Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.11779/1917
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Yazici, Berkay | - |
dc.contributor.author | Özdemir, Arda | - |
dc.contributor.author | Ayhan, Tuba | - |
dc.date.accessioned | 2023-03-06T06:53:18Z | |
dc.date.available | 2023-03-06T06:53:18Z | |
dc.date.issued | 2022 | - |
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? | en_US |
dc.identifier.isbn | 9781670000000 | - |
dc.identifier.uri | https://hdl.handle.net/20.500.11779/1917 | - |
dc.identifier.uri | https://doi.org/10.1109/asyu56188.2022.9925481 | - |
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. | en_US |
dc.language.iso | en | en_US |
dc.publisher | IEEE | en_US |
dc.rights | info:eu-repo/semantics/openAccess | en_US |
dc.subject | Artificial intelligence | en_US |
dc.subject | driver drowsiness detection | en_US |
dc.subject | machine learning | en_US |
dc.subject | SoC | en_US |
dc.title | System-on-Chip Based Driver Drowsiness Detection and Warning System | en_US |
dc.type | Conference Object | en_US |
dc.identifier.doi | 10.1109/ASYU56188.2022.9925481 | - |
dc.identifier.scopus | 2-s2.0-85142701323 | en_US |
dc.authorid | Ayhan, Tuba/ 0000-0002-1447-0770 | - |
dc.relation.publicationcategory | Konferans Öğesi - Ulusal - Kurum Öğretim Elemanı | en_US |
dc.department | Mühendislik Fakültesi, Makine Mühendisligi Bölümü | en_US |
dc.relation.journal | 2022 Innovations in Intelligent Systems and Applications Conference (ASYU) | en_US |
dc.institutionauthor | Yazici, Berkay, Özdemir, Arda, Ayhan,Tuba | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
item.grantfulltext | open | - |
item.languageiso639-1 | en | - |
item.cerifentitytype | Publications | - |
item.fulltext | With Fulltext | - |
item.openairetype | Conference Object | - |
crisitem.author.dept | 02.05. Department of Electrical and Electronics Engineering | - |
Appears in Collections: | Makine Mühendisliği Bölümü koleksiyonu Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
System-on-Chip_Based_Driver_Drowsiness_Detection_and_Warning_System.pdf | Full Text - Article | 414.38 kB | Adobe PDF | View/Open |
CORE Recommender
Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.