Design of Video Detection for Drowsy Prevention Based on Car Driving

Main Article Content

Byeongtae Ahn

Abstract

In this paper, a drowsiness prevention system was developed to prevent large-scale
disasters in traffic accidents. And drowsiness was predicted using face recognition face
recognition technique and eye blink recognition technique, and prediction was improved by
applying machine learning to improve drowsiness prediction. Additionally, the CO2 sensor
chip was used to detect additional drowsiness prevention. In addition, STT (Speach To Text)
was applied using voice recognition technology so that the driver can apply for a desired
music or broadcast or make a phone call in order to break drowsiness while driving.

Downloads

Download data is not yet available.

Metrics

Metrics Loading ...

Article Details

How to Cite
Byeongtae Ahn. (2021). Design of Video Detection for Drowsy Prevention Based on Car Driving. Turkish Journal of Computer and Mathematics Education (TURCOMAT), 12(14), 5807–5816. https://doi.org/10.17762/turcomat.v12i14.11810
Section
Research Articles

Most read articles by the same author(s)

1 2 > >>