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Survey on Wearable Sensor Technologies on Driver Drowsiness Detection

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dc.contributor.author Gunathilaka, PDST
dc.contributor.author Kalansooria, P
dc.date.accessioned 2020-12-31T22:19:14Z
dc.date.available 2020-12-31T22:19:14Z
dc.date.issued 2020
dc.identifier.uri http://ir.kdu.ac.lk/handle/345/2995
dc.description Article Full Text en_US
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
dc.subject Drowsiness Detection en_US
dc.subject No-eye movement en_US
dc.subject highly drowsy en_US
dc.subject Heartrate. en_US
dc.title Survey on Wearable Sensor Technologies on Driver Drowsiness Detection en_US
dc.identifier.journal KDU-IRC-2020 en_US
dc.identifier.pgnos 485-492 en_US


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