Publication:
Multi-source information fusion for drowsy driving detection based on wireless sensor networks

Simple item page
dc.citedby18
dc.contributor.authorWei L.en_US
dc.contributor.authorMukhopadhyay S.C.en_US
dc.contributor.authorJidin R.en_US
dc.contributor.authorChen C.-P.en_US
dc.contributor.authorid55726997800en_US
dc.contributor.authorid24479163700en_US
dc.contributor.authorid6508169028en_US
dc.contributor.authorid23491392900en_US
dc.date.accessioned2023-12-28T04:13:07Z
dc.date.available2023-12-28T04:13:07Z
dc.date.issued2013
dc.description.abstractDrowsy driving is a major cause of road accidents. This paper analyses the drivers' behavior in the state of fatigue driving and introduces the latest developments of drowsy driving detection technology. In this study we also propose a drowsy driving detection based on the driver's physiological signals such as eye activity measures, the inclination of the driver's head, sagging posture, heart beat rate, skin electric potential, and electroencephalographic (EEG) activities, as well as response characteristics, decline in gripping force on the steering wheel and lane keeping characteristics. By developing a hierarchical model that is able to collect the sensing data, analyze the driving behavior and the reactions to the driver, it can provide a safe and a comfortable driving environment. Combining different indications of drowsiness and processing the contextual information to predict whether a driver is drowsy, the system not only issues a warning for the driver, but also provides the drowsy driving information to transportation control center and other vehicles if necessary. � 2013 IEEE.en_US
dc.description.natureFinalen_US
dc.identifier.ArtNo6727771
dc.identifier.doi10.1109/ICSensT.2013.6727771
dc.identifier.epage857
dc.identifier.scopus2-s2.0-84897880672
dc.identifier.spage850
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84897880672&doi=10.1109%2fICSensT.2013.6727771&partnerID=40&md5=896cfbaf922695733e56594548e18399
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/29443
dc.pagecount7
dc.sourceScopus
dc.sourcetitleProceedings of the International Conference on Sensing Technology, ICST
dc.subjectdriver behaviour
dc.subjectdrowsy driving
dc.subjectwireless sensor networks
dc.subjectAutomobile drivers
dc.subjectHierarchical systems
dc.subjectHighway accidents
dc.subjectPhysiological models
dc.subjectContextual information
dc.subjectDriver behaviour
dc.subjectDrowsy driving
dc.subjectElectroencephalographic (EEG)
dc.subjectMulti-source information fusion
dc.subjectPhysiological signals
dc.subjectResponse characteristic
dc.subjectTransportation control
dc.subjectWireless sensor networks
dc.titleMulti-source information fusion for drowsy driving detection based on wireless sensor networksen_US
dc.typeConference paperen_US
dspace.entity.typePublication
Files
Collections
SCOPUS