2.1.1 the Mindwave Mobile via series of

2.1.1 Controlling electrical devices with human brainwaves:
Keerthana, et al. (2010) of VIT University developed a way of switching electrical appliances
on and off using brainwaves. Our project uses a Neurosky Mindwave Mobile to
sense brainwaves and its transmission. The project starts with the Mindwave Mobile.
Raw brainwave data is inserted to the Mindwave Mobile via series of processing algorithms
for making it suitable for microcontroller use. The data translated that is resulted
is fed into a microcontroller which has an electrical appliance connected to it through a
relay.
The user can turn the electrical appliance on and off using brainwaves. This
project also tests the Mindwave Mobiles accuracy in terms of translating brainwave data
into usable ones. A series of tests like changing intensities of Gamma and Beta waves is
made and the Mindwave Mobile manages to pass all of them. This project do not use
other features of blink detection.
The max transmission range of Bluetooth and the limited range of brainwaverelated
data that the Mindwave Mobile can sense is the limitation of the project. The
Mindwave Mobile is probably the most affordable EEG headset which is available is
aless robust and comprehensive feature set. PC-based hands-free short messaging
system through facial movements using Emotiv EPOC :
Emotivs EPOC headset detects specific facial movements and the developer
gets the access to all possible controls. It uses Specific facial movements like up, down,
left and right directions. A message is sent to the recipient via the GSM module.
This project is primarily made for people with motor handicaps but anyone
who wishes to have a hands-free way of communicating with others can use this. The
cost of project is its biggest limitation. Emotivs EPOC headset detects a larger range of
brainwaves but it is extremely expensive and hence unavailable to most students.
2.1.2 Remote-Controlled Car :
Hector Dominguez (2014) developed a Bluetooth remote-controlled RC car for his summer
studys final project. The main components of this project include an ATmega1284, an
L293D motor controller, an HC-05 Bluetooth module, 9V DC motors, a 5V regulator, 9V
batteries and a car chassis. On the software side, he used AVR Studio 6, the Android
SDK and Eclipse Dominguezs project uses of a Bluetooth module to send and receive
signals through the Android application that serves as the remote controller of the RC
car.
The project specifically uses PWM signals to drive the DC motors on the RC
car. The Android application utilized Android Bluetooth API and was made with Java
and XML. The RC cars several features include the ability to move forward, backwards,
left and right, a 5-second turbo button, wheel arrangement buttons and headlights.
2.1.3 Mobile controlled wheelchair:
Roger Achkar and his team (2015) developed a smartphone-controlled wheelchair with
an auto-movement feature that allows you to save a predefined path that the wheelchair
will take. The wheelchair has two DC motors attached to it with two relays attached to
each. One relay operates the DC motor is connected to and the second one switches the
motors phase to go forward or backward. An IP cam is mounted on the wheelchair, which
connects wirelessly to a router connected to the Arduino board. The mounted IP adds
video monitoring to the wheelchair that can be used by the wheelchair administrator to
monitor the current location of the patient.
Limitations of this project is that the lack of an obstacle-sensing feature that
would make its auto-movement more effective. Also, motor-handicapped people with no
limbs have no way of using the wheelchair as it requires them to use a smartphone to
control it. This wheelchair is limited to patients with fully-functional hands.
2.1.4 Android-controlled monitoring toy car via WIFI
Rosevir Ceballos and his team (2016) developed an Android-controlled RC car with video
streaming via Wireless Fidelity (WIFI) and an Android application to control the RC
car. It basically is an RC car with an IP camera and a router mounted on it that can
be controlled through an Android smartphone application. They made clever use of a
smartphones accelerometer and gyroscope by using it as the steering apparatus of the
RC car. Apart from being able to stream directly to the Android application, Ceballos
project is also able to save video to an SD card attached to the IP camera. The IP camera
also features night vision and the ability to be panned through the Android application.
A major limitation in Ceballos project was the motorcycle lead-acid battery
they used to power their car. It can only power the system incessantly for short periods of
time before requiring to be charged again. Using other types of batteries more appropriate
for RC cars such as lithium polymer ones will improve battery life. Another limitation is
the max distance between the smartphone controller and the RC car itself it is limited to
the max transmission range of WIFI. 

2.1.1 Controlling electrical devices with human brainwaves:
Keerthana, et al. (2010) of VIT University developed a way of switching electrical appliances
on and off using brainwaves. Our project uses a Neurosky Mindwave Mobile to
sense brainwaves and its transmission. The project starts with the Mindwave Mobile.
Raw brainwave data is inserted to the Mindwave Mobile via series of processing algorithms
for making it suitable for microcontroller use. The data translated that is resulted
is fed into a microcontroller which has an electrical appliance connected to it through a
relay.
The user can turn the electrical appliance on and off using brainwaves. This
project also tests the Mindwave Mobiles accuracy in terms of translating brainwave data
into usable ones. A series of tests like changing intensities of Gamma and Beta waves is
made and the Mindwave Mobile manages to pass all of them. This project do not use
other features of blink detection.
The max transmission range of Bluetooth and the limited range of brainwaverelated
data that the Mindwave Mobile can sense is the limitation of the project. The
Mindwave Mobile is probably the most affordable EEG headset which is available is
aless robust and comprehensive feature set. PC-based hands-free short messaging
system through facial movements using Emotiv EPOC :
Emotivs EPOC headset detects specific facial movements and the developer
gets the access to all possible controls. It uses Specific facial movements like up, down,
left and right directions. A message is sent to the recipient via the GSM module.
This project is primarily made for people with motor handicaps but anyone
who wishes to have a hands-free way of communicating with others can use this. The
cost of project is its biggest limitation. Emotivs EPOC headset detects a larger range of
brainwaves but it is extremely expensive and hence unavailable to most students.
2.1.2 Remote-Controlled Car :
Hector Dominguez (2014) developed a Bluetooth remote-controlled RC car for his summer
studys final project. The main components of this project include an ATmega1284, an
L293D motor controller, an HC-05 Bluetooth module, 9V DC motors, a 5V regulator, 9V
batteries and a car chassis. On the software side, he used AVR Studio 6, the Android
SDK and Eclipse Dominguezs project uses of a Bluetooth module to send and receive
signals through the Android application that serves as the remote controller of the RC
car.
The project specifically uses PWM signals to drive the DC motors on the RC
car. The Android application utilized Android Bluetooth API and was made with Java
and XML. The RC cars several features include the ability to move forward, backwards,
left and right, a 5-second turbo button, wheel arrangement buttons and headlights.
2.1.3 Mobile controlled wheelchair:
Roger Achkar and his team (2015) developed a smartphone-controlled wheelchair with
an auto-movement feature that allows you to save a predefined path that the wheelchair
will take. The wheelchair has two DC motors attached to it with two relays attached to
each. One relay operates the DC motor is connected to and the second one switches the
motors phase to go forward or backward. An IP cam is mounted on the wheelchair, which
connects wirelessly to a router connected to the Arduino board. The mounted IP adds
video monitoring to the wheelchair that can be used by the wheelchair administrator to
monitor the current location of the patient.
Limitations of this project is that the lack of an obstacle-sensing feature that
would make its auto-movement more effective. Also, motor-handicapped people with no
limbs have no way of using the wheelchair as it requires them to use a smartphone to
control it. This wheelchair is limited to patients with fully-functional hands.
2.1.4 Android-controlled monitoring toy car via WIFI
Rosevir Ceballos and his team (2016) developed an Android-controlled RC car with video
streaming via Wireless Fidelity (WIFI) and an Android application to control the RC
car. It basically is an RC car with an IP camera and a router mounted on it that can
be controlled through an Android smartphone application. They made clever use of a
smartphones accelerometer and gyroscope by using it as the steering apparatus of the
RC car. Apart from being able to stream directly to the Android application, Ceballos
project is also able to save video to an SD card attached to the IP camera. The IP camera
also features night vision and the ability to be panned through the Android application.
A major limitation in Ceballos project was the motorcycle lead-acid battery
they used to power their car. It can only power the system incessantly for short periods of
time before requiring to be charged again. Using other types of batteries more appropriate
for RC cars such as lithium polymer ones will improve battery life. Another limitation is
the max distance between the smartphone controller and the RC car itself it is limited to
the max transmission range of WIFI. 

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