| dc.description.abstract | Intoxicated driving is dangerous ,
drowsiness is an another form of fatigue
which claims hundreds of lives every year in
fetal crashes.US National Highway Traffic
Safety Administration has estimated that a
total of 100,000 vehicle crashes each year are
a direct result of driver drowsiness (Anon.,
n.d.).In order to prevent from these
devastating accidents we should identify the
drowsy moment and control it before mishap
happen. For that driver drowsiness state
should be monitored. But detecting
drowsiness using face image behavior or
drivers eye blinking is not accurate enough.
Though we can measure rapid eye
movement sleep and slow eye movement
sleep, we cannot measure no eye movement
sleep. Researchers have found that eye open
sleep is quite common, so this human drowsy
behavior also should be measured through
the system (Anon., 2019). After analyzing
drowsy behavior, has classified as normal,
slightly drowsy and highly drowsy. Mention
drowsy detection methods identify
drowsiness when highly drowsy. But it’s
rarely possible to prevent from the highly
drowsy state. Even if they prevent from that,
it’s too late to prevent from mishap. So the
exciting drowsiness detection system is
absolute. Now we have accurate sensors to
detect heart rate, EEG, EOG Etc. Through
those we can measure drowsiness in normal
and slightly drowsy states where it’s possible
to prevent from mishap. Sensor signals will
be processed by the desktop application and
identify whether the driver is drowsy or not.
For more accuracy, place the sensor in the
steering wheel. The aim is an accurate
drowsiness detection system which covers
the weakness of absolute systems. | en_US |
