NEUROSYNC: A HYBRID BRAINWAVE–GESTURE CONTROL SYSTEM

Abstract

— Today, automation technology is becoming increasingly accessible, user friendly, and efficient, enabling novel solutions for improving the quality of life. This project explores the integration of brain-computer interfaces (BCI) with the Internet of Things (IoT) to provide a smart assistive system for individuals with limited physical mobility. The system employs an EEG headset to capture real-time brain signals, which are transmitted via Bluetooth to an ESP32 microcontroller for processing. Based on the interpreted brain signals, the system can control electrical appliances such as lights and fans by switching a relay module ON or OFF. The system also supports hand gesture control as a backup input method, ensuring reliable operation even when brain signals are unstable. Additionally, the system is designed to detect abnormal brain activity, automatically triggering alerts through an application, and activating a buzzer to notify caregivers or family members. The application also provides a real-time display of appliance status, ensuring users are always aware of the current system state. The expected outcome of this project is a reliable and user-friendly brain-controlled automation system that enhances safety, and convenience for physically challenged individuals.