Driver Drowsiness Detection using Evolutionary Machine Learning: A Survey
One of the factors that kills hundreds of people every year is driving accidents caused by drowsy drivers. There are different methods to prevent this type of accidents. Recently Machine Learning (ML) and Deep Learning (DL) have emerged as very effective and valuable approaches for detecting driver...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
EDP Sciences
2024-01-01
|
| Series: | BIO Web of Conferences |
| Online Access: | https://www.bio-conferences.org/articles/bioconf/pdf/2024/16/bioconf_iscku2024_00007.pdf |
| _version_ | 1797213282216443904 |
|---|---|
| author | Yasir Jumhaa Maha Majeed Osama Taima Alaa |
| author_facet | Yasir Jumhaa Maha Majeed Osama Taima Alaa |
| author_sort | Yasir Jumhaa Maha |
| collection | DOAJ |
| description | One of the factors that kills hundreds of people every year is driving accidents caused by drowsy drivers. There are different methods to prevent this type of accidents. Recently Machine Learning (ML) and Deep Learning (DL) have emerged as very effective and valuable approaches for detecting driver drowsiness. Moreover, the optimization of machine learning (ML) and deep learning (DL) models may be achieved through the utilization of evolutionary algorithms (EA). This survey aims to offer an overview of recent studies in driver drowsiness detection-based machine learning and deep learning models that have been improved by EA. This survey divides the approaches for detecting drowsiness into two groups: those that rely on ML, and DL, and those that rely on models-based deep learning and machine learning that are optimized by evolutionary algorithms. |
| first_indexed | 2024-04-24T10:55:48Z |
| format | Article |
| id | doaj.art-dfcdbeed82be4eccbe38ca01e1552b90 |
| institution | Directory Open Access Journal |
| issn | 2117-4458 |
| language | English |
| last_indexed | 2024-04-24T10:55:48Z |
| publishDate | 2024-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | BIO Web of Conferences |
| spelling | doaj.art-dfcdbeed82be4eccbe38ca01e1552b902024-04-12T07:36:28ZengEDP SciencesBIO Web of Conferences2117-44582024-01-01970000710.1051/bioconf/20249700007bioconf_iscku2024_00007Driver Drowsiness Detection using Evolutionary Machine Learning: A SurveyYasir Jumhaa Maha0Majeed Osama1Taima Alaa2College of Computer Science and Information Technology, University of Al-QadisiyahCollege of Computer Science and Information Technology, University of Al-QadisiyahCollege of Computer Science and Information Technology, University of Al-QadisiyahOne of the factors that kills hundreds of people every year is driving accidents caused by drowsy drivers. There are different methods to prevent this type of accidents. Recently Machine Learning (ML) and Deep Learning (DL) have emerged as very effective and valuable approaches for detecting driver drowsiness. Moreover, the optimization of machine learning (ML) and deep learning (DL) models may be achieved through the utilization of evolutionary algorithms (EA). This survey aims to offer an overview of recent studies in driver drowsiness detection-based machine learning and deep learning models that have been improved by EA. This survey divides the approaches for detecting drowsiness into two groups: those that rely on ML, and DL, and those that rely on models-based deep learning and machine learning that are optimized by evolutionary algorithms.https://www.bio-conferences.org/articles/bioconf/pdf/2024/16/bioconf_iscku2024_00007.pdf |
| spellingShingle | Yasir Jumhaa Maha Majeed Osama Taima Alaa Driver Drowsiness Detection using Evolutionary Machine Learning: A Survey BIO Web of Conferences |
| title | Driver Drowsiness Detection using Evolutionary Machine Learning: A Survey |
| title_full | Driver Drowsiness Detection using Evolutionary Machine Learning: A Survey |
| title_fullStr | Driver Drowsiness Detection using Evolutionary Machine Learning: A Survey |
| title_full_unstemmed | Driver Drowsiness Detection using Evolutionary Machine Learning: A Survey |
| title_short | Driver Drowsiness Detection using Evolutionary Machine Learning: A Survey |
| title_sort | driver drowsiness detection using evolutionary machine learning a survey |
| url | https://www.bio-conferences.org/articles/bioconf/pdf/2024/16/bioconf_iscku2024_00007.pdf |
| work_keys_str_mv | AT yasirjumhaamaha driverdrowsinessdetectionusingevolutionarymachinelearningasurvey AT majeedosama driverdrowsinessdetectionusingevolutionarymachinelearningasurvey AT taimaalaa driverdrowsinessdetectionusingevolutionarymachinelearningasurvey |