Home Automation for Disabled Using Brain Computer Interface and Raspberry Pi

Abstract

Electroencephalography (EEG)-based smart home control systems are a key application of Brain-Computer Interfaces (BCIs). BCIs empower people with disabilities to achieve greater independence at home. These interfaces allow individuals with severe impairments to interact with their surroundings and communicate with others. Many people with special needs, particularly the elderly, face significant challenges in their daily lives that can severely impact their quality of life. This project aims to develop a non-invasive BCI for people with special needs to control household appliances and access an emergency system. A graphical user interface (GUI) will provide users with the ability to manage various smart home devices. This system will also benefit people with physical limitations by granting them greater control over their home's electrical and electronic appliances. This study successfully developed and implemented a BCI system for controlling home appliances. By leveraging the Steady-State Visually Evoked Potentials (SSVEPs) generated in response to flickering visual stimuli, the BCI system accurately interpreted user intentions through signal analysis and classification techniques.