A REAL-TIME DRIVER DROWSINESS DETECTION SYSTEM

OBUN, PRISCA OSOWOAYIP (2025) A REAL-TIME DRIVER DROWSINESS DETECTION SYSTEM. Other thesis, GODFREY OKOYE UNIVERSITY, ENUGU..

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Abstract

During long driving sessions at nighttime the critical reason behind many car incidents becomes driver fatigue. This research introduces a live driver fatigue system based on Artificial Intelligence vision methods which track facial indicators along with physical behavior signals for sleepiness. Eye closure and yawning and head nodding detection come from a system that integrates Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM) networks. The system produces real-time alerts when drowsiness indicators achieve established thresholds which aids in preventing crashes along with improving safety conditions on the roads.

Item Type: Thesis (Other)
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Natural and Applied Sciences
Depositing User: Uchenna Eneogwe
Date Deposited: 30 May 2026 23:17
Last Modified: 30 May 2026 23:17
URI: http://eprints.gouni.edu.ng/id/eprint/5683

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