[31] A NOVEL ARCHITECTURE FOR ELECTROENCEPHALAGRAM BASED BRAIN-COMPUTER INTERFACE FOR INTELLIGENT VEHICLE CONTROL
How to Cite the Article: V. Raju, K. V. S Ganesh, T. Pattala Naidu, Ch. N. Sowmya, K. Durga Prasad & M. Poorna Sai (2026). A Novel Architecture for Electroencephalagram Based Brain- Computer Interface for Intelligent Vehicle Control. International Journal of Multidisciplinary Research & Reviews, 5(5),382-390. https://doi.org/10.56815/ijmrr.v5i5.2026.382-390
Abstract
The project titled "EEG Based Brain Computer Interface for Intelligent Vehicle Control" presents the design and development of an assistive robotic vehicle that can be controlled using brain signals and eye movements. This system aims to support individuals with
physical disabilities by enabling hands-free control of a vehicle through neural and visual inputs.The proposed system integrates an
EEG module with multiple electrodes to capture brain signals from the user. These signals are processed and transmitted to a microcontroller unit (MCU), which acts as the central controller. The EEG signal is used to activate or deactivate the system, ensuring that
the vehicle responds only when valid brain activity is detected. Simultaneously, a camera connected to a computer processes real-time video using computer vision techniques. The Python-based application utilizes libraries such as OpenCV and MediaPipe to track eye movements and determine directional commands like forward,backward, left, and right. The processed commands are transmitted to the ESP32-based controller via HTTP communication. The controller interprets these commands and drives the motor driver accordingly to control the movement of the vehicle's motors. The system includes smoothing, calibration, and threshold-based decision mechanisms to ensure accurate and stable control. Additionally, safety features such as automatic stop when no signal or human face is detected enhance the reliability of the system.Overall, this project demonstrates an efficient integration of Brain-Computer Interface (BCI), embedded systems, and computer vision to create an intelligent and user-friendly vehicle control system. The developed system has potential applications in assistive technologies, smart mobility solutions, and advanced human-machine interaction systems.
