Brain Computer Interface Based Home Automation System Using Raspberry Pi

Umme Habiba Maginmani¹ , Mujamil Dakhani²

Section:Research Paper, Product Type: Journal-Paper
Vol.8 , Issue.5 , pp.70-76, Oct-2020

Online published on Oct 31, 2020

Copyright © Umme Habiba Maginmani, Mujamil Dakhani . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
 

View this paper at   Google Scholar | DPI Digital Library

XML View     PDF Download

How to Cite this Paper

Abstract :
In our general public there are more individuals endured by immobile sicknesses causes them a few handicaps like they can`t talk and unfit to move truly and incapable to communicate their regular essential needs, however they can even now utilize their eyes and now and again move their heads. This paper show how it is working under the guideline of Brain-Computer Interface (BCI). Our model encourages them to work home appliances by having eye blink. This framework is having a center framework as Raspberry Pi. However, the machines can be picked by having need for apparatuses. In this application, Machines are turned on by having one blink and turned off by making double blink. In this framework, need as a request for light, fan, and Tv. We can work more machines by providing moreover request of needs.

Key-Words / Index Term :
Brain, Brain-Computer Interface, Eye–blink, Raspberry Pi, Bluetooth, Home Appliances, Mind-wave mobile, Brain sense

References :
[1] Jonathan R. Wolpaw, Niels Birbaumer, Dennis J. McFarland, Gert Pfurtscheller, Theresa M. Vaughan, “Brain–computer interfaces for communication and control”, Clinical Neurophysiology 2002.
[2] M. RajyaLakshmi, T. Kameswara Rao, Dr. T. V. Prasad, “Exploration of Recent Advances in The Field of Brain Computer Interface”, IOSR J. of Computer Engg., Vol.8, Issue 2, 2012.
[3] T. Kameswara Rao, M. Rajya Lakshmi, Dr. T. V. Prasad, “An Exploration of Brain Computer Interface and Its Recent Trends”, Int. J. of Advanced Research in Artificial Intelligence, Vol. 1, Issue 8, 2012.
[4] Jonathan R.Wolpaw , Niels Birbaumer, William J.Heetderks, Dennis J.McFarland, P. Hunter Peckham, Gerwin Schalk, Emanuel Donchin, Louis A. Quatrano, Charles J. Robinson, and Theresa M. Vaughan, Brain–Computer Interface Technology: A Review of the First International Meeting, IEEE Trans. on Rehabilitation Engg, Vol. 8, No. 2, 2000
[5] Leigh R. Hochberg and John P. Donoghue, “Sensors for Brain-Computer Interfaces”, IEEE Engineering in Medicine and Biology Magazine. Sep/Oct 2006.
[6]M. Rajya Lakshmi, T. V. Prasad and V. Chandra Prakash, "Survey on EEG Signal Processing Methods", International Journal of Advanced Research in Computer Science and Software Engineering, 2014.
[7]F Lotte et al., "A review of classification algorithms for EEG based brain–computer interfaces: a 10 year update", J. Neural Eng., 2018.
[8] Rajesh Singla, Neha Sharma, Navleen Singh Rekhi “A Review Based on Function Classification of EEG Signals” (IJCSIS) International Journal of Computer Science and Information Security, Vol. 11, No. 5, May 2013
[9] A. Z. Alkar and U. Buhur, “An internet based wireless home automation system for multifunctional devices,” IEEE Trans. Consum. Electron., vol. 51, no. 4, pp. 1169–1174, Nov. 2005.