Development of a Raspberry Pi-Based Circuit to Detect Drowsiness in Drivers and Prevent Traffic Accidents

dc.contributor.authorE. Brizuela-Guzmán
dc.contributor.authorVallejo-Cristofer A. Cabrera
dc.contributor.authorM. Malo-García
dc.contributor.authorA. Rodríguez-Zavala
dc.contributor.authorD.A. López-Luna
dc.contributor.authorD. Iniestra-Martínez
dc.contributor.authorM. García-Pérez
dc.contributor.authorM.O. Falcón-Antonio
dc.coverage.spatialBolivia
dc.date.accessioned2026-03-22T19:17:19Z
dc.date.available2026-03-22T19:17:19Z
dc.date.issued2023
dc.description.abstractDrowsiness is one of the main causes of traffic accidents. This work presents a Raspberry Pi 4-based drowsiness detection system that uses closed eyes detection to identify drowsy drivers. The system uses a camera module to capture images of the driver's face and then applies the Haar cascade algorithm to detect if the driver's eyes are closed for more than a certain amount of time, in case of exceeding that time, the system will sound an alarm to alert the driver, and with this, it can prevent accidents by promptly alerting the driver if they have fallen asleep. Furthermore, it is highlighted that the device does not pose a visual obstruction or cause any discomfort due to its size and operation.
dc.identifier.doi10.1109/ieeeconf60929.2023.10525428
dc.identifier.urihttps://doi.org/10.1109/ieeeconf60929.2023.10525428
dc.identifier.urihttps://andeanlibrary.org/handle/123456789/75167
dc.language.isoen
dc.sourceUniversidad La Salle
dc.subjectRaspberry pi
dc.subjectHaar-like features
dc.subjectALARM
dc.subjectComputer science
dc.subjectDrunk driving
dc.subjectFalse alarm
dc.subjectComputer vision
dc.subjectReal-time computing
dc.subjectSimulation
dc.subjectComputer security
dc.titleDevelopment of a Raspberry Pi-Based Circuit to Detect Drowsiness in Drivers and Prevent Traffic Accidents
dc.typearticle

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