Enhancing Road Safety: Real-Time Distracted Driver Detection Using Nvidia Jetson Nano and YOLOv8
Küçük Resim Yok
Tarih
2024
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Ieee
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
This study introduces an innovative approach that combines cutting-edge technology and advanced models for real-time applications. Leveraging the performance of the Nvidia Jetson Nano, alongside an integrated camera and GSM/GPS module, our innovative system demonstrates both its practicality and versatility. Specifically, by employing the YOLOv8 classification model for handling State Farm Distracted Driver Detection data which underscores its adaptability and effectiveness in this critical domain. Additionally, our research thoroughly assesses computational efficiency, exploring both hardware and software-based analysis methods. This work is a cornerstone in harnessing technology for real-world impact, merging innovation with practicality and comprehensive evaluation.
Açıklama
Zooming Innovation in Consumer Technologies Conference (ZINC) -- MAY 22-23, 2024 -- Novi Sad, SERBIA
Anahtar Kelimeler
Deep Learning, YOLOv8, Distracted Driver Detection, Driver Behavior, Vehicle to Everything
Kaynak
2024 Zooming Innovation in Consumer Technologies Conference, Zinc 2024
WoS Q Değeri
N/A
Scopus Q Değeri
N/A
