Abstract

Various factors can cause accidents, but the main factor that dominates the causes of accidents is the driver's actions, especially continuing to drive in a state of drowsiness. To avoid accidents, a safety driving system is needed to inform the driver when in a drowsiness condition. This paper reports on the early stages of developing a safety driving system implemented in an embedded computer vision method. We calculated the perclos from the ear and the ear from eye landmarks. We obtained significant results from the perclos when the driver had driven for 3 hours. The average perclos for 3 hours is 0.152, while after more than 3 hours driving is 0.590. This result is significant in distinguishing the driver's condition, especially in developing rules for a safety driving system. The processing speed we obtained in extracting eye landmarks was 189.91 milliseconds at a speed of 10 fps. This speed is fast enough to detect drowsiness. Furthermore, developing a drowsiness detection system will involve a professional driver subject who works as a transporter and adding psychological signal characteristics such as ECG signal and driving behavior modality parameters in producing a multimodal based decision-making system.

Original languageEnglish
Title of host publicationProceeding of the International Conference on Computer Engineering, Network and Intelligent Multimedia, CENIM 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages117-121
Number of pages5
ISBN (Electronic)9781665476508
DOIs
Publication statusPublished - 2022
Event2022 International Conference on Computer Engineering, Network and Intelligent Multimedia, CENIM 2022 - Surabaya, Indonesia
Duration: 22 Nov 202223 Nov 2022

Publication series

NameProceeding of the International Conference on Computer Engineering, Network and Intelligent Multimedia, CENIM 2022

Conference

Conference2022 International Conference on Computer Engineering, Network and Intelligent Multimedia, CENIM 2022
Country/TerritoryIndonesia
CitySurabaya
Period22/11/2223/11/22

Keywords

  • drowsiness detection
  • eye aspect ratio
  • perclos
  • safety driving system

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