction

A Brain-Computer Interface (BCI) can be defined as a system that connects a brain to a machine so that signals from the brain can be controlled by various external activities without the involvement of muscles or peripheral nerves [1] . BCI-based applications can be utilized to control wheelchairs, toys, video games, prosthetics, and computer applications. On top of that, a BCI-based home automation control system has recently been suggested based on the promised advantages of artificial intelligence. In contrast to other types of home automation systems [2] , here we are focusing on the utilization of a BCI system for home automation using the Steady-State Visual Evoked Potentials (SSVEP) interface in order to aid elderly people, people with disabilities, and people who are in serious medical conditions to acquire their basic requirements. We propose to use Google Assistant and Alexa, which are linked with Sinric Pro for the voice-controlling process.

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References

References is not available for this document.