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Smart city article details
| Title | Real-Time Driver Drowsiness Detection Using Wearable Technology |
|---|---|
| ID_Doc | 44351 |
| Authors | Misbhauddin M.; AlMutlaq A.; Almithn A.; Alshukr N.; Aleesa M. |
| Year | 2019 |
| Published | ACM International Conference Proceeding Series |
| DOI | http://dx.doi.org/10.1145/3368756.3369081 |
| Abstract | Road accidents are a worldwide problem, consequences of which can lead to death. One of the reasons drivers experience near-miss or real accidents is because of drowsy driving. Drowsy driving is considered as a major problem that not only affects the driver but also threatens the life of others and cause damage to the country's infrastructure. In this paper, we propose a wearable-based solution that tracks the user's state of activeness and gives real-time feedback. Our proposed solution tracks and records the user's Heart Rate Variability and the Galvanic Skin Response to identify the user's state of activeness. The proposed mobile application interfaces with the wearable device to gather user data and perform analysis. If results are lower than the expected threshold, the user is informed by auditory feedback. © 2019 Association for Computing Machinery. |
| Author Keywords | Drowsiness detection; Galvanic Skin Response; Heart Rate Variability; Wearable Technology |
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