Review of Related Literature According to CITATION Pad151 l 1033

Review of Related Literature
According to CITATION Pad151 l 1033 (Padmajothi & Pradeep, 2015) A rapid growth of research on smart houses is proposed and developed to provide various kinds of environmental control systems. Some environmental control systems in a smart house employed radio frequency identification (RFID), external sensor modules, and voice recognition as the controlled signals.

An Electroencephalogram (EEG) based smart living environmental control system to auto-adjust the living environment is proposed CITATION Che101 l 1033 (Chen, et al., 2010) in the journal article. CITATION Che101 l 1033 (Chen, et al., 2010)Figure 3. Detailed architecture of embedded signal processing unit that is implemented on the OMAP1510 platform. (a) Interactive flow control unit that includes EEG data recovery, data flow control, task management, peripheral control and TCP/IP. (b) Real-time physiological signal processing unit that includes down-sampling, Hanning window multiplier, short-time FFT, normalization, moving average, ICA decomposition and drowsy state estimator, etc. CITATION Che101 l 1033 (Chen, et al., 2010)The EEG based sensors record these signals for various activities. The generated signals have different frequencies based on the intensity of the action. CITATION Ahm16 l 1033 (Ahmad, Masood, Kathia, Zafar, & Zahid, 2016)
Figure.4 depicts the block diagram of data transmission in the system CITATION Ahm16 l 1033 (Ahmad, Masood, Kathia, Zafar, & Zahid, 2016) CITATION Hri18 l 1033 (Hridya, Vipitha, & Vidya, 2018)It has basically an EEG sensor circuit and a microcontroller. EEG signal is acquired using electrodes. Our system uses 3 electrode scheme. The electrodes are placed in 3 forehead position. The EEG signal is filtered and amplified using amplifiers .The filtered and amplified signal is fed to a microcontroller (Nano board).The microcontroller converts the analog signal to digital signal CITATION Hri18 l 1033 (Hridya, Vipitha, & Vidya, 2018)And one of the journal article that we are using as a reference tackled about the Brain computer Interface. A BCI is a computer-based system that acquires brain signals, analyzes them, and translates them into commands that are relayed to an output device to carry out a desired action CITATION Kru12 l 1033 (Krusienski, Shih, & Wolpaw, 2012). By 2006, a microelectrode array was implanted in the primary motor cortex of a young man with complete tetraplegia after a C3-C4 cervical injury. Using the signals obtained from this electrode array, a BCI system enabled the patient to open simulated e-mail, operate a television, open and close a prosthetic hand, and perform rudimentary actions with a robotic arm.11 In 2011, Krusienski and Shih12demonstrated that signals recorded directly from the cortical surface (Electrocorticography ECoG ) can be translated by a BCI to allow a person to accurately spell words on a computer screen. Brain-computer interface research is growing at an extremely rapid rate, as evidenced by the number of peer-reviewed publications in this field over the past 10 years CITATION Kru12 l 1033 (Krusienski, Shih, & Wolpaw, 2012).
Since the beginning of the journey of home automation researchers found many ideal systems to put in a home automated household that varies from the easiest technology to the hardest technology. The difficulty of technology has a significant connection to the cost of the system. The more the complex the system is the more it will cost you.
Short Message Service (SMS) Based Home Security System is one of the low cost system for the home automation. This system uses a Passive infrared sensor (PIR sensor). Passive infrared is a type of sensor that measures the light radiating from its point of view. They are commonly used in motion sensors or detectors. The PIR sensors have the widest view than other sensors and are most sensitive and advanced option. Thus the PIR sensor lights are ideal to any home security system and were selected for present automated home CITATION Azi111 l 1033 (Azid & Kumar, 2011).

One of the journal articles tackles about WiFi being the connection of a smart home system. There are two main parts, one is the main server or which controls the entire system within the house, via LAN or internet. Another part is hardware interface module, which provides connection on what will be controlled on the system. This system provides security and power management throughout the house (ElShafee & Hamed, 2012).

This study can be related on how it will be used as there will be several components which can be controlled, such as alarms and appliance. Basic knowledge about computer is needed which is common for most people even in elderlies. Microsoft windows is the operation system that will be used. Accounts per user will made, on which administrator will also exist as it will control all of the existing accounts that has an access on the control system. Programming technologies such as, HTML, ASP and CSS are implemented. An integrated circuit will used, which is the arduino. The programming language that will be implemented is the ASP.net, using the Microsoft visual studio 2010. For the house system logs, text file will be used. By using the arduino, it was built by C language, which is responsible on what is happening on the sensors of the components within the house (ElShafee & Hamed, 2012).

By using the PIC16F73 microcontroller, the appliances used in the house can be controlled by using the programming language, C language. The use of the appliances can be interpret as on/off as it basically turns on and off the appliances. All the actions that will take effect to the appliances is by a software that is controlled by a computer (M. R. Alam, F. Kader, K. T. Ahmmed, & N.A. Jahan, 2013).

One of the article discuss that having a smart home system eases the way of everyday living. Transmitter will used here to connect the appliances and alarms for it to be controlled, by the use of remotes, or keypads. Implementation of the system requires the compatibility of the transmitter and the appliances. Checking of the product before purchasing is needed since the technology must be compatible with each other. An artificial intelligence will be made for the protection of the user from health problem. It will also detect the location of a fire if a fire happens. A smart home will also protects the user on its important files, from external attacks such as DDoS (R.J. Robles, T. Kim, 2010).

Global System for Mobile communications (GSM) is used for the user to receive an SMS or email whether there is a theft or a disaster occur in the house such as fire and leakage of gas. For it to be detected, there is a camera implemented within the house, and when there is a movement, the user receives an SMS or email. Another proposal which uses Atmega644p a microprocessor, and GSM-GPS module on which handles the alarms within the house (J. Bangali & A. Shaligram, 2013).
By a biometric scanner, on which it detects the hand print of an authorized user, has a full access on all electronics within the house (C. Matsuura, G. Cooper & T. Leishman, 2010).

Another topic related to home automation is internet of things. The interconnection by means of the Internet of registering gadgets inserted in ordinary articles, empowering them to send and get information.
CITATION Kan151 l 1033 (Kanhere, et al., 2015)The raw brain signals are forwarded to the cloud server via Internet access. The cloud server uses a person-dependent pertained deep learning model for analyzing the raw signals. CITATION Kan151 l 1033 (Kanhere, et al., 2015)The analysis results translated signs could be utilized for inciting capacities in an extensive variety of Internet of Things (IoT) candidates, for example, smart city.

Another Brain Computer Interface (BCI) related research topic is P300 based Brain Computer Interface for Disabled. BCI is a communication system that recognizes user’s command only from his or her brainwaves and reacts according to them CITATION Cha12 l 1033 (Chaudhari, Deore, ; Gawali, 2012).

A Brain Computer Interface (BCI) allows people suffering from neuromuscular disorder to use electroencephalographic (EEG) activity to control external device such as robots, virtual environment or spelling devices, video games, wheelchairs, mobile phone control etc. CITATION Cha12 l 1033 (Chaudhari, Deore, ; Gawali, 2012)P300 base BCI showed that patients suffering from amyotrophic lateral sclerosis (ALS) can use a BCI to control a spelling device and communication with their environment. CITATION Dis07 l 1033 (Diserens, Ebrahimi, Hoffmann, ; Vesin, 2007)According to the research studies that were done in the journal articles, there are many different possible ways to convert a normal house to an automated one. And the aims of this study is to generate an effective and convenient household for the seniors and the disabled person.

The identified studies that were talked about in this research is related to the research paper we are doing. Several ideas about how someone’s life can be more convenient is slowly being recognized by the people around the world. And that every research is connected to one another.

The main objective of our research is about the more convenient way our elder and disabled person live their lives is. Therefore brain wave sensors and such is a great and easy way to manipulate for them.
To wrap this Review of Related Literature, the stated research above is very important as it will be the base of future researchers.

References
ElShafee, A., Hamed K. A. , (2012), Design and implementation of a WiFi based home automation system, 5,
Azid, S.I. , Kumar, S. (2011), Analysis and performance of a low cost SMS based home security system.
Bangali, J., Shaligram, A. (2013), Deisgn and implementation of security for smart home based on GSM technology, SERSC, 7(2013), 201-208
Robles, R. J., Kim, T. (2010), A review on security in smart home development, 15.
Bennet, R. W., Griffith, L. M., Lund, A. M. (2009), System and method for home automation and security, United States patent
Jose, A. C., Malekian, R. (2015), Smart home automation security: a literature review, 5(4)
Matsuura, C., Cooper, G., Leishman, T. (2010), Home automation security system and method, United States patent application publication
Brennan, C. P., McChullag P.J., Gallway L. & LightBody, G., (2015), Promoting autonomy in a smart home environment with smarter interface, IEEE
Aydin, E. A., Bay, O. F., Guler, I. (2014), Region based brain computer interface for a home control application, IEEE
Kiran, T. R., Rajesh, T. A., (2016), brain wave enabled multi-functional, communication, controlling and speech signal generation system, IEEE
Kaur, S., Singh, R., Khairwal N., Jain P., (2016), Advanced computational intelligence, Home automation and security system, 3(3)References
BIBLIOGRAPHY Ahmad, M., Masood, M. H., Kathia, M. A., Zafar, R., & Zahid, A. (2016). BRAIN COMPUTER INTERFACE BASED SMART HOME CONTROL USING EEG SIGNAL . SCIENCE INTERNATIONAL (LAHORE).

Azid, S. I., & Kumar, S. (2011). Analysis and Performance of a Low Cost SMS Based Home Security System . International Journal of Smart Home .

Chaudhari, R., Deore, R., & Gawali, B. (2012). P300 based Brain Computer Interface for Disabled . International Journal of Advanced Research in Computer Engineering & Technology .

Chen, S. A., Chen, T. C., Lin, C. T., Lin, F. C., Lu, S. W., & Ko, L. W. (2010). EEG-based Brain-computer Interface for Smart Living Environmental Auto-adjustment . ournal of Medical and Biological Engineering.

Diserens, K., Ebrahimi, T., Hoffmann, U., & Vesin, J. M. (2007). An efficient P300-based brain–computer interface for disabled subjects. International Journal of Advanced Research in Computer Engineering & Technology .

Hridya, S. G., Vipitha, E. P., & Vidya, G. (2018). BRAIN CONTROLLED HOME AUTOMATION SYSTEM . International Research Journal of Engineering and Technology (IRJET) .

Kanhere, S., Liu, Y., Yao, L., Sheng, M., Zhang, S., & Zhang, X. (2015). Internet of Things Meets Brain-Computer Interface: A Uni?ed Deep Learning Framework for Enabling Human-Thing Cognitive Interactivity. JOURNAL OF L ATEX CLASS FILES.

Krusienski, D. J., Shih, J. J., & Wolpaw, J. R. (2012). Brain-Computer Interfaces in Medicine. Mayo Clin Proceedings.

Padmajothi, V., & Pradeep, S. (2015). BRAIN CONTROLLED SMART HOME NETWORK BASED ON COGNITIVE STATE . International Journal of Emerging Technology in Computer Science & Electronics (IJETCSE) .