Abstract:
Drowsiness is one of the major risk factors causing accidents that result in a large
number of damage. Drivers and industrial workers ,who do not take regular breaks when driving
or work for long time probably have a large effect on several mishaps occurring from
drowsiness.
Therefore, advanced technology to reduce these accidental rates is a very
challenging problem.
The purpose of this project is to develop a portable wireless device that can
automatically detect the drowsiness in real time by using the electrooculogram (EOG).
These include the mechanism that take the dynamic signal of the eye and turn it
into an electrical signal through electrodes placed around the eye to monitor the eye movement.
The signal was sent via the wireless communication of zigbee to a standalone microcontroller to
analyze drowsiness using Convolutional Neural Networks .The alarm will ring when the
drowsiness occurs. Such application is helpful to reduce losses of casualty and property.
Description:
no of pages 47, Cd , اتصالات 1/2018 , in the store