System-On Based Driver Drowsiness Detection and Warning System
| dc.contributor.author | Yazici, Berkay | |
| dc.contributor.author | Ayhan, Tuba | |
| dc.contributor.author | Özdemir, Arda | |
| dc.date.accessioned | 2023-03-06T06:53:18Z | |
| dc.date.available | 2023-03-06T06:53:18Z | |
| dc.date.issued | 2022 | |
| dc.description.abstract | The aim of this project is to detect the drowsiness level of the driver in the vehicle, to warn the driver and to prevent possible accidents. Percentage Eye Closure (PERCLOS) and Convolutional Neural Network (CNN) are used to detect drowsiness. The system is implemented on Xilinx PYNQ-Z2 development board. The system is tested under real world conditions in real time. A high accuracy rate of 92% and a fast working system with 0.8 s is achieved. A speaker is activated to warn the driver when drowsiness is detected. Moreover, the drowsiness information is sent to the cloud by using a Wi-Fi module. | |
| dc.identifier.citation | Yazici, B., Ozdemir, A., & Ayhan, T. (2022). System-on-Chip Based Driver Drowsiness Detection and Warning System. 2022 Innovations in Intelligent Systems and Applications Conference (ASYU). https://doi.org/10.1109/asyu56188.2022.9925481? | |
| dc.identifier.doi | 10.1109/ASYU56188.2022.9925481 | |
| dc.identifier.isbn | 9781670000000 | |
| dc.identifier.scopus | 2-s2.0-85142701323 | |
| dc.identifier.uri | https://doi.org/10.1109/asyu56188.2022.9925481 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.11779/1917 | |
| dc.language.iso | en | |
| dc.publisher | IEEE | |
| dc.relation.ispartof | 2022 Innovations in Intelligent Systems and Applications Conference (ASYU) | |
| dc.rights | info:eu-repo/semantics/openAccess | |
| dc.subject | Soc | |
| dc.subject | Machine learning | |
| dc.subject | Driver drowsiness detection | |
| dc.subject | Artificial intelligence | |
| dc.title | System-On Based Driver Drowsiness Detection and Warning System | |
| dc.type | Conference Object | |
| dspace.entity.type | Publication | |
| gdc.author.id | Ayhan, Tuba/ 0000-0002-1447-0770 | |
| gdc.author.institutional | Ayhan,Tuba | |
| gdc.bip.impulseclass | C5 | |
| gdc.bip.influenceclass | C5 | |
| gdc.bip.popularityclass | C4 | |
| gdc.coar.access | open access | |
| gdc.coar.type | text::conference output | |
| gdc.description.department | Mühendislik Fakültesi, Makine Mühendisligi Bölümü | |
| gdc.description.endpage | 5 | |
| gdc.description.publicationcategory | Konferans Öğesi - Ulusal - Kurum Öğretim Elemanı | |
| gdc.description.startpage | 1 | |
| gdc.identifier.openalex | W4312343902 | |
| gdc.index.type | Scopus | |
| gdc.oaire.diamondjournal | false | |
| gdc.oaire.impulse | 4.0 | |
| gdc.oaire.influence | 2.949408E-9 | |
| gdc.oaire.isgreen | true | |
| gdc.oaire.keywords | Artificial intelligence | |
| gdc.oaire.keywords | machine learning | |
| gdc.oaire.keywords | SoC | |
| gdc.oaire.keywords | driver drowsiness detection | |
| gdc.oaire.popularity | 6.0105005E-9 | |
| gdc.oaire.publicfunded | false | |
| gdc.oaire.sciencefields | 0301 basic medicine | |
| gdc.oaire.sciencefields | 0303 health sciences | |
| gdc.oaire.sciencefields | 03 medical and health sciences | |
| gdc.openalex.collaboration | National | |
| gdc.openalex.fwci | 0.81131163 | |
| gdc.openalex.normalizedpercentile | 0.71 | |
| gdc.opencitations.count | 0 | |
| gdc.plumx.mendeley | 5 | |
| gdc.plumx.scopuscites | 5 | |
| gdc.publishedmonth | Eylül | |
| gdc.relation.journal | 2022 Innovations in Intelligent Systems and Applications Conference (ASYU) | |
| gdc.scopus.citedcount | 5 | |
| gdc.virtual.author | Ayhan, Tuba | |
| gdc.wos.publishedmonth | Eylül | |
| gdc.yokperiod | YÖK - 2021-22 | |
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