• D. A. Zubov University of Central Asia, Bishkek, Kyrgyzstan, Kyrgyzstan
  • M. S. Qureshi University of Central Asia, Bishkek, Kyrgyzstan, Kyrgyzstan
  • U. Köse Süleyman Demirel University, Isparta, Turkey, Turkey
  • A. I. Kupin Kryvyi Rih National University, Kryvyi Rih, Ukraine, Ukraine



brain-to-thing, immobilized people, EEG sensor, MQTT


Context. Immobilized people face additional barriers in almost all areas of life, including simple operations like turning the light on/off and controlling the air conditioner. The object of the study was to develop the brain-to-thin communication of affordable priceto control the smart home appliances by immobilized people from neck to toes.

Objective. The goal of the work is to manage smart home appliances via brain-to-thing communication with EEG non-invasive electrodes, edge IoT devices, and MQTT protocol if the brain and eye control of the disabled work normally.

Method. A non-invasive Sichiray TGAM brainwave EEG sensor kit captures signals and then transmit them via Bluetooth to the HC-05 module connected to the Arduino Mega microcontroller. Information about edge IoT devices is presented to the disabled on the LCD 1602 display wired to the same Arduino Mega. The disabled person chooses the option shown on display via the double blink that is detected if the quality of signal equals zero and low/mid gamma waves are less than ten in three consecutive Bluetooth packets. Control commands are sent from Arduino Mega (MQTT publisher) to the edge IoT devices (MQTT subscribers) that analyze them and start a specific operation like opening a door and turning the alarm on/off.

Results. Five females and five males of different ages from 8 to 59 years old examined the control of smart home appliances with the Sichiray TGAM brainwave sensor kit. Everyone successfully handled the Sichiray headset and showed satisfaction with the brain-to-thing system.

Conclusions. In this work, a smart home concept for immobilized people was developed using the brain-to-thing approach and the MQTT communication between the MQTT publisher, Sichiray TGAM brainwave EEG sensor kit connected via Bluetooth to the Arduino Mega microcontroller, and edge IoT devices total priced at USD 150. The most likely prospect of the presented work is to produce the sample that is ready to market.

Author Biographies

D. A. Zubov, University of Central Asia, Bishkek, Kyrgyzstan

Dr. Sc., Associate Professor of the Department of Computer Science

M. S. Qureshi, University of Central Asia, Bishkek, Kyrgyzstan

Dr. Sc., Assistant Professor of the Department of Computer Science

U. Köse, Süleyman Demirel University, Isparta, Turkey

Dr. Sc., Associate Professor the Department of Computer Engineering

A. I. Kupin, Kryvyi Rih National University, Kryvyi Rih, Ukraine

Dr. Sc., Professor, Head of the Department of Computer Systems and Networks


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How to Cite

Zubov, D. A., Qureshi, M. S., Köse, U., & Kupin, A. I. (2022). PROTOTYPING SMART HOME FOR IMMOBILIZED PEOPLE: EEG/MQTT-BASED BRAIN-TO-THING COMMUNICATION. Radio Electronics, Computer Science, Control, (2), 90.



Neuroinformatics and intelligent systems